AWS consists of many cloud services that you can use in combinations tailored  to your business or organizational needs. This section introduces the major  AWS services by category. To access the services, you can use the AWS  Management Console, the Command Line Interface, or Software Development  Kits (SDKs).

AWS Management Console

Access and manage Amazon Web Services through the AWS Management  Console, a simple and intuitive user interface. You can also use the AWS  Console Mobile Application to quickly view resources on the go.

AWS Command Line Interface

The AWS Command Line Interface (CLI) is a unified tool to manage your AWS  services. With just one tool to download and configure, you can control multiple  AWS services from the command line and automate them through scripts.

Software Development Kits

Our Software Development Kits (SDKs) simplify using AWS services in your  applications with an Application Program Interface (API) tailored to your  programming language or platform.

Analytics

Amazon Athena

Amazon Athena is an interactive query service that makes it easy to analyze  data in Amazon S3 using standard SQL. Athena is serverless, so there is no  infrastructure to manage, and you pay only for the queries that you run.

Athena is easy to use. Simply point to your data in Amazon S3, define the  schema, and start querying using standard SQL. Most results are delivered  within seconds. With Athena, there’s no need for complex extract, transform,  and load (ETL) jobs to prepare your data for analysis. This makes it easy for  anyone with SQL skills to quickly analyze large-scale datasets.

Athena is out-of-the-box integrated with AWS Glue Data Catalog, allowing you  to create a unified metadata repository across various services, crawl data  sources to discover schemas and populate your Catalog with new and modified  table and partition definitions, and maintain schema versioning. You can also  use Glue’s fully-managed ETL capabilities to transform data or convert it into  columnar formats to optimize cost and improve performance.

Amazon EMR

Amazon EMR provides a managed Hadoop framework that makes it easy, fast,  and cost-effective to process vast amounts of data across dynamically scalable  Amazon EC2 instances. You can also run other popular distributed frameworks  such as Apache Spark, HBase, Presto, and Flink in Amazon EMR, and interact  with data in other AWS data stores such as Amazon S3 and Amazon 

DynamoDB. EMR Notebooks, based on the popular Jupyter Notebook, provide  a development and collaboration environment for ad hoc querying and  exploratory analysis.

Amazon EMR securely and reliably handles a broad set of big data use cases,  including log analysis, web indexing, data transformations (ETL), machine  learning, financial analysis, scientific simulation, and bioinformatics.

Amazon CloudSearch

Amazon CloudSearch is a managed service in the AWS Cloud that makes it  simple and cost-effective to set up, manage, and scale a search solution for your website or application. Amazon CloudSearch supports 34 languages and  popular search features such as highlighting, autocomplete, and geospatial  search.

Amazon Elasticsearch Service

Amazon Elasticsearch Service makes it easy to deploy, secure, operate, and  scale Elasticsearch to search, analyze, and visualize data in real-time. With  Amazon Elasticsearch Service, you get easy-to-use APIs and real-time analytics capabilities to power use-cases such as log analytics, full-text search,  application monitoring, and clickstream analytics, with enterprise-grade  availability, scalability, and security. The service offers integrations with open source tools like Kibana and Logstash for data ingestion and visualization. It  also integrates seamlessly with other AWS services such as Amazon Virtual  Private Cloud (Amazon VPC), AWS Key Management System (AWS KMS),  Amazon Kinesis Data Firehose, AWS Lambda, AWS Identity and Access  Management (IAM), Amazon Cognito, and Amazon CloudWatch, so that you  can go from raw data to actionable insights quickly.

Amazon Kinesis

Amazon Kinesis makes it easy to collect, process, and analyze real-time,  streaming data so you can get timely insights and react quickly to new  information. Amazon Kinesis offers key capabilities to cost-effectively process  streaming data at any scale, along with the flexibility to choose the tools that  best suit the requirements of your application. With Amazon Kinesis, you can  ingest real-time data such as video, audio, application logs, website  clickstreams, and IoT telemetry data for machine learning, analytics, and other  applications. Amazon Kinesis enables you to process and analyze data as it  arrives and respond instantly instead of having to wait until all your data is  collected before the processing can begin.

Amazon Kinesis currently offers four services: Kinesis Data Firehose, Kinesis  Data Analytics, Kinesis Data Streams, and Kinesis Video Streams.

Amazon Kinesis Data Firehose

Amazon Kinesis Data Firehose is the easiest way to reliably load streaming  data into data stores and analytics tools. It can capture, transform, and load  streaming data into Amazon S3, Amazon Redshift, Amazon Elasticsearch  Service, and Splunk, enabling near real-time analytics with existing business  intelligence tools and dashboards you’re already using today. It is a fully  managed service that automatically scales to match the throughput of your data  and requires no ongoing administration. It can also batch, compress, transform,  and encrypt the data before loading it, minimizing the amount of storage used at  the destination and increasing security.

You can easily create a Firehose delivery stream from the AWS Management  Console, configure it with a few clicks, and start sending data to the stream  from hundreds of thousands of data sources to be loaded continuously to AWS—all in just a few minutes. You can also configure your delivery stream to  automatically convert the incoming data to columnar formats like Apache  Parquet and Apache ORC, before the data is delivered to Amazon S3, for cost effective storage and analytics.

Amazon Kinesis Data Analytics

Amazon Kinesis Data Analytics is the easiest way to analyze streaming data,  gain actionable insights, and respond to your business and customer needs in  real time. Amazon Kinesis Data Analytics reduces the complexity of building,  managing, and integrating streaming applications with other AWS services.  SQL users can easily query streaming data or build entire streaming  applications using templates and an interactive SQL editor. Java developers  can quickly build sophisticated streaming applications using open source Java  libraries and AWS integrations to transform and analyze data in real-time.

Amazon Kinesis Data Analytics takes care of everything required to run your  queries continuously and scales automatically to match the volume and  throughput rate of your incoming data.

Amazon Kinesis Data Streams

Amazon Kinesis Data Streams (KDS) is a massively scalable and durable real time data streaming service. KDS can continuously capture gigabytes of data  per second from hundreds of thousands of sources such as website  clickstreams, database event streams, financial transactions, social media  feeds, IT logs, and location-tracking events. The data collected is available in  milliseconds to enable real-time analytics use cases such as real-time  dashboards, real-time anomaly detection, dynamic pricing, and more.

Amazon Kinesis Video Streams

Amazon Kinesis Video Streams makes it easy to securely stream video from  connected devices to AWS for analytics, machine learning (ML), playback, and  other processing. Kinesis Video Streams automatically provisions and  elastically scales all the infrastructure needed to ingest streaming video data  from millions of devices. It also durably stores, encrypts, and indexes video data  in your streams, and allows you to access your data through easy-to-use APIs.  Kinesis Video Streams enables you to playback video for live and on-demand  viewing, and quickly build applications that take advantage of computer vision and video analytics through integration with Amazon Recognition Video, and  libraries for ML frameworks such as Apache MxNet, TensorFlow, and OpenCV.

Amazon Redshift

Amazon Redshift is a fast, scalable data warehouse that makes it simple and  cost-effective to analyze all your data across your data warehouse and data  lake. Redshift delivers ten times faster performance than other data  warehouses by using machine learning, massively parallel query execution, and  columnar storage on high-performance disk. You can setup and deploy a new  data warehouse in minutes, and run queries across petabytes of data in your  Redshift data warehouse, and exabytes of data in your data lake built on  Amazon S3. You can start small for just $0.25 per hour and scale to $250 per  terabyte per year, less than one-tenth the cost of other solutions.

Amazon QuickSight

Amazon QuickSight is a fast, cloud-powered business intelligence (BI) service  that makes it easy for you to deliver insights to everyone in your organization.  QuickSight lets you create and publish interactive dashboards that can be  accessed from browsers or mobile devices. You can embed dashboards into  your applications, providing your customers with powerful self-service analytics.  QuickSight easily scales to tens of thousands of users without any software to  install, servers to deploy, or infrastructure to manage.

AWS Data Pipeline

AWS Data Pipeline is a web service that helps you reliably process and move  data between different AWS compute and storage services, as well as on premises data sources, at specified intervals. With AWS Data Pipeline, you can  regularly access your data where it’s stored, transform and process it at scale,  and efficiently transfer the results to AWS services such as Amazon S3,  Amazon RDS, Amazon DynamoDB, and Amazon EMR.

AWS Data Pipeline helps you easily create complex data processing workloads  that are fault tolerant, repeatable, and highly available. You don’t have to worry  about ensuring resource availability, managing inter-task dependencies,  retrying transient failures or timeouts in individual tasks, or creating a failure  notification system. AWS Data Pipeline also allows you to move and process  data that was previously locked up in on-premises data silos.

AWS Glue

AWS Glue is a fully managed extract, transform, and load (ETL) service that  makes it easy for customers to prepare and load their data for analytics. You  can create and run an ETL job with a few clicks in the AWS Management  Console. You simply point AWS Glue to your data stored on AWS, and AWS  Glue discovers your data and stores the associated metadata (e.g. table  definition and schema) in the AWS Glue Data Catalog. Once cataloged, your  data is immediately searchable, queryable, and available for ETL.

AWS Lake Formation

AWS Lake Formation is a service that makes it easy to set up a secure data  lake in days. A data lake is a centralized, curated, and secured repository that  stores all your data, both in its original form and prepared for analysis. A data  lake enables you to break down data silos and combine different types of  analytics to gain insights and guide better business decisions.

However, setting up and managing data lakes today involves a lot of manual,  complicated, and time-consuming tasks. This work includes loading data from  diverse sources, monitoring those data flows, setting up partitions, turning on 

encryption and managing keys, defining transformation jobs and monitoring  their operation, re-organizing data into a columnar format, configuring access  control settings, deduplicating redundant data, matching linked records,  granting access to data sets, and auditing access over time.

Creating a data lake with Lake Formation is as simple as defining where your  data resides and what data access and security policies you want to apply.  Lake Formation then collects and catalogs data from databases and object  storage, moves the data into your new Amazon S3 data lake, cleans and  classifies data using machine learning algorithms, and secures access to your  sensitive data. Your users can then access a centralized catalog of data which  describes available data sets and their appropriate usage. Your users then  leverage these data sets with their choice of analytics and machine learning  services, like Amazon EMR for Apache Spark, Amazon Redshift, Amazon  Athena, Amazon SageMaker, and Amazon QuickSight.

Amazon Managed Streaming for Kafka (MSK)

Amazon Managed Streaming for Kafka (Amazon MSK) is a fully managed  service that makes it easy for you to build and run applications that use Apache

Kafka to process streaming data. Apache Kafka is an open-source platform for  building real-time streaming data pipelines and applications. With Amazon  MSK, you can use Apache Kafka APIs to populate data lakes, stream changes  to and from databases, and power machine learning and analytics applications.

Apache Kafka clusters are challenging to setup, scale, and manage in  production. When you run Apache Kafka on your own, you need to provision  servers, configure Apache Kafka manually, replace servers when they fail,  orchestrate server patches and upgrades, architect the cluster for high  availability, ensure data is durably stored and secured, setup monitoring and  alarms, and carefully plan scaling events to support load changes. Amazon  Managed Streaming for Kafka makes it easy for you to build and run production  applications on Apache Kafka without needing Apache Kafka infrastructure  management expertise. That means you spend less time managing  infrastructure and more time building applications.

With a few clicks in the Amazon MSK console you can create highly available  Apache Kafka clusters with settings and configuration based on Apache Kafka’s  deployment best practices. Amazon MSK automatically provisions and runs  your Apache Kafka clusters. Amazon MSK continuously monitors cluster health  and automatically replaces unhealthy nodes with no downtime to your  application. In addition, Amazon MSK secures your Apache Kafka cluster by  encrypting data at rest.

Application Integration

AWS Step Functions

AWS Step Functions lets you coordinate multiple AWS services into serverless  workflows so you can build and update apps quickly. Using Step Functions, you  can design and run workflows that stitch together services such as AWS  Lambda and Amazon ECS into feature-rich applications. Workflows are made  up of a series of steps, with the output of one step acting as input into the next.  Application development is simpler and more intuitive using Step Functions,  because it translates your workflow into a state machine diagram that is easy to  understand, easy to explain to others, and easy to change. You can monitor  each step of execution as it happens, which means you can identify and fix  problems quickly. Step Functions automatically triggers and tracks each step,  and retries when there are errors, so your application executes in order and as  expected.

Amazon MQ

Amazon MQ is a managed message broker service for Apache ActiveMQ that  makes it easy to set up and operate message brokers in the cloud. Message  brokers allow different software systems–often using different programming  languages, and on different platforms–to communicate and exchange  information. Amazon MQ reduces your operational load by managing the  provisioning, setup, and maintenance of ActiveMQ, a popular open-source  message broker. Connecting your current applications to Amazon MQ is easy  because it uses industry-standard APIs and protocols for messaging, including  JMS, NMS, AMQP, STOMP, MQTT, and WebSocket. Using standards means  that in most cases, there’s no need to rewrite any messaging code when you  migrate to AWS.

Amazon SQS

Amazon Simple Queue Service (Amazon SQS) is a fully managed message  queuing service that enables you to decouple and scale microservices,  distributed systems, and serverless applications. SQS eliminates the complexity  and overhead associated with managing and operating message oriented  middleware, and empowers developers to focus on differentiating work. Using  SQS, you can send, store, and receive messages between software  components at any volume, without losing messages or requiring other services  to be available. Get started with SQS in minutes using the AWS console,  Command Line Interface or SDK of your choice, and three simple commands.

SQS offers two types of message queues. Standard queues offer maximum  throughput, best-effort ordering, and at-least-once delivery. SQS FIFO queues  are designed to guarantee that messages are processed exactly once, in the  exact order that they are sent.

Amazon SNS

Amazon Simple Notification Service (Amazon SNS) is a highly available,  durable, secure, fully managed pub/sub messaging service that enables you to  decouple microservices, distributed systems, and serverless applications.  Amazon SNS provides topics for high-throughput, push-based, many-to-many  messaging. Using Amazon SNS topics, your publisher systems can fan out  messages to a large number of subscriber endpoints for parallel processing,  including Amazon SQS queues, AWS Lambda functions, and HTTP/S webhooks. Additionally, SNS can be used to fan out notifications to end users  using mobile push, SMS, and email. 

Amazon SWF

Amazon Simple Workflow (Amazon SWF) helps developers build, run, and  scale background jobs that have parallel or sequential steps. You can think of  Amazon SWF as a fully-managed state tracker and task coordinator in the  cloud. If your application’s steps take more than 500 milliseconds to complete,  you need to track the state of processing. If you need to recover or retry if a  task fails, Amazon SWF can help you.

AR and VR

Amazon Sumerian

Amazon Sumerian lets you create and run virtual reality (VR), augmented  reality (AR), and 3D applications quickly and easily without requiring any  specialized programming or 3D graphics expertise. With Sumerian, you can  build highly immersive and interactive scenes that run on popular hardware  such as Oculus Go, Oculus Rift, HTC Vive, HTC Vive Pro, Google Daydream,  and Lenovo Mirage as well as Android and iOS mobile devices. For example,  you can build a virtual classroom that lets you train new employees around the  world, or you can build a virtual environment that enables people to tour a  building remotely. Sumerian makes it easy to create all the building blocks  needed to build highly immersive and interactive 3D experiences including  adding objects (e.g. characters, furniture, and landscape), and designing,  animating, and scripting environments. Sumerian does not require specialized  expertise and you can design scenes directly from your browser.

AWS Cost Management

AWS Cost Explorer

AWS Cost Explorer has an easy-to-use interface that lets you visualize,  understand, and manage your AWS costs and usage over time. Get started  quickly by creating custom reports (including charts and tabular data) that  analyze cost and usage data, both at a high level (e.g., total costs and usage  across all accounts) and for highly-specific requests (e.g., m2.2xlarge costs  within account Y that are tagged “project: secretProject”).

AWS Budgets

AWS Budgets gives you the ability to set custom budgets that alert you when  your costs or usage exceed (or are forecasted to exceed) your budgeted  amount. You can also use AWS Budgets to set RI utilization or coverage  targets and receive alerts when your utilization drops below the threshold you  define. RI alerts support Amazon EC2, Amazon RDS, Amazon Redshift, and  Amazon ElastiCache reservations.

Budgets can be tracked at the monthly, quarterly, or yearly level, and you can  customize the start and end dates. You can further refine your budget to track  costs associated with multiple dimensions, such as AWS service, linked  account, tag, and others. Budget alerts can be sent via email and/or Amazon  Simple Notification Service (SNS) topic.

Budgets can be created and tracked from the AWS Budgets dashboard or via  the Budgets API.

AWS Cost & Usage Report

The AWS Cost & Usage Report is a single location for accessing  comprehensive information about your AWS costs and usage.

The AWS Cost & Usage Report lists AWS usage for each service category  used by an account and its IAM users in hourly or daily line items, as well as  any tags that you have activated for cost allocation purposes. You can also  customize the AWS Cost & Usage Report to aggregate your usage data to the  daily or monthly level.

Reserved Instance (RI) Reporting

AWS provides a number of RI-specific cost management solutions out-of-the box to help you better understand and manage your RIs. Using the RI  Utilization and Coverage reports available in AWS Cost Explorer, you can  visualize your RI data at an aggregate level or inspect a particular RI  subscription. To access the most detailed RI information available, you can  leverage the AWS Cost & Usage Report. You can also set a custom RI  utilization target via AWS Budgets and receive alerts when your utilization drops  below the threshold you define.

Blockchain

Amazon Managed Blockchain

Amazon Managed Blockchain is a fully managed service that makes it easy to  create and manage scalable blockchain networks using the popular open  source frameworks Hyperledger Fabric and Ethereum.

Blockchain makes it possible to build applications where multiple parties can  execute transactions without the need for a trusted, central authority. Today,  building a scalable blockchain network with existing technologies is complex to  set up and hard to manage. To create a blockchain network, each network  member needs to manually provision hardware, install software, create and  manage certificates for access control, and configure networking components.  Once the blockchain network is running, you need to continuously monitor the  infrastructure and adapt to changes, such as an increase in transaction  requests, or new members joining or leaving the network.

Amazon Managed Blockchain is a fully managed service that allows you to set  up and manage a scalable blockchain network with just a few clicks. Amazon  Managed Blockchain eliminates the overhead required to create the network,  and automatically scales to meet the demands of thousands of applications  running millions of transactions. Once your network is up and running, Managed  Blockchain makes it easy to manage and maintain your blockchain network. It  manages your certificates, lets you easily invite new members to join the  network, and tracks operational metrics such as usage of compute, memory,  and storage resources. In addition, Managed Blockchain can replicate an  immutable copy of your blockchain network activity into Amazon Quantum  Ledger Database (QLDB), a fully managed ledger database. This allows you to  easily analyze the network activity outside the network and gain insights into  trends.

Business Applications

Alexa for Business

Alexa for Business is a service that enables organizations and employees to  use Alexa to get more work done. With Alexa for Business, employees can use  Alexa as their intelligent assistant to be more productive in meeting rooms, at  their desks, and even with the Alexa devices they already have at home.

Amazon WorkDocs

Amazon WorkDocs is a fully managed, secure enterprise storage and sharing  service with strong administrative controls and feedback capabilities that  improve user productivity.

Users can comment on files, send them to others for feedback, and upload new  versions without having to resort to emailing multiple versions of their files as  attachments. Users can take advantage of these capabilities wherever they are,  using the device of their choice, including PCs, Macs, tablets, and phones.  Amazon WorkDocs offers IT administrators the option of integrating with  existing corporate directories, flexible sharing policies and control of the location  where data is stored. You can get started using Amazon WorkDocs with a 30- day free trial providing 1 TB of storage per user for up to 50 users.

Amazon WorkMail

Amazon WorkMail is a secure, managed business email and calendar service  with support for existing desktop and mobile email client applications. Amazon  WorkMail gives users the ability to seamlessly access their email, contacts, and  calendars using the client application of their choice, including Microsoft  Outlook, native iOS and Android email applications, any client application  supporting the IMAP protocol, or directly through a web browser. You can  integrate Amazon WorkMail with your existing corporate directory, use email  journaling to meet compliance requirements, and control both the keys that encrypt your data and the location in which your data is stored. You can also  set up interoperability with Microsoft Exchange Server, and programmatically  manage users, groups, and resources using the Amazon WorkMail SDK.

Amazon Chime

Amazon Chime is a communications service that transforms online meetings  with a secure, easy-to-use application that you can trust. Amazon Chime works  seamlessly across your devices so that you can stay connected. You can use  Amazon Chime for online meetings, video conferencing, calls, chat, and to  share content, both inside and outside your organization. 

Amazon Chime works with Alexa for Business, which means you can use Alexa  to start your meetings with your voice. Alexa can start your video meetings in  large conference rooms, and automatically dial into online meetings in smaller  huddle rooms and from your desk.

Compute

Amazon EC2

Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides  secure, resizable compute capacity in the cloud. It is designed to make web scale computing easier for developers.

The Amazon EC2 simple web service interface allows you to obtain and  configure capacity with minimal friction. It provides you with complete control of  your computing resources and lets you run on Amazon’s proven computing  environment. Amazon EC2 reduces the time required to obtain and boot new  server instances (called Amazon EC2 instances) to minutes, allowing you to  quickly scale capacity, both up and down, as your computing requirements  change. Amazon EC2 changes the economics of computing by allowing you to  pay only for capacity that you actually use. Amazon EC2 provides developers  and system administrators the tools to build failure resilient applications and  isolate themselves from common failure scenarios.

Instance types

Amazon EC2 passes on to you the financial benefits of Amazon’s scale. You  pay a very low rate for the compute capacity you actually consume. See  Amazon EC2 Instance Purchasing Options for a more detailed description.

• On-Demand Instances—With On-Demand instances, you pay for  compute capacity by the hour with no long-term commitments. You can  increase or decrease your compute capacity depending on the demands  of your application and only pay the specified hourly rate for the  instances you use. The use of On-Demand instances frees you from  the costs and complexities of planning, purchasing, and maintaining  hardware and transforms what are commonly large fixed costs into much  smaller variable costs. On-Demand instances also remove the need to  buy “safety net” capacity to handle periodic traffic spikes.

• Reserved Instances—Reserved Instances provide you with a significant  discount (up to 75%) compared to On-Demand instance pricing. You  have the flexibility to change families, operating system types, and  tenancies while benefitting from Reserved Instance pricing when you use  Convertible Reserved Instances.

• Spot Instances—Spot Instances are available at up to a 90% discount  compared to On-Demand prices and let you take advantage of unused  EC2 capacity in the AWS Cloud. You can significantly reduce the cost of  running your applications, grow your application’s compute capacity and  throughput for the same budget, and enable new types of cloud  computing applications.

Amazon EC2 Auto Scaling

Amazon EC2 Auto Scaling helps you maintain application availability and allows  you to automatically add or remove EC2 instances according to conditions you  define. You can use the fleet management features of Amazon EC2 Auto  Scaling to maintain the health and availability of your fleet. You can also use the  dynamic and predictive scaling features of Amazon EC2 Auto Scaling to add or remove EC2 instances. Dynamic scaling responds to changing demand and  predictive scaling automatically schedules the right number of EC2 instances  based on predicted demand. Dynamic scaling and predictive scaling can be  used together to scale faster.

Amazon Elastic Container Registry

Amazon Elastic Container Registry (Amazon ECR) is a fully-managed Docker  container registry that makes it easy for developers to store, manage, and  deploy Docker container images. Amazon ECR is integrated with Amazon  Elastic Container Service (Amazon ECS), simplifying your development to  production workflow. Amazon ECR eliminates the need to operate your own  container repositories or worry about scaling the underlying infrastructure.  Amazon ECR hosts your images in a highly available and scalable architecture,  allowing you to reliably deploy containers for your applications. Integration with  AWS Identity and Access Management (IAM) provides resource-level control of  each repository. With Amazon ECR, there are no upfront fees or commitments.  You pay only for the amount of data you store in your repositories and data  transferred to the Internet.

Amazon Elastic Container Service

Amazon Elastic Container Service (Amazon ECS) is a highly scalable, high performance container orchestration service that supports Docker containers  and allows you to easily run and scale containerized applications on AWS.  Amazon ECS eliminates the need for you to install and operate your own

container orchestration software, manage and scale a cluster of virtual  machines, or schedule containers on those virtual machines.

With simple API calls, you can launch and stop Docker-enabled applications,  query the complete state of your application, and access many familiar features  such as IAM roles, security groups, load balancers, Amazon CloudWatch  Events, AWS CloudFormation templates, and AWS CloudTrail logs.

Amazon Elastic Container Service for Kubernetes

Amazon Elastic Container Service for Kubernetes (Amazon EKS) makes it easy  to deploy, manage, and scale containerized applications using Kubernetes on  AWS.

Amazon EKS runs the Kubernetes management infrastructure for you across  multiple AWS availability zones to eliminate a single point of failure. Amazon  EKS is certified Kubernetes conformant so you can use existing tooling and  plugins from partners and the Kubernetes community. Applications running on  any standard Kubernetes environment are fully compatible and can be easily  migrated to Amazon EKS.

Amazon Lightsail

Amazon Lightsail is designed to be the easiest way to launch and manage a  virtual private server with AWS. Lightsail plans include everything you need to  jumpstart your project – a virtual machine, SSD- based storage, data transfer,  DNS management, and a static IP address – for a low, predictable price.

AWS Batch

AWS Batch enables developers, scientists, and engineers to easily and  efficiently run hundreds of thousands of batch computing jobs on AWS. AWS  Batch dynamically provisions the optimal quantity and type of compute  resources (e.g., CPU or memory-optimized instances) based on the volume and  specific resource requirements of the batch jobs submitted. With AWS Batch,  there is no need to install and manage batch computing software or server  clusters that you use to run your jobs, allowing you to focus on analyzing results  and solving problems. AWS Batch plans, schedules, and executes your batch  computing workloads across the full range of AWS compute services and  features, such as Amazon EC2 and Spot Instances.

AWS Elastic Beanstalk

AWS Elastic Beanstalk is an easy-to-use service for deploying and scaling web  applications and services developed with Java, .NET, PHP, Node.js, Python,  Ruby, Go, and Docker on familiar servers such as Apache, Nginx, Passenger,  and Internet Information Services (IIS).

You can simply upload your code, and AWS Elastic Beanstalk automatically  handles the deployment, from capacity provisioning, load balancing, and auto  scaling to application health monitoring. At the same time, you retain full control  over the AWS resources powering your application and can access the  underlying resources at any time.

AWS Fargate

AWS Fargate is a compute engine for Amazon ECS that allows you to  run containers without having to manage servers or clusters. With AWS  Fargate, you no longer have to provision, configure, and scale clusters of virtual  machines to run containers. This removes the need to choose server types,  decide when to scale your clusters, or optimize cluster packing. AWS Fargate  removes the need for you to interact with or think about servers or clusters.  Fargate lets you focus on designing and building your applications instead of  managing the infrastructure that runs them.

Amazon ECS has two modes: Fargate launch type and EC2 launch type. With  Fargate launch type, all you have to do is package your application in  containers, specify the CPU and memory requirements, define networking and  IAM policies, and launch the application. EC2 launch type allows you to have  server-level, more granular control over the infrastructure that runs your  container applications. With EC2 launch type, you can use Amazon ECS to  manage a cluster of servers and schedule placement of containers on the  servers. Amazon ECS keeps track of all the CPU, memory and other resources  in your cluster, and also finds the best server for a container to run on based on  your specified resource requirements. You are responsible for provisioning,  patching, and scaling clusters of servers. You can decide which type of server  to use, which applications and how many containers to run in a cluster to  optimize utilization, and when you should add or remove servers from a cluster.  EC2 launch type gives you more control of your server clusters and provides a  broader range of customization options, which might be required to support  some specific applications or possible compliance and government  requirements.

AWS Lambda

AWS Lambda lets you run code without provisioning or managing servers. You  pay only for the compute time you consume—there is no charge when your  code is not running. With Lambda, you can run code for virtually any type of  application or backend service—all with zero administration. Just upload your  code, and Lambda takes care of everything required to run and scale your code  with high availability. You can set up your code to automatically trigger from  other AWS services, or you can call it directly from any web or mobile app.

AWS Serverless Application Repository

The AWS Serverless Application Repository enables you to quickly deploy code  samples, components, and complete applications for common use cases such  as web and mobile back-ends, event and data processing, logging, monitoring,  IoT, and more. Each application is packaged with an AWS Serverless  Application Model (SAM) template that defines the AWS resources used.  Publicly shared applications also include a link to the application’s source code.  There is no additional charge to use the Serverless Application Repository – you  only pay for the AWS resources used in the applications you deploy.

You can also use the Serverless Application Repository to publish your own  applications and share them within your team, across your organization, or with  the community at large. To share an application you’ve built, publish it to the  AWS Serverless Application Repository.

AWS Outposts

AWS Outposts bring native AWS services, infrastructure, and operating models  to virtually any data center, co-location space, or on-premises facility. You can  use the same APIs, the same tools, the same hardware, and the same  functionality across on-premises and the cloud to deliver a truly consistent  hybrid experience. Outposts can be used to support workloads that need to  remain on-premises due to low latency or local data processing needs.

AWS Outposts come in two variants: 1) VMware Cloud on AWS Outposts  allows you to use the same VMware control plane and APIs you use to run your  infrastructure, 2) AWS native variant of AWS Outposts allows you to use the  same exact APIs and control plane you use to run in the AWS cloud, but on premises. AWS Outposts infrastructure is fully managed, maintained, and supported by  AWS to deliver access to the latest AWS services. Getting started is easy, you  simply log into the AWS Management Console to order your Outposts servers,  choosing from a wide range of compute and storage options. You can order one  or more servers, or quarter, half, and full rack units.

VMware Cloud on AWS

VMware Cloud on AWS is an integrated cloud offering jointly developed by  AWS and VMware delivering a highly scalable, secure and innovative service  that allows organizations to seamlessly migrate and extend their on-premises  VMware vSphere-based environments to the AWS Cloud running on next generation Amazon Elastic Compute Cloud (Amazon EC2) bare metal  infrastructure. VMware Cloud on AWS is ideal for enterprise IT infrastructure  and operations organizations looking to migrate their on-premises vSphere based workloads to the public cloud, consolidate and extend their data center  capacities, and optimize, simplify and modernize their disaster recovery  solutions. VMware Cloud on AWS is delivered, sold, and supported globally by  VMware and its partners with availability in the following AWS Regions: US  East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), Asia Pacific  (Tokyo), Europe (Frankfurt), Europe (Ireland), and Europe (London). With each  release, VMware Cloud on AWS availability will expand into additional global  regions.

VMware Cloud on AWS brings the broad, diverse and rich innovations of AWS  services natively to the enterprise applications running on VMware’s compute,  storage and network virtualization platforms. This allows organizations to easily  and rapidly add new innovations to their enterprise applications by natively  integrating AWS infrastructure and platform capabilities such as AWS Lambda,  Amazon Simple Queue Service (SQS), Amazon S3, Elastic Load Balancing,  Amazon RDS, Amazon DynamoDB, Amazon Kinesis and Amazon Redshift,  among many others.

With VMware Cloud on AWS, organizations can simplify their Hybrid IT  operations by using the same VMware Cloud Foundation technologies including  vSphere, vSAN, NSX, and vCenter Server across their on-premises data  centers and on the AWS Cloud without having to purchase any new or custom  hardware, rewrite applications, or modify their operating models. The service  automatically provisions infrastructure and provides full VM compatibility and  workload portability between your on-premises environments and the AWS

Cloud. With VMware Cloud on AWS, you can leverage AWS’s breadth of  services, including compute, databases, analytics, Internet of Things (IoT),  security, mobile, deployment, application services, and more.

Customer Engagement

Amazon Connect

Amazon Connect is a self-service, cloud-based contact center service that  makes it easy for any business to deliver better customer service at lower cost.  Amazon Connect is based on the same contact center technology used by  Amazon customer service associates around the world to power millions of  customer conversations. The self-service graphical interface in Amazon  Connect makes it easy for non-technical users to design contact flows, manage  agents, and track performance metrics – no specialized skills required. There  are no up-front payments or long-term commitments and no infrastructure to  manage with Amazon Connect; customers pay by the minute for Amazon  Connect usage plus any associated telephony services.

Amazon SES

Amazon Simple Email Service (Amazon SES) is a cloud-based email sending  service designed to help digital marketers and application developers send  marketing, notification, and transactional emails. It is a reliable, cost-effective  service for businesses of all sizes that use email to keep in contact with their  customers.

You can use our SMTP interface or one of the AWS SDKs to integrate Amazon  SES directly into your existing applications. You can also integrate the email  sending capabilities of Amazon SES into the software you already use, such as  ticketing systems and email clients.

See also Amazon Pinpoint.

Database

Amazon Aurora

Amazon Aurora is a MySQL and PostgreSQL compatible relational database  engine that combines the speed and availability of high-end commercial  databases with the simplicity and cost-effectiveness of open source databases.

Amazon Aurora is up to five times faster than standard MySQL databases and  three times faster than standard PostgreSQL databases. It provides the  security, availability, and reliability of commercial databases at 1/10th the cost.  Amazon Aurora is fully managed by Amazon Relational Database Service  (RDS), which automates time-consuming administration tasks like hardware  provisioning, database setup, patching, and backups.

Amazon Aurora features a distributed, fault-tolerant, self-healing storage  system that auto-scales up to 64TB per database instance. It delivers high  performance and availability with up to 15 low-latency read replicas, point-in time recovery, continuous backup to Amazon S3, and replication across three  Availability Zones (AZs).

Amazon RDS

Amazon Relational Database Service (Amazon RDS) makes it easy to set up,  operate, and scale a relational database in the cloud. It provides cost-efficient  and resizable capacity while automating time-consuming administration tasks  such as hardware provisioning, database setup, patching and backups. It frees 

you to focus on your applications so you can give them the fast performance,  high availability, security and compatibility they need.

Amazon RDS is available on several database instance types – optimized for  memory, performance or I/O – and provides you with six familiar database  engines to choose from, including Amazon  

Aurora, PostgreSQL, MySQL, MariaDB, Oracle Database, and SQL Server.  You can use the AWS Database Migration Service to easily migrate or replicate  your existing databases to Amazon RDS.

Amazon RDS on VMware

Amazon Relational Database Service (RDS) on VMware lets you deploy  managed databases in on-premises VMware environments using the Amazon  RDS technology enjoyed by hundreds of thousands of AWS customers.  Amazon RDS provides cost-efficient and resizable capacity while automating  time-consuming administration tasks including hardware provisioning, database setup, patching, and backups, freeing you to focus on your applications. RDS  on VMware brings these same benefits to your on-premises deployments,  making it easy to set up, operate, and scale databases in VMware vSphere  private data centers, or to migrate them to AWS.

RDS on VMware allows you to utilize the same simple interface for managing  databases in on-premises VMware environments as you would use in AWS.  You can easily replicate RDS on VMware databases to RDS instances in AWS,  enabling low-cost hybrid deployments for disaster recovery, read replica  bursting, and optional long-term backup retention in Amazon Simple Storage  Service (Amazon S3).

Amazon DynamoDB

Amazon DynamoDB is a key-value and document database that delivers single digit millisecond performance at any scale. It’s a fully managed, multiregion,  multimaster database with built-in security, backup and restore, and in-memory  caching for internet-scale applications. DynamoDB can handle more than 10  trillion requests per day and support peaks of more than 20 million requests per  second.

Many of the world’s fastest growing businesses such as Lyft, Airbnb, and Redfin  as well as enterprises such as Samsung, Toyota, and Capital One depend on  the scale and performance of DynamoDB to support their mission-critical  workloads.

More than 100,000 AWS customers have chosen DynamoDB as their key-value  and document database for mobile, web, gaming, ad tech, IoT, and other  applications that need low-latency data access at any scale. Create a new table  for your application and let DynamoDB handle the rest.

Amazon ElastiCache

Amazon ElastiCache is a web service that makes it easy to deploy, operate,  and scale an in-memory cache in the cloud. The service improves the  performance of web applications by allowing you to retrieve information from  fast, managed, in-memory caches, instead of relying entirely on slower disk based databases.

Amazon ElastiCache supports two open-source in-memory caching engines:

• Redis – a fast, open source, in-memory data store and cache. Amazon  ElastiCache for Redis is a Redis- compatible in-memory service that  delivers the ease-of-use and power of Redis along with the availability,  reliability, and performance suitable for the most demanding applications.  Both single- node and up to 15-shard clusters are available, enabling  scalability to up to 3.55 TiB of in-memory data. ElastiCache for Redis is  fully managed, scalable, and secure. This makes it an ideal candidate to  power high-performance use cases such as web, mobile apps, gaming,  ad-tech, and IoT.

• Memcached – a widely adopted memory object caching system.  ElastiCache for Memcached is protocol compliant with Memcached, so  popular tools that you use today with existing Memcached environments  will work seamlessly with the service.

Amazon Neptune

Amazon Neptune is a fast, reliable, fully-managed graph database service that  makes it easy to build and run applications that work with highly connected  datasets. The core of Amazon Neptune is a purpose-built, high-performance  graph database engine optimized for storing billions of relationships and  querying the graph with milliseconds latency. Amazon Neptune supports  popular graph models Property Graph and W3C’s RDF, and their respective  query languages Apache TinkerPop Gremlin and SPARQL, allowing you to  easily build queries that efficiently navigate highly connected datasets. Neptune  powers graph use cases such as recommendation engines, fraud detection,  knowledge graphs, drug discovery, and network security.

Amazon Neptune is highly available, with read replicas, point-in-time recovery,  continuous backup to Amazon S3, and replication across Availability Zones.  Neptune is secure with support for encryption at rest. Neptune is fully-managed,  so you no longer need to worry about database management tasks such as  hardware provisioning, software patching, setup, configuration, or backups.

Amazon Quantum Ledger Database (QLDB)

Amazon QLDB is a fully managed ledger database that provides a transparent,  immutable, and cryptographically verifiable transaction log owned by a central  trusted authority. Amazon QLDB tracks each and every application data change  and maintains a complete and verifiable history of changes over time.Ledgers are typically used to record a history of economic and financial activity  in an organization. Many organizations build applications with ledger-like  functionality because they want to maintain an accurate history of their  applications’ data, for example, tracking the history of credits and debits in  banking transactions, verifying the data lineage of an insurance claim, or tracing  movement of an item in a supply chain network. Ledger applications are often  implemented using custom audit tables or audit trails created in relational  databases. However, building audit functionality with relational databases is  time-consuming and prone to human error. It requires custom development,  and since relational databases are not inherently immutable, any unintended  changes to the data are hard to track and verify. Alternatively, blockchain  frameworks, such as Hyperledger Fabric and Ethereum, can also be used as a  ledger. However, this adds complexity as you need to set-up an entire  blockchain network with multiple nodes, manage its infrastructure, and require  the nodes to validate each transaction before it can be added to the ledger.

Amazon QLDB is a new class of database that eliminates the need to engage in  the complex development effort of building your own ledger-like applications.  With QLDB, your data’s change history is immutable – it cannot be altered or  deleted – and using cryptography, you can easily verify that there have been no  unintended modifications to your application’s data. QLDB uses an immutable  transactional log, known as a journal, that tracks each application data change  and maintains a complete and verifiable history of changes over time. QLDB is  easy to use because it provides developers with a familiar SQL-like API, a  flexible document data model, and full support for transactions. QLDB is also  serverless, so it automatically scales to support the demands of your  application. There are no servers to manage and no read or write limits to  configure. With QLDB, you only pay for what you use.

Amazon Timestream

Amazon Timestream is a fast, scalable, fully managed time series database  service for IoT and operational applications that makes it easy to store and  analyze trillions of events per day at 1/10th the cost of relational databases.  Driven by the rise of IoT devices, IT systems, and smart industrial machines,  time-series data — data that measures how things change over time — is one  of the fastest growing data types. Time-series data has specific characteristics  such as typically arriving in time order form, data is append-only, and queries  are always over a time interval. While relational databases can store this data,  they are inefficient at processing this data as they lack optimizations such as storing and retrieving data by time intervals. Timestream is a purpose-built time  series database that efficiently stores and processes this data by time intervals.  With Timestream, you can easily store and analyze log data for DevOps, sensor 

data for IoT applications, and industrial telemetry data for equipment  maintenance. As your data grows over time, Timestream’s adaptive query  processing engine understands its location and format, making your data  simpler and faster to analyze. Timestream also automates rollups, retention,  tiering, and compression of data, so you can manage your data at the lowest  possible cost. Timestream is serverless, so there are no servers to manage. It  manages time-consuming tasks such as server provisioning, software patching,  setup, configuration, or data retention and tiering, freeing you to focus on  building your applications.

Amazon DocumentDB

Amazon DocumentDB (with MongoDB compatibility) is a fast, scalable, highly  available, and fully managed document database service that supports  MongoDB workloads.

Amazon DocumentDB is designed from the ground-up to give you the  performance, scalability, and availability you need when operating mission critical MongoDB workloads at scale. Amazon DocumentDB implements the  Apache 2.0 open source MongoDB 3.6 API by emulating the responses that a  MongoDB client expects from a MongoDB server, allowing you to use your  existing MongoDB drivers and tools with Amazon DocumentDB.

Desktop and App Streaming

Amazon WorkSpaces

Amazon WorkSpaces is a fully managed, secure cloud desktop service. You  can use Amazon WorkSpaces to provision either Windows or Linux desktops in  just a few minutes and quickly scale to provide thousands of desktops to  workers across the globe. You can pay either monthly or hourly, just for the  WorkSpaces you launch, which helps you save money when compared to  traditional desktops and on-premises VDI solutions. Amazon WorkSpaces helps  you eliminate the complexity in managing hardware inventory, OS versions and  patches, and Virtual Desktop Infrastructure (VDI), which helps simplify your  desktop delivery strategy. With Amazon WorkSpaces, your users get a fast,  responsive desktop of their choice that they can access anywhere, anytime,  from any supported device.

Amazon AppStream 2.0

Amazon AppStream 2.0 is a fully managed application streaming service. You  centrally manage your desktop applications on AppStream 2.0 and securely  deliver them to any computer. You can easily scale to any number of users  across the globe without acquiring, provisioning, and operating hardware or  infrastructure. AppStream 2.0 is built on AWS, so you benefit from a data center  and network architecture designed for the most security-sensitive organizations.  Each user has a fluid and responsive experience with your applications,  including GPU-intensive 3D design and engineering ones, because your  applications run on virtual machines (VMs) optimized for specific use cases and  each streaming session automatically adjusts to network conditions.

Enterprises can use AppStream 2.0 to simplify application delivery and  complete their migration to the cloud. Educational institutions can provide every  student access to the applications they need for class on any  computer. Software vendors can use AppStream 2.0 to deliver trials, demos,  and training for their applications with no downloads or installations. They can  also develop a full software-as-a-service (SaaS) solution without rewriting their  application.

Developer Tools

AWS CodeCommit

AWS CodeCommit is a fully-managed source control service that hosts secure  Git-based repositories. It makes it easy for teams to collaborate on code in a  secure and highly scalable ecosystem. CodeCommit eliminates the need to  operate your own source control system or worry about scaling its  infrastructure. You can use CodeCommit to securely store anything from source  code to binaries, and it works seamlessly with your existing Git tools.

AWS CodeBuild

AWS CodeBuild is a fully managed build service that compiles source code,  runs tests, and produces software packages that are ready to deploy. With  CodeBuild, you don’t need to provision, manage, and scale your own build  servers. CodeBuild scales continuously and processes multiple builds  concurrently, so your builds are not left waiting in a queue. You can get started  quickly by using prepackaged build environments, or you can create custom  build environments that use your own build tools.

AWS CodeDeploy

AWS CodeDeploy is a service that automates code deployments to any  instance, including EC2 instances and instances running on premises. AWS  CodeDeploy makes it easier for you to rapidly release new features, helps you  avoid downtime during application deployment, and handles the complexity of  updating your applications. You can use AWS CodeDeploy to automate  software deployments, eliminating the need for error-prone manual operations.  The service scales with your infrastructure so you can easily deploy to one  instance or thousands.

AWS CodePipeline

AWS CodePipeline is a fully managed continuous delivery service that helps  you automate your release pipelines for fast and reliable application and  infrastructure updates. CodePipeline automates the build, test, and deploy  phases of your release process every time there is a code change, based on  the release model you define. This enables you to rapidly and reliably deliver  features and updates. You can easily integrate AWS CodePipeline with third party services such as GitHub or with your own custom plugin. With AWS  CodePipeline, you only pay for what you use. There are no upfront fees or long term commitments.

AWS CodeStar

AWS CodeStar enables you to quickly develop, build, and deploy applications  on AWS. AWS CodeStar provides a unified user interface, enabling you to  easily manage your software development activities in one place. With AWS  CodeStar, you can set up your entire continuous delivery toolchain in minutes,  allowing you to start releasing code faster. AWS CodeStar makes it easy for  your whole team to work together securely, allowing you to easily manage  access and add owners, contributors, and viewers to your projects. Each AWS  CodeStar project comes with a project management dashboard, including an  integrated issue tracking capability powered by Atlassian JIRA Software. With  the AWS CodeStar project dashboard, you can easily track progress across  your entire software development process, from your backlog of work items to  teams’ recent code deployments. For more information, see AWS CodeStar  features.

Amazon Corretto

Amazon Corretto is a no-cost, multiplatform, production-ready distribution of the  Open Java Development Kit (OpenJDK). Corretto comes with long-term support  that will include performance enhancements and security fixes. Amazon runs  Corretto internally on thousands of production services and Corretto is certified  as compatible with the Java SE standard. With Corretto, you can develop and  run Java applications on popular operating systems, including Amazon Linux 2,  Windows, and macOS. Amazon Corretto 8 is in Preview.

AWS Cloud9

AWS Cloud9 is a cloud-based integrated development environment (IDE) that  lets you write, run, and debug your code with just a browser. It includes a code  editor, debugger, and terminal. Cloud9 comes prepackaged with essential tools  for popular programming languages, including JavaScript, Python, PHP, and  more, so you don’t need to install files or configure your development machine  to start new projects. Since your Cloud9 IDE is cloud-based, you can work on  your projects from your office, home, or anywhere using an internet-connected  machine. Cloud9 also provides a seamless experience for developing  serverless applications enabling you to easily define resources, debug, and  switch between local and remote execution of serverless applications. With  Cloud9, you can quickly share your development environment with your team,  enabling you to pair program and track each other’s inputs in real time.

AWS X-Ray

AWS X-Ray helps developers analyze and debug distributed applications in  production or under development, such as those built using a microservices  architecture. With X-Ray, you can understand how your application and its  underlying services are performing so you can identify and troubleshoot the root  cause of performance issues and errors. X-Ray provides an end-to-end view of  requests as they travel through your application, and shows a map of your  application’s underlying components. You can use X- Ray to analyze both  applications in development and in production, from simple three-tier  applications to complex microservices applications consisting of thousands of  services.

Game Tech

Amazon GameLift

Amazon GameLift is a managed service for deploying, operating, and scaling  dedicated game servers for session-based multiplayer games. Amazon  GameLift makes it easy to manage server infrastructure, scale capacity to lower  latency and cost, match players into available game sessions, and defend from  distributed denial-of-service (DDoS) attacks. You pay for the compute  resources and bandwidth your games actually use, without monthly or annual  contracts.

Amazon Lumberyard

Amazon Lumberyard is a free, cross-platform, 3D game engine for you to  create the highest-quality games, connect your games to the vast compute and  storage of the AWS Cloud, and engage fans on Twitch. By starting game  projects with Lumberyard, you can spend more of your time creating great  gameplay and building communities of fans, and less time on the  undifferentiated heavy lifting of building a game engine and managing server  infrastructure.

Internet of Things (IoT)

AWS IoT Core

AWS IoT Core is a managed cloud service that lets connected devices easily  and securely interact with cloud applications and other devices. AWS IoT Core  can support billions of devices and trillions of messages, and can process and  route those messages to AWS endpoints and to other devices reliably and  securely. With AWS IoT Core, your applications can keep track of and  communicate with all your devices, all the time, even when they aren’t  connected.

AWS IoT Core makes it easy to use AWS services like AWS Lambda, Amazon  Kinesis, Amazon S3, Amazon SageMaker, Amazon DynamoDB, Amazon  CloudWatch, AWS CloudTrail, and Amazon QuickSight to build Internet of  Things (IoT) applications that gather, process, analyze and act on data  generated by connected devices, without having to manage any infrastructure.

Amazon FreeRTOS

Amazon FreeRTOS (a:FreeRTOS) is an operating system for microcontrollers  that makes small, low-power edge devices easy to program, deploy, secure,  connect, and manage. Amazon FreeRTOS extends the FreeRTOS kernel, a  popular open source operating system for microcontrollers, with software  libraries that make it easy to securely connect your small, low-power devices to  AWS cloud services like AWS IoT Core or to more powerful edge devices  running AWS IoT Greengrass.

A microcontroller (MCU) is a single chip containing a simple processor that can  be found in many devices, including appliances, sensors, fitness trackers,  industrial automation, and automobiles. Many of these small devices could  benefit from connecting to the cloud or locally to other devices. For example,  smart electricity meters need to connect to the cloud to report on usage, and  building security systems need to communicate locally so that a door will unlock  when you badge in. Microcontrollers have limited compute power and memory  capacity and typically perform simple, functional tasks. Microcontrollers  frequently run operating systems that do not have built-in functionality to  connect to local networks or the cloud, making IoT applications a challenge.  Amazon FreeRTOS helps solve this problem by providing both the core  operating system (to run the edge device) as well as software libraries that  make it easy to securely connect to the cloud (or other edge devices) so you  can collect data from them for IoT applications and take action.

AWS IoT Greengrass

AWS IoT Greengrass seamlessly extends AWS to devices so they can act  locally on the data they generate, while still using the cloud for management,  analytics, and durable storage. With AWS IoT Greengrass, connected devices  can run AWS Lambda functions, execute predictions based on machine  learning models, keep device data in sync, and communicate with other devices  securely – even when not connected to the Internet.

With AWS IoT Greengrass, you can use familiar languages and programming  models to create and test your device software in the cloud, and then deploy it  to your devices. AWS IoT Greengrass can be programmed to filter device data 

and only transmit necessary information back to the cloud. You can also  connect to third-party applications, on-premises software, and AWS services  out-of-the-box with AWS IoT Greengrass Connectors. Connectors also  jumpstart device onboarding with pre-built protocol adapter integrations and allow you to streamline authentication via integration with AWS Secrets  Manager.

AWS IoT 1-Click

AWS IoT 1-Click is a service that enables simple devices to trigger AWS  Lambda functions that can execute an action. AWS IoT 1-Click supported  devices enable you to easily perform actions such as notifying technical  support, tracking assets, and replenishing goods or services. AWS IoT 1-Click  supported devices are ready for use right out of the box and eliminate the need  for writing your own firmware or configuring them for secure connectivity. AWS  IoT 1-Click supported devices can be easily managed. You can easily create  device groups and associate them with a Lambda function that executes your  desired action when triggered. You can also track device health and activity  with the pre-built reports.

AWS IoT Analytics

AWS IoT Analytics is a fully-managed service that makes it easy to run and  operationalize sophisticated analytics on massive volumes of IoT data without  having to worry about the cost and complexity typically required to build an IoT  analytics platform. It is the easiest way to run analytics on IoT data and get  insights to make better and more accurate decisions for IoT applications and  machine learning use cases.

IoT data is highly unstructured which makes it difficult to analyze with traditional analytics and business intelligence tools that are designed to process structured  data. IoT data comes from devices that often record fairly noisy processes  (such as temperature, motion, or sound). The data from these devices can  frequently have significant gaps, corrupted messages, and false readings that  must be cleaned up before analysis can occur. Also, IoT data is often only  meaningful in the context of additional, third party data inputs. For example, to  help farmers determine when to water their crops, vineyard irrigation systems  often enrich moisture sensor data with rainfall data from the vineyard, allowing  for more efficient water usage while maximizing harvest yield.

AWS IoT Analytics automates each of the difficult steps that are required to  analyze data from IoT devices. AWS IoT Analytics filters, transforms, and  enriches IoT data before storing it in a time-series data store for analysis. You  can setup the service to collect only the data you need from your devices, apply  mathematical transforms to process the data, and enrich the data with device-specific metadata such as device type and location before storing the  processed data. Then, you can analyze your data by running ad hoc or  scheduled queries using the built-in SQL query engine, or perform more  complex analytics and machine learning inference. AWS IoT Analytics makes it  easy to get started with machine learning by including pre-built models for  common IoT use cases.

You can also use your own custom analysis, packaged in a container, to  execute on AWS IoT Analytics. AWS IoT Analytics automates the execution of  your custom analyses created in Jupyter Notebook or your own tools (such as  Matlab, Octave, etc.) to be executed on your schedule.

AWS IoT Analytics is a fully managed service that operationalizes analyses and  scales automatically to support up to petabytes of IoT data. With AWS IoT  Analytics, you can analyze data from millions of devices and build fast,  responsive IoT applications without managing hardware or infrastructure.

AWS IoT Button

The AWS IoT Button is a programmable button based on the Amazon Dash  Button hardware. This simple Wi-Fi device is easy to configure, and it’s  designed for developers to get started with AWS IoT Core, AWS Lambda,  Amazon DynamoDB, Amazon SNS, and many other Amazon Web Services  without writing device-specific code.

You can code the button’s logic in the cloud to configure button clicks to count  or track items, call or alert someone, start or stop something, order services, or  even provide feedback. For example, you can click the button to unlock or start  a car, open your garage door, call a cab, call your spouse or a customer service  representative, track the use of common household chores, medications or  products, or remotely control your home appliances.

The button can be used as a remote control for Netflix, a switch for your Philips  Hue light bulb, a check-in/check-out device for Airbnb guests, or a way to order  your favorite pizza for delivery. You can integrate it with third-party APIs like  Twitter, Facebook, Twilio, Slack or even your own company’s applications.  Connect it to things we haven’t even thought of yet.

AWS IoT Device Defender

AWS IoT Device Defender is a fully managed service that helps you secure  your fleet of IoT devices. AWS IoT Device Defender continuously audits your  IoT configurations to make sure that they aren’t deviating from security best  practices. A configuration is a set of technical controls you set to help keep  information secure when devices are communicating with each other and the  cloud. AWS IoT Device Defender makes it easy to maintain and enforce IoT  configurations, such as ensuring device identity, authenticating and authorizing  devices, and encrypting device data. AWS IoT Device Defender continuously  audits the IoT configurations on your devices against a set of predefined  security best practices. AWS IoT Device Defender sends an alert if there are  any gaps in your IoT configuration that might create a security risk, such as  identity certificates being shared across multiple devices or a device with a  revoked identity certificate trying to connect to AWS IoT Core.

AWS IoT Device Defender also lets you continuously monitor security metrics  from devices and AWS IoT Core for deviations from what you have defined as  appropriate behavior for each device. If something doesn’t look right, AWS IoT 

Device Defender sends out an alert so you can take action to remediate the  issue. For example, traffic spikes in outbound traffic might indicate that a device  is participating in a DDoS attack. AWS IoT Greengrass and Amazon FreeRTOS automatically integrate with AWS IoT Device Defender to provide security  metrics from the devices for evaluation.

AWS IoT Device Defender can send alerts to the AWS IoT Console, Amazon  CloudWatch, and Amazon SNS. If you determine that you need to take an  action based on an alert, you can use AWS IoT Device Management to take  mitigating actions such as pushing security fixes.

AWS IoT Device Management

As many IoT deployments consist of hundreds of thousands to millions of  devices, it is essential to track, monitor, and manage connected device fleets.  You need to ensure your IoT devices work properly and securely after they  have been deployed. You also need to secure access to your devices, monitor  health, detect and remotely troubleshoot problems, and manage software and  firmware updates.

AWS IoT Device Management makes it easy to securely onboard, organize,  monitor, and remotely manage IoT devices at scale. With AWS IoT Device Management, you can register your connected devices individually or in bulk,  and easily manage permissions so that devices remain secure. You can also  organize your devices, monitor and troubleshoot device functionality, query the  state of any IoT device in your fleet, and send firmware updates over-the-air  (OTA). AWS IoT Device Management is agnostic to device type and OS, so you  can manage devices from constrained microcontrollers to connected cars all  with the same service. AWS IoT Device Management allows you to scale your  fleets and reduce the cost and effort of managing large and diverse IoT device  deployments.

AWS IoT Events

AWS IoT Events is a fully managed IoT service that makes it easy to detect and  respond to events from IoT sensors and applications. Events are patterns of  data identifying more complicated circumstances than expected, such as  changes in equipment when a belt is stuck or connected motion detectors using  movement signals to activate lights and security cameras. To detect events  before AWS IoT Events, you had to build costly, custom applications to collect  data, apply decision logic to detect an event, and then trigger another  application to react to the event. Using AWS IoT Events, it’s simple to detect  events across thousands of IoT sensors sending different telemetry data, such  as temperature from a freezer, humidity from respiratory equipment, and belt  speed on a motor, and hundreds of equipment management applications. You  simply select the relevant data sources to ingest, define the logic for each event  using simple ‘if-then-else’ statements, and select the alert or custom action to  trigger when an event occurs. AWS IoT Events continuously monitors data from  multiple IoT sensors and applications, and it integrates with other services, such  as AWS IoT Core and AWS IoT Analytics, to enable early detection and unique  insights into events. AWS IoT Events automatically triggers alerts and actions in  response to events based on the logic you define. This helps resolve issues  quickly, reduce maintenance costs, and increase operational efficiency.

AWS IoT SiteWise

AWS IoT SiteWise is a managed service that makes it easy to collect and  organize data from industrial equipment at scale. You can easily monitor  equipment across your industrial facilities to identify waste, such as breakdown  of equipment and processes, production inefficiencies, and defects in products.  Today, getting performance metrics from industrial equipment is tough because  data is often locked into proprietary on-premises data stores and typically requires specialized expertise to retrieve it and put it in a format that is useful  for searching and analysis. IoT SiteWise simplifies this process by providing  software running on a gateway that resides in your facilities and automates the  process of collecting and organizing industrial equipment data. This gateway  securely connects to your on-premises data servers, collects data, and sends  the data to the AWS Cloud. You can run the IoT SiteWise software on an AWS  Snowball Edge gateway or install the IoT SiteWise software on popular third party industrial gateways. These gateways are specifically designed for  industrial environments that are likely already in your facilities connecting your  industrial equipment.

You can use IoT SiteWise to monitor operations across facilities, quickly  compute common industrial performance metrics, and build applications to  analyze industrial equipment data, prevent costly equipment issues, and reduce  production inefficiencies. With IoT SiteWise, you can focus on understanding  and optimizing your operations, rather than building costly in-house data  collection and management applications.

AWS IoT Things Graph

AWS IoT Things Graph is a service that makes it easy to visually connect  different devices and web services to build IoT applications.

IoT applications are being built today using a variety of devices and web  services to automate tasks for a wide range of use cases, such as smart  homes, industrial automation, and energy management. Because there aren’t  any widely adopted standards, it’s difficult today for developers to get devices  from multiple manufacturers to connect to each other as well as with web  services. This forces developers to write lots of code to wire together all of the  devices and web services they need for their IoT application. AWS IoT Things  Graph provides a visual drag-and-drop interface for connecting and  coordinating devices and web services, so you can build IoT applications  quickly. For example, in a commercial agriculture application, you can define  interactions between humidity, temperature, and sprinkler sensors with weather  data services in the cloud to automate watering. You represent devices and  services using pre-built reusable components, called models, that hide low-level  details, such as protocols and interfaces, and are easy to integrate to create  sophisticated workflows.You can get started with AWS IoT Things Graph using these pre-built models  for popular device types, such as switches and programmable logic controllers  (PLCs), or create your own custom model using a GraphQL-based schema  modeling language, and deploy your IoT application to AWS IoT Greengrass enabled devices such as cameras, cable set-top boxes, or robotic arms in just a  few clicks. IoT Greengrass is software that provides local compute and secure  cloud connectivity so devices can respond quickly to local events even without  internet connectivity, and runs on a huge range of devices from a Raspberry Pi  to a server-level appliance. IoT Things Graph applications run on IoT  Greengrass-enabled devices.

AWS Partner Device Catalog

The AWS Partner Device Catalog helps you find devices and hardware to help  you explore, build, and go to market with your IoT solutions. Search for and find  hardware that works with AWS, including development kits and embedded  systems to build new devices, as well as off-the-shelf-devices such as  gateways, edge servers, sensors, and cameras for immediate IoT project  integration. The choice of AWS enabled hardware from our curated catalog of  devices from APN partners can help make the rollout of your IoT projects  easier. All devices listed in the AWS Partner Device Catalog are also available  for purchase from our partners to get you started quickly.

Machine Learning

Amazon SageMaker

Amazon SageMaker is a fully-managed platform that enables developers and  data scientists to quickly and easily build, train, and deploy machine learning  models at any scale. Amazon SageMaker removes all the barriers that typically  slow down developers who want to use machine learning.

Machine learning often feels a lot harder than it should be to most developers  because the process to build and train models, and then deploy them into  production is too complicated and too slow. First, you need to collect and  prepare your training data to discover which elements of your data set are  important. Then, you need to select which algorithm and framework you’ll use.  After deciding on your approach, you need to teach the model how to make  predictions by training, which requires a lot of compute. Then, you need to tune  the model so it delivers the best possible predictions, which is often a tedious and manual effort. After you’ve developed a fully trained model, you need to  integrate the model with your application and deploy this application on  infrastructure that will scale. All of this takes a lot of specialized expertise,  access to large amounts of compute and storage, and a lot of time to  experiment and optimize every part of the process. In the end, it’s not a surprise  that the whole thing feels out of reach for most developers.

Amazon SageMaker removes the complexity that holds back developer  success with each of these steps. Amazon SageMaker includes modules that  can be used together or independently to build, train, and deploy your machine  learning models.

Amazon SageMaker Ground Truth

Amazon SageMaker Ground Truth helps you build highly accurate training  datasets for machine learning quickly. SageMaker Ground Truth offers easy  access to public and private human labelers and provides them with built-in  workflows and interfaces for common labeling tasks. Additionally, SageMaker  Ground Truth can lower your labeling costs by up to 70% using automatic  labeling, which works by training Ground Truth from data labeled by humans so  that the service learns to label data independently.

Successful machine learning models are built on the shoulders of large volumes  of high-quality training data. But, the process to create the training data  necessary to build these models is often expensive, complicated, and time consuming. The majority of models created today require a human to manually  label data in a way that allows the model to learn how to make correct  decisions. For example, building a computer vision system that is reliable  enough to identify objects – such as traffic lights, stop signs, and pedestrians – requires thousands of hours of video recordings that consist of hundreds of  millions of video frames. Each one of these frames needs all of the important  elements like the road, other cars, and signage to be labeled by a human  before any work can begin on the model you want to develop.

Amazon SageMaker Ground Truth significantly reduces the time and effort  required to create datasets for training to reduce costs. These savings are  achieved by using machine learning to automatically label data. The model is  able to get progressively better over time by continuously learning from labels  created by human labelers.Where the labeling model has high confidence in its results based on what it  has learned so far, it will automatically apply labels to the raw data. Where the  labeling model has lower confidence in its results, it will pass the data to  humans to do the labeling. The human-generated labels are provided back to  the labeling model for it to learn from and improve. Over time, SageMaker  Ground Truth can label more and more data automatically and substantially  speed up the creation of training datasets.

Amazon Comprehend

Amazon Comprehend is a natural language processing (NLP) service that uses  machine learning to find insights and relationships in text. No machine learning  experience required.

There is a treasure trove of potential sitting in your unstructured data. Customer  emails, support tickets, product reviews, social media, even advertising copy  represents insights into customer sentiment that can be put to work for your  business. The question is how to get at it? As it turns out, Machine learning is  particularly good at accurately identifying specific items of interest inside vast  swathes of text (such as finding company names in analyst reports), and can  learn the sentiment hidden inside language (identifying negative reviews, or  positive customer interactions with customer service agents), at almost limitless  scale.

Amazon Comprehend uses machine learning to help you uncover the insights  and relationships in your unstructured data. The service identifies the language  of the text; extracts key phrases, places, people, brands, or events;  understands how positive or negative the text is; analyzes text using  tokenization and parts of speech; and automatically organizes a collection of  text files by topic. You can also use AutoML capabilities in Amazon  Comprehend to build a custom set of entities or text classification models that  are tailored uniquely to your organization’s needs.

For extracting complex medical information from unstructured text, you can use  Amazon Comprehend Medical. The service can identify medical information,  such as medical conditions, medications, dosages, strengths, and frequencies  from a variety of sources like doctor’s notes, clinical trial reports, and patient  health records. Amazon Comprehend Medical also identifies the relationship  among the extracted medication and test, treatment and procedure information  for easier analysis. For example, the service identifies a particular dosage, strength, and frequency related to a specific medication from unstructured  clinical notes.

Amazon Lex

Amazon Lex is a service for building conversational interfaces into any  application using voice and text. Lex provides the advanced deep learning  functionalities of automatic speech recognition (ASR) for converting speech to  text, and natural language understanding (NLU) to recognize the intent of the  text, to enable you to build applications with highly engaging user experiences  and lifelike conversational interactions. With Amazon Lex, the same deep  learning technologies that power Amazon Alexa are now available to any  developer, enabling you to quickly and easily build sophisticated, natural  language, conversational bots (“chatbots”).

Speech recognition and natural language understanding are some of the most  challenging problems to solve in computer science, requiring sophisticated  deep learning algorithms to be trained on massive amounts of data and  infrastructure. Amazon Lex democratizes these deep learning technologies by  putting the power of Alexa within reach of all developers. Harnessing these  technologies, Amazon Lex enables you to define entirely new categories of  products made possible through conversational interfaces.

Amazon Polly

Amazon Polly is a service that turns text into lifelike speech. Polly lets you  create applications that talk, enabling you to build entirely new categories of  speech-enabled products. Polly is an Amazon artificial intelligence (AI) service  that uses advanced deep learning technologies to synthesize speech that  sounds like a human voice. Polly includes 47 lifelike voices spread across 24  languages, so you can select the ideal voice and build speech-enabled  applications that work in many different countries.

Amazon Polly delivers the consistently fast response times required to support  real-time, interactive dialog. You can cache and save Polly’s speech audio to  replay offline or redistribute. And Polly is easy to use. You simply send the text  you want converted into speech to the Polly API, and Polly immediately returns  the audio stream to your application so your application can play it directly or  store it in a standard audio file format, such as MP3. With Polly, you only pay for the number of characters you convert to speech,  and you can save and replay Polly’s generated speech. Polly’s low cost per  character converted, and lack of restrictions on storage and reuse of voice  output, make it a cost-effective way to enable Text-to-Speech everywhere.

Amazon Rekognition

Amazon Rekognition is a service that makes it easy to add image analysis to  your applications. With Rekognition, you can detect objects, scenes, and faces  in images. You can also search and compare faces. The Amazon Rekognition  API enables you to quickly add sophisticated deep-learning-based visual search  and image classification to your applications.

Amazon Rekognition is based on the same proven, highly scalable, deep  learning technology developed by Amazon’s computer vision scientists to  analyze billions of images daily for Prime Photos. Amazon Rekognition uses  deep neural network models to detect and label thousands of objects and  scenes in your images, and we are continually adding new labels and facial  recognition features to the service.

The Amazon Rekognition API lets you easily build powerful visual search and  discovery into your applications. With Amazon Rekognition, you only pay for the  images you analyze and the face metadata you store. There are no minimum  fees, and there are no upfront commitments.

Amazon Translate

Amazon Translate is a neural machine translation service that delivers fast,  high-quality, and affordable language translation. Neural machine translation is  a form of language translation automation that uses deep learning models to  deliver more accurate and more natural sounding translation than traditional  statistical and rule-based translation algorithms. Amazon Translate allows you  to localize content – such as websites and applications – for international users,  and to easily translate large volumes of text efficiently.

Amazon Transcribe

Amazon Transcribe is an automatic speech recognition (ASR) service that  makes it easy for developers to add speech-to-text capability to their  applications. Using the Amazon Transcribe API, you can analyze audio files  stored in Amazon S3 and have the service return a text file of the transcribed speech. You can also send a live audio stream to Amazon Transcribe and  receive a stream of transcripts in real time.

Amazon Transcribe can be used for lots of common applications, including the  transcription of customer service calls and generating subtitles on audio and  video content. The service can transcribe audio files stored in common formats,  like WAV and MP3, with time stamps for every word so that you can easily  locate the audio in the original source by searching for the text. Amazon  Transcribe is continually learning and improving to keep pace with the evolution  of language.

Amazon Elastic Inference

Amazon Elastic Inference allows you to attach low-cost GPU-powered  acceleration to Amazon EC2 and Amazon SageMaker instances to reduce the  cost of running deep learning inference by up to 75%. Amazon Elastic Inference  supports TensorFlow, Apache MXNet, and ONNX models, with more  frameworks coming soon.

In most deep learning applications, making predictions using a trained model— a process called inference—can drive as much as 90% of the compute costs of  the application due to two factors. First, standalone GPU instances are  designed for model training and are typically oversized for inference. While  training jobs batch process hundreds of data samples in parallel, most inference  happens on a single input in real time that consumes only a small amount of  GPU compute. Even at peak load, a GPU’s compute capacity may not be fully  utilized, which is wasteful and costly. Second, different models need different  amounts of GPU, CPU, and memory resources. Selecting a GPU instance type  that is big enough to satisfy the requirements of the least used resource often  results in under-utilization of the other resources and high costs.

Amazon Elastic Inference solves these problems by allowing you to attach just  the right amount of GPU-powered inference acceleration to any EC2 or  SageMaker instance type with no code changes. With Amazon Elastic  Inference, you can now choose the instance type that is best suited to the  overall CPU and memory needs of your application, and then separately  configure the amount of inference acceleration that you need to use resources  efficiently and to reduce the cost of running inference.

Amazon Forecast

Amazon Forecast is a fully managed service that uses machine learning to  deliver highly accurate forecasts.

Companies today use everything from simple spreadsheets to complex financial  planning software to attempt to accurately forecast future business outcomes  such as product demand, resource needs, or financial performance. These  tools build forecasts by looking at a historical series of data, which is called time  series data. For example, such tools may try to predict the future sales of a  raincoat by looking only at its previous sales data with the underlying  assumption that the future is determined by the past. This approach can  struggle to produce accurate forecasts for large sets of data that have irregular  trends. Also, it fails to easily combine data series that change over time (such  as price, discounts, web traffic, and number of employees) with relevant  independent variables like product features and store locations.

Based on the same technology used at Amazon.com, Amazon Forecast uses machine learning to combine time series data with additional variables to build  forecasts. Amazon Forecast requires no machine learning experience to get  started. You only need to provide historical data, plus any additional data that  you believe may impact your forecasts. For example, the demand for a  particular color of a shirt may change with the seasons and store location. This  complex relationship is hard to determine on its own, but machine learning is  ideally suited to recognize it. Once you provide your data, Amazon Forecast will  automatically examine it, identify what is meaningful, and produce a forecasting  model capable of making predictions that are up to 50% more accurate than  looking at time series data alone.

Amazon Forecast is a fully managed service, so there are no servers to  provision, and no machine learning models to build, train, or deploy. You pay  only for what you use, and there are no minimum fees and no upfront  commitments.

Amazon Textract

Amazon Textract is a service that automatically extracts text and data from  scanned documents. Amazon Textract goes beyond simple optical character  recognition (OCR) to also identify the contents of fields in forms and information  stored in tables. Many companies today extract data from documents and forms through manual  data entry that’s slow and expensive or through simple optical character  recognition (OCR) software that is difficult to customize. Rules and workflows  for each document and form often need to be hard-coded and updated with  each change to the form or when dealing with multiple forms. If the form  deviates from the rules, the output is often scrambled and unusable.

Amazon Textract overcomes these challenges by using machine learning to  instantly “read” virtually any type of document to accurately extract text and  data without the need for any manual effort or custom code. With Textract you  can quickly automate document workflows, enabling you to process millions of  document pages in hours. Once the information is captured, you can take  action on it within your business applications to initiate next steps for a loan  application or medical claims processing. Additionally, you can create smart  search indexes, build automated approval workflows, and better maintain  compliance with document archival rules by flagging data that may require  redaction.

Amazon Personalize

Amazon Personalize is a machine learning service that makes it easy for  developers to create individualized recommendations for customers using their  applications.

Machine learning is being increasingly used to improve customer engagement  by powering personalized product and content recommendations, tailored  search results, and targeted marketing promotions. However, developing the  machine-learning capabilities necessary to produce these sophisticated  recommendation systems has been beyond the reach of most organizations  today due to the complexity of developing machine learning functionality.  Amazon Personalize allows developers with no prior machine learning  experience to easily build sophisticated personalization capabilities into their  applications, using machine learning technology perfected from years of use on  Amazon.com.

With Amazon Personalize, you provide an activity stream from your application  – page views, signups, purchases, and so forth – as well as an inventory of the  items you want to recommend, such as articles, products, videos, or music. You  can also choose to provide Amazon Personalize with additional demographic  information from your users such as age, or geographic location. Amazon Personalize will process and examine the data, identify what is meaningful,  select the right algorithms, and train and optimize a personalization model that  is customized for your data.

All data analyzed by Amazon Personalize is kept private and secure, and only  used for your customized recommendations. You can start serving your  personalized predictions via a simple API call from inside the virtual private  cloud that the service maintains. You pay only for what you use, and there are  no minimum fees and no upfront commitments.

Amazon Personalize is like having your own Amazon.com machine learning  personalization team at your disposal, 24 hours a day.

Amazon Deep Learning AMIs

The AWS Deep Learning AMIs provide machine learning practitioners and  researchers with the infrastructure and tools to accelerate deep learning in the cloud, at any scale. You can quickly launch Amazon EC2 instances pre installed with popular deep learning frameworks such as Apache MXNet and  Gluon, TensorFlow, Microsoft Cognitive Toolkit, Caffe, Caffe2, Theano, Torch,  PyTorch, Chainer, and Keras to train sophisticated, custom AI models,  experiment with new algorithms, or to learn new skills and techniques

AWS DeepLens

AWS DeepLens helps put deep learning in the hands of developers, literally,  with a fully programmable video camera, tutorials, code, and pre-trained models  designed to expand deep learning skills.

AWS DeepRacer

AWS DeepRacer is a 1/18th scale race car which gives you an interesting and  fun way to get started with reinforcement learning (RL). RL is an advanced  machine learning (ML) technique which takes a very different approach to  training models than other machine learning methods. Its super power is that it  learns very complex behaviors without requiring any labeled training data, and  can make short term decisions while optimizing for a longer term goal.

With AWS DeepRacer, you now have a way to get hands-on with RL,  experiment, and learn through autonomous driving. You can get started with the virtual car and tracks in the cloud-based 3D racing simulator, and for a real-world experience, you can deploy your trained models onto AWS DeepRacer  and race your friends, or take part in the global AWS DeepRacer League.  Developers, the race is on.

Apache MXNet on AWS

Apache MXNet on AWS is a fast and scalable training and inference framework  with an easy-to-use, concise API for machine learning.

MXNet includes the Gluon interface that allows developers of all skill levels to  get started with deep learning on the cloud, on edge devices, and on mobile  apps. In just a few lines of Gluon code, you can build linear regression,  convolutional networks and recurrent LSTMs for object detection, speech  recognition, recommendation, and personalization.

You can get started with MxNet on AWS with a fully-managed experience  using Amazon SageMaker, a platform to build, train, and deploy machine  learning models at scale. Or, you can use the AWS Deep Learning AMIs to  build custom environments and workflows with MxNet as well as other  frameworks including TensorFlow, PyTorch, Chainer, Keras, Caffe, Caffe2, and  Microsoft Cognitive Toolkit.

TensorFlow on AWS

TensorFlow™ enables developers to quickly and easily get started with deep  learning in the cloud. The framework has broad support in the industry and has  become a popular choice for deep learning research and application  development, particularly in areas such as computer vision, natural language  understanding and speech translation.

You can get started on AWS with a fully-managed TensorFlow experience with  Amazon SageMaker, a platform to build, train, and deploy machine learning  models at scale. Or, you can use the AWS Deep Learning AMIs to build custom  environments and workflows with TensorFlow and other popular frameworks  including Apache MXNet, PyTorch, Caffe, Caffe2, Chainer, Gluon, Keras, and  Microsoft Cognitive Toolkit.

AWS Inferentia

AWS Inferentia is a machine learning inference chip designed to deliver high  performance at low cost. AWS Inferentia will support the TensorFlow, Apache MXNet, and PyTorch deep learning frameworks, as well as models that use the  ONNX format.

Making predictions using a trained machine learning model–a process called  inference–can drive as much as 90% of the compute costs of the application.  Using Amazon Elastic Inference, developers can reduce inference costs by up  to 75% by attaching GPU-powered inference acceleration to Amazon EC2 and  Amazon SageMaker instances. However, some inference workloads require an  entire GPU or have extremely low latency requirements. Solving this challenge  at low cost requires a dedicated inference chip.

AWS Inferentia provides high throughput, low latency inference performance at  an extremely low cost. Each chip provides hundreds of TOPS (tera operations  per second) of inference throughput to allow complex models to make fast  predictions. For even more performance, multiple AWS Inferentia chips can be  used together to drive thousands of TOPS of throughput. AWS Inferentia will be  available for use with Amazon SageMaker, Amazon EC2, and Amazon Elastic  Inference.

Management and Governance

Amazon CloudWatch

Amazon CloudWatch is a monitoring and management service built for  developers, system operators, site reliability engineers (SRE), and IT  managers. CloudWatch provides you with data and actionable insights to  monitor your applications, understand and respond to system-wide performance  changes, optimize resource utilization, and get a unified view of operational  health. CloudWatch collects monitoring and operational data in the form of logs,  metrics, and events, providing you with a unified view of AWS resources,  applications and services that run on AWS, and on-premises servers. You can  use CloudWatch to set high resolution alarms, visualize logs and metrics side  by side, take automated actions, troubleshoot issues, and discover insights to  optimize your applications, and ensure they are running smoothly.

AWS Auto Scaling

AWS Auto Scaling monitors your applications and automatically adjusts  capacity to maintain steady, predictable performance at the lowest possible  cost. Using AWS Auto Scaling, it’s easy to setup application scaling for multiple resources across multiple services in minutes. The service provides a simple,  powerful user interface that lets you build scaling plans for resources  including Amazon EC2 instances and Spot Fleets, Amazon ECS tasks, Amazon  DynamoDB tables and indexes, and Amazon Aurora Replicas. AWS Auto  Scaling makes scaling simple with recommendations that allow you to optimize  performance, costs, or balance between them. If you’re already using Amazon  EC2 Auto Scaling to dynamically scale your Amazon EC2 instances, you can  now combine it with AWS Auto Scaling to scale additional resources for other  AWS services. With AWS Auto Scaling, your applications always have the right  resources at the right time.

AWS Control Tower

AWS Control Tower automates the set-up of a baseline environment, or landing  zone, that is a secure, well-architected multi-account AWS environment. The  configuration of the landing zone is based on best practices that have been  established by working with thousands of enterprise customers to create a  secure environment that makes it easier to govern AWS workloads with rules  for security, operations, and compliance.

As enterprises migrate to AWS, they typically have a large number of  applications and distributed teams. They often want to create multiple accounts  to allow their teams to work independently, while still maintaining a consistent  level of security and compliance. In addition, they use AWS’s management and  security services, like AWS Organizations, AWS Service Catalog and AWS  Config, that provide very granular controls over their workloads. They want to  maintain this control, but they also want a way to centrally govern and enforce  the best use of AWS services across all the accounts in their environment.

Control Tower automates the set-up of their landing zone and configures AWS  management and security services based on established best practices in a  secure, compliant, multi-account environment. Distributed teams are able to  provision new AWS accounts quickly, while central teams have the peace of  mind knowing that new accounts are aligned with centrally established,  company-wide compliance policies. This gives you control over your  environment, without sacrificing the speed and agility AWS provides your  development teams.

AWS Systems Manager

AWS Systems Manager gives you visibility and control of your infrastructure on  AWS. Systems Manager provides a unified user interface so you can view  operational data from multiple AWS services and allows you to automate  operational tasks across your AWS resources. With Systems Manager, you can  group resources, like Amazon EC2 instances, Amazon S3 buckets, or Amazon  RDS instances, by application, view operational data for monitoring and  troubleshooting, and take action on your groups of resources. Systems  Manager simplifies resource and application management, shortens the time to  detect and resolve operational problems, and makes it easy to operate and  manage your infrastructure securely at scale.

AWS Systems Manager contains the following tools:

• Resource groups: Lets you create a logical group of resources  associated with a particular workload such as different layers of an  application stack, or production versus development environments. For  example, you can group different layers of an application, such as the  frontend web layer and the backend data layer. Resource groups can be  created, updated, or removed programmatically through the API.

• Insights Dashboard: Displays operational data that the AWS Systems  Manager automatically aggregates for each resource group. Systems  Manager eliminates the need for you to navigate across multiple AWS  consoles to view your operational data. With Systems Manager you can  view API call logs from AWS CloudTrail, resource configuration changes  from AWS Config, software inventory, and patch compliance status by  resource group. You can also easily integrate your AWS  

CloudWatch Dashboards, AWS Trusted Advisor notifications, and AWS  Personal Health Dashboard performance and availability alerts into your  Systems Manager dashboard. Systems Manager centralizes all relevant 

operational data, so you can have a clear view of your infrastructure  compliance and performance.

• Run Command: Provides a simple way of automating common  administrative tasks like remotely executing shell scripts or PowerShell  commands, installing software updates, or making changes to the  configuration of OS, software, EC2 and instances and servers in your on premises data center.

• State Manager: Helps you define and maintain consistent OS  configurations such as firewall settings and anti-malware definitions to  comply with your policies. You can monitor the configuration of a large  set of instances, specify a configuration policy for the instances, and  automatically apply updates or configuration changes.

• Inventory: Helps you collect and query configuration and inventory  information about your instances and the software installed on them. You  can gather details about your instances such as installed applications,  DHCP settings, agent detail, and custom items. You can run queries to  track and audit your system configurations.

• Maintenance Window: Lets you define a recurring window of time to run  administrative and maintenance tasks across your instances. This  ensures that installing patches and updates, or making other  configuration changes does not disrupt business-critical operations. This  helps improve your application availability.

• Patch Manager: Helps you select and deploy operating system and  software patches automatically across large groups of instances. You  can define a maintenance window so that patches are applied only  during set times that fit your needs. These capabilities help ensure that  your software is always up to date and meets your compliance policies.

• Automation: Simplifies common maintenance and deployment tasks,  such as updating Amazon Machine Images (AMIs). Use the Automation  feature to apply patches, update drivers and agents, or bake applications  into your AMI using a streamlined, repeatable, and auditable process.

• Parameter Store: Provides an encrypted location to store important  administrative information such as passwords and database strings. The  Parameter Store integrates with AWS KMS to make it easy to encrypt  the information you keep in the Parameter Store.

• Distributor: Helps you securely distribute and install software packages,  such as software agents. Systems Manager Distributor allows you to  centrally store and systematically distribute software packages while you  maintain control over versioning. You can use Distributor to create and  distribute software packages and then install them using Systems  Manager Run Command and State Manager. Distributor can also use  Identity and Access Management (IAM) policies to control who can  create or update packages in your account. You can use the existing  IAM policy support for Systems Manager Run Command and State  Manager to define who can install packages on your hosts.

• Session Manager: Provides a browser-based interactive shell and CLI  for managing Windows and Linux EC2 instances, without the need to  open inbound ports, manage SSH keys, or use bastion hosts.  Administrators can grant and revoke access to instances through a  central location by using AWS Identity and Access Management  (IAM) policies. This allows you to control which users can access each  instance, including the option to provide non-root access to specified  users. Once access is provided, you can audit which user accessed an  instance and log each command to Amazon S3 or Amazon CloudWatch  Logs using AWS CloudTrail.

AWS CloudFormation

AWS CloudFormation gives developers and systems administrators an easy  way to create and manage a collection of related AWS resources, provisioning  and updating them in an orderly and predictable fashion.

You can use the AWS CloudFormation sample templates or create your own  templates to describe your AWS resources, and any associated dependencies  or runtime parameters, required to run your application. You don’t need to figure  out the order for provisioning AWS services or the subtleties of making those  dependencies work. CloudFormation takes care of this for you. After the AWS  resources are deployed, you can modify and update them in a controlled and  predictable way, in effect applying version control to your AWS infrastructure  the same way you do with your software. You can also visualize your templates  as diagrams and edit them using a drag-and-drop interface with the AWS  CloudFormation Designer.

AWS CloudTrail

AWS CloudTrail is a web service that records AWS API calls for your account  and delivers log files to you. The recorded information includes the identity of  the API caller, the time of the API call, the source IP address of the API caller, 

the request parameters, and the response elements returned by the AWS  service.

With CloudTrail, you can get a history of AWS API calls for your account,  including API calls made using the AWS Management Console, AWS SDKs,  command line tools, and higher-level AWS services (such as AWS  CloudFormation). The AWS API call history produced by CloudTrail enables  security analysis, resource change tracking, and compliance auditing.

AWS Config

AWS Config is a fully managed service that provides you with an AWS resource  inventory, configuration history, and configuration change notifications to enable  security and governance. The Config Rules feature enables you to create rules 

that automatically check the configuration of AWS resources recorded by AWS  Config.

With AWS Config, you can discover existing and deleted AWS resources,  determine your overall compliance against rules, and dive into configuration  details of a resource at any point in time. These capabilities enable compliance  auditing, security analysis, resource change tracking, and troubleshooting.

AWS OpsWorks

AWS OpsWorks is a configuration management service that provides managed  instances of Chef and Puppet. Chef and Puppet are automation platforms that  allow you to use code to automate the configurations of your servers.  OpsWorks lets you use Chef and Puppet to automate how servers are  configured, deployed, and managed across your Amazon EC2 instances or on premises compute environments. OpsWorks has three offerings, AWS  Opsworks for Chef Automate, AWS OpsWorks for Puppet Enterprise, and AWS  OpsWorks Stacks.

AWS Service Catalog

AWS Service Catalog allows organizations to create and manage catalogs of IT  services that are approved for use on AWS. These IT services can include everything from virtual machine images, servers, software, and databases to  complete multi-tier application architectures. AWS Service Catalog allows you  to centrally manage commonly deployed IT services and helps you achieve  consistent governance and meet your compliance requirements, while enabling  users to quickly deploy only the approved IT services they need.

AWS Trusted Advisor

AWS Trusted Advisor is an online resource to help you reduce cost, increase  performance, and improve security by optimizing your AWS environment.  Trusted Advisor provides real-time guidance to help you provision your  resources following AWS best practices.

AWS Personal Health Dashboard

AWS Personal Health Dashboard provides alerts and remediation guidance  when AWS is experiencing events that might affect you. While the Service  Health Dashboard displays the general status of AWS services, Personal  Health Dashboard gives you a personalized view into the performance and  availability of the AWS services underlying your AWS resources. The  dashboard displays relevant and timely information to help you manage events  in progress, and provides proactive notification to help you plan for scheduled  activities. With Personal Health Dashboard, alerts are automatically triggered by  changes in the health of AWS resources, giving you event visibility and  guidance to help quickly diagnose and resolve issues.

AWS Managed Services

AWS Managed Services provides ongoing management of your AWS  infrastructure so you can focus on your applications. By implementing best  practices to maintain your infrastructure, AWS Managed Services helps to  reduce your operational overhead and risk. AWS Managed Services automates  common activities such as change requests, monitoring, patch management,  security, and backup services, and provides full-lifecycle services to provision,  run, and support your infrastructure. Our rigor and controls help to enforce your  corporate and security infrastructure policies, and enables you to develop  solutions and applications using your preferred development approach. AWS  Managed Services improves agility, reduces cost, and unburdens you from  infrastructure operations so you can direct resources toward differentiating your  business.

AWS Console Mobile Application

The AWS Console Mobile Application lets customers view and manage a select  set of resources to support incident response while on-the-go. 

The Console Mobile Application allows AWS customers to monitor resources  through a dedicated dashboard and view configuration details, metrics, and  alarms for select AWS services. The Dashboard provides permitted users with  a single view a resource’s status, with real-time data on Amazon CloudWatch,  Personal Health Dashboard, and AWS Billing and Cost Management.  Customers can view ongoing issues and follow through to the relevant  CloudWatch alarm screen for a detailed view with graphs and configuration  options. In addition, customers can check on the status of specific AWS  services, view detailed resource screens, and perform select actions. 

AWS License Manager

AWS License Manager makes it easier to manage licenses in AWS and on premises servers from software vendors such as Microsoft, SAP, Oracle, and  IBM. AWS License Manager lets administrators create customized licensing  rules that emulate the terms of their licensing agreements, and then enforces  these rules when an instance of EC2 gets launched. Administrators can use  these rules to limit licensing violations, such as using more licenses than an  agreement stipulates or reassigning licenses to different servers on a short-term  basis. The rules in AWS License Manager enable you to limit a licensing breach  by physically stopping the instance from launching or by notifying administrators  about the infringement. Administrators gain control and visibility of all their  licenses with the AWS License Manager dashboard and reduce the risk of non compliance, misreporting, and additional costs due to licensing overages.

AWS License Manager integrates with AWS services to simplify the  management of licenses across multiple AWS accounts, IT catalogs, and on premises, through a single AWS account. License administrators can add rules  in AWS Service Catalog, which allows them to create and manage catalogs of  IT services that are approved for use on all their AWS accounts. Through  seamless integration with AWS Systems Manager and AWS Organizations,  administrators can manage licenses across all the AWS accounts in an  organization and on-premises environments. AWS Marketplace buyers can also  use AWS License Manager to track bring your own license (BYOL) software  obtained from the Marketplace and keep a consolidated view of all their  licenses.

AWS Well-Architected Tool

The AWS Well-Architected Tool helps you review the state of your workloads  and compares them to the latest AWS architectural best practices. The tool is  based on the AWS Well-Architected Framework, developed to help cloud  architects build secure, high-performing, resilient, and efficient application  infrastructure. This Framework provides a consistent approach for customers  and partners to evaluate architectures, has been used in tens of thousands of  workload reviews conducted by the AWS solutions architecture team, and  provides guidance to help implement designs that scale with application needs  over time.

To use this free tool, available in the AWS Management Console, just define  your workload and answer a set of questions regarding operational excellence,  security, reliability, performance efficiency, and cost optimization. The AWS  Well-Architected Tool then provides a plan on how to architect for the cloud  using established best practices.

Media Services

Amazon Elastic Transcoder

Amazon Elastic Transcoder is media transcoding in the cloud. It is designed to  be a highly scalable, easy- to-use, and cost-effective way for developers and  businesses to convert (or transcode) media files from their source format into  versions that will play back on devices like smartphones, tablets, and PCs.

AWS Elemental MediaConnect

AWS Elemental MediaConnect is a high-quality transport service for live video.  Today, broadcasters and content owners rely on satellite networks or fiber  connections to send their high-value content into the cloud or to transmit it to  partners for distribution. Both satellite and fiber approaches are expensive,  require long lead times to set up, and lack the flexibility to adapt to changing  requirements. To be more nimble, some customers have tried to use solutions  that transmit live video on top of IP infrastructure, but have struggled with  reliability and security.

Now you can get the reliability and security of satellite and fiber combined with  the flexibility, agility, and economics of IP-based networks using AWS  Elemental MediaConnect. MediaConnect enables you to build mission-critical live video workflows in a fraction of the time and cost of satellite or fiber  services. You can use MediaConnect to ingest live video from a remote event  site (like a stadium), share video with a partner (like a cable TV distributor), or  replicate a video stream for processing (like an over-the-top service).  MediaConnect combines reliable video transport, highly secure stream sharing,  and real-time network traffic and video monitoring that allow you to focus on  your content, not your transport infrastructure.

AWS Elemental MediaConvert

AWS Elemental MediaConvert is a file-based video transcoding service with  broadcast-grade features. It allows you to easily create video-on-demand  (VOD) content for broadcast and multiscreen delivery at scale. The service  combines advanced video and audio capabilities with a simple web services  interface and pay-as-you-go pricing. With AWS Elemental MediaConvert, you  can focus on delivering compelling media experiences without having to worry  about the complexity of building and operating your own video processing  infrastructure.

AWS Elemental MediaLive

AWS Elemental MediaLive is a broadcast-grade live video processing service. It  lets you create high-quality video streams for delivery to broadcast televisions  and internet-connected multiscreen devices, like connected TVs, tablets, smart  phones, and set-top boxes. The service works by encoding your live video  streams in real-time, taking a larger-sized live video source and compressing it  into smaller versions for distribution to your viewers. With AWS Elemental  MediaLive, you can easily set up streams for both live events and 24×7  channels with advanced broadcasting features, high availability, and pay-as you-go pricing. AWS Elemental MediaLive lets you focus on creating compelling  live video experiences for your viewers without the complexity of building and  operating broadcast-grade video processing infrastructure.

AWS Elemental Media Package

AWS Elemental MediaPackage reliably prepares and protects your video for  delivery over the Internet. From a single video input, AWS Elemental  MediaPackage creates video streams formatted to play on connected TVs,  mobile phones, computers, tablets, and game consoles. It makes it easy to  implement popular video features for viewers (start-over, pause, rewind, etc.), like those commonly found on DVRs. AWS Elemental MediaPackage can also  protect your content using Digital Rights Management (DRM). AWS Elemental  MediaPackage scales automatically in response to load, so your viewers will  always get a great experience without you having to accurately predict in  advance the capacity you’ll need.

AWS Elemental MediaStore

AWS Elemental MediaStore is an AWS storage service optimized for media. It  gives you the performance, consistency, and low latency required to deliver live  streaming video content. AWS Elemental MediaStore acts as the origin store in  your video workflow. Its high performance capabilities meet the needs of the  most demanding media delivery workloads, combined with long-term, cost effective storage.

AWS Elemental MediaTailor

AWS Elemental MediaTailor lets video providers insert individually targeted  advertising into their video streams without sacrificing broadcast-level quality-of service. With AWS Elemental MediaTailor, viewers of your live or on-demand  video each receive a stream that combines your content with ads personalized  to them. But unlike other personalized ad solutions, with AWS Elemental  MediaTailor your entire stream – video and ads – is delivered with broadcast grade video quality to improve the experience for your viewers. AWS Elemental  MediaTailor delivers automated reporting based on both client and server-side  ad delivery metrics, making it easy to accurately measure ad impressions and  viewer behavior. You can easily monetize unexpected high-demand viewing  events with no up-front costs using AWS Elemental MediaTailor. It also  improves ad delivery rates, helping you make more money from every video,  and it works with a wider variety of content delivery networks, ad decision  servers, and client devices.

See also Amazon Kinesis Video Streams.

Migration and Transfer

AWS Migration Hub

AWS Migration Hub provides a single location to track the progress of  application migrations across multiple AWS and partner solutions. Using Migration Hub allows you to choose the AWS and partner migration tools that  best fit your needs, while providing visibility into the status of migrations across  your portfolio of applications. Migration Hub also provides key metrics and  progress for individual applications, regardless of which tools are being used to  migrate them. For example, you might use AWS Database Migration Service,  AWS Server Migration Service, and partner migration tools such as ATADATA  ATAmotion, CloudEndure Live Migration, or RiverMeadow Server Migration  Saas to migrate an application comprised of a database, virtualized web  servers, and a bare metal server. Using Migration Hub, you can view the  migration progress of all the resources in the application. This allows you to  quickly get progress updates across all of your migrations, easily identify and  troubleshoot any issues, and reduce the overall time and effort spent on your  migration projects.

AWS Application Discovery Service

AWS Application Discovery Service helps enterprise customers plan migration  projects by gathering information about their on-premises data centers.

Planning data center migrations can involve thousands of workloads that are  often deeply interdependent. Server utilization data and dependency mapping  are important early first steps in the migration process. AWS Application  Discovery Service collects and presents configuration, usage, and behavior  data from your servers to help you better understand your workloads.

The collected data is retained in encrypted format in an AWS Application  Discovery Service data store. You can export this data as a CSV file and use it  to estimate the Total Cost of Ownership (TCO) of running on AWS and to plan  your migration to AWS. In addition, this data is also available in AWS Migration  Hub, where you can migrate the discovered servers and track their progress as  they get migrated to AWS.

AWS Database Migration Service

AWS Database Migration Service helps you migrate databases to AWS easily  and securely. The source database remains fully operational during the  migration, minimizing downtime to applications that rely on the database. The  AWS Database Migration Service can migrate your data to and from most widely used commercial and open-source databases. The service supports  homogeneous migrations such as Oracle to Oracle, as well as heterogeneous  migrations between different database platforms, such as Oracle to Amazon Aurora or Microsoft SQL Server to MySQL. It also allows you to stream data to  Amazon Redshift from any of the supported sources including Amazon Aurora,  PostgreSQL, MySQL, MariaDB, Oracle, SAP ASE, and SQL Server, enabling  consolidation and easy analysis of data in the petabyte-scale data warehouse. 

AWS Database Migration Service can also be used for continuous data  replication with high availability.

AWS Server Migration Service

AWS Server Migration Service (SMS) is an agentless service which makes it  easier and faster for you to migrate thousands of on-premises workloads to  AWS. AWS SMS allows you to automate, schedule, and track incremental  replications of live server volumes, making it easier for you to coordinate large scale server migrations.

AWS Snowball

AWS Snowball is a petabyte-scale data transport solution that uses secure  appliances to transfer large amounts of data into and out of AWS. The use of  Snowball addresses common challenges with large- scale data transfers  including high network costs, long transfer times, and security concerns.  Transferring data with Snowball is simple, fast, secure, and can be as little as  one-fifth the cost of high-speed Internet.

With Snowball, you don’t need to write any code or purchase any hardware to  transfer your data. Simply create a job in the AWS Management Console and a  Snowball appliance will be automatically shipped to you. Once it arrives, attach  the appliance to your local network, download and run the Snowball client to  establish a connection, and then use the client to select the file directories that  you want to transfer to the appliance. The client will then encrypt and transfer  the files to the appliance at high speed. Once the transfer is complete and the  appliance is ready to be returned, the E Ink shipping label will automatically  update and you can track the job status using the Amazon Simple Notification  Service (Amazon SNS), text messages, or directly in the console.

Snowball uses multiple layers of security designed to protect your data  including tamper-resistant enclosures, 256-bit encryption, and an industry standard Trusted Platform Module (TPM) designed to ensure both security and  full chain of custody of your data. Once the data transfer job has been  processed and verified, AWS performs a software erasure of the Snowball  appliance.

AWS Snowball Edge

AWS Snowball Edge is a data migration and edge computing device that comes  in two options. Snowball Edge Storage Optimized provides 100 TB of capacity  and 24 vCPUs and is well suited for local storage and large scale data transfer.  Snowball Edge Compute Optimized provides 52 vCPUs and an optional GPU  for use cases such as advanced machine learning and full motion video  analysis in disconnected environments. Customers can use these two options  for data collection, machine learning and processing, and storage in  environments with intermittent connectivity (such as manufacturing, industrial,  and transportation) or in extremely remote locations (such as military or  maritime operations) before shipping it back to AWS. These devices may also  be rack mounted and clustered together to build larger, temporary installations.

Snowball Edge supports specific Amazon EC2 instance types as well as AWS  Lambda functions, so customers may develop and test in AWS then deploy  applications on devices in remote locations to collect, pre-process, and return  the data. Common use cases include data migration, data transport, image  collation, IoT sensor stream capture, and machine learning.

AWS Snowmobile

AWS Snowmobile is an exabyte-scale data transfer service used to move  extremely large amounts of data to AWS. You can transfer up to 100 PB per  Snowmobile, a 45-foot long ruggedized shipping container, pulled by a semi trailer truck. Snowmobile makes it easy to move massive volumes of data to the  cloud, including video libraries, image repositories, or even a complete data  center migration. Transferring data with Snowmobile is secure, fast, and cost  effective.

After an initial assessment, a Snowmobile will be transported to your data  center, and AWS personnel will configure it for you so it can be accessed as a  network storage target. When your Snowmobile is on site, AWS personnel will  work with your team to connect a removable, high-speed network switch from  the Snowmobile to your local network. Then you can begin your high-speed  data transfer from any number of sources within your data center to the  Snowmobile. After your data is loaded, the Snowmobile is driven back to AWS  where your data is imported into Amazon S3 or Amazon Glacier.

AWS Snowmobile uses multiple layers of security designed to protect your data  including dedicated security personnel, GPS tracking, alarm monitoring, 24/7

video surveillance, and an optional escort security vehicle while in transit. All  data is encrypted with 256-bit encryption keys managed through AWS KMS and  designed to ensure both security and full chain of custody of your data.

AWS DataSync

AWS DataSync is a data transfer service that makes it easy for you to automate  moving data between on-premises storage and Amazon S3 or Amazon Elastic  File System (Amazon EFS). DataSync automatically handles many of the tasks  related to data transfers that can slow down migrations or burden your IT  operations, including running your own instances, handling encryption,  managing scripts, network optimization, and data integrity validation. You can  use DataSync to transfer data at speeds up to 10 times faster than open-source  tools. DataSync uses an on-premises software agent to connect to your existing  storage or file systems using the Network File System (NFS) protocol, so you  don’t have write scripts or modify your applications to work with AWS APIs. You  can use DataSync to copy data over AWS Direct Connect or internet links to  AWS. The service enables one-time data migrations, recurring data processing  workflows, and automated replication for data protection and recovery. Getting  started with DataSync is easy: Deploy the DataSync agent on premises,  connect it to a file system or storage array, select Amazon EFS or S3 as your  AWS storage, and start moving data. You pay only for the data you copy.

AWS Transfer for SFTP

AWS Transfer for SFTP is a fully managed service that enables the transfer of  files directly into and out of Amazon S3 using the Secure File Transfer Protocol  (SFTP)—also known as Secure Shell (SSH) File Transfer Protocol. AWS helps 

you seamlessly migrate your file transfer workflows to AWS Transfer for  SFTP—by integrating with existing authentication systems, and providing DNS  routing with Amazon Route 53—so nothing changes for your customers and  partners, or their applications. With your data in S3, you can use it with AWS  services for processing, analytics, machine learning, and archiving. Getting  started with AWS Transfer for SFTP (AWS SFTP) is easy; there is no  infrastructure to buy and setup.

Mobile

AWS Amplify

AWS Amplify makes it easy to create, configure, and implement scalable mobile  applications powered by AWS. Amplify seamlessly provisions and manages  your mobile backend and provides a simple framework to easily integrate your  backend with your iOS, Android, Web, and React Native frontends. Amplify also  automates the application release process of both your frontend and backend  allowing you to deliver features faster.

Mobile applications require cloud services for actions that can’t be done directly  on the device, such as offline data synchronization, storage, or data sharing  across multiple users. You often have to configure, set up, and manage multiple  services to power the backend. You also have to integrate each of those  services into your application by writing multiple lines of code. However, as the  number of application features grow, your code and release process becomes  more complex and managing the backend requires more time.

Amplify provisions and manages backends for your mobile applications. You  just select the capabilities you need such as authentication, analytics, or offline  data sync and Amplify will automatically provision and manage the AWS service  that powers each of the capabilities. You can then integrate those capabilities  into your application through the Amplify libraries and UI components.

Amazon Cognito

Amazon Cognito lets you add user sign-up, sign-in, and access control to your  web and mobile apps quickly and easily. With Amazon Cognito, you also have  the option to authenticate users through social identity providers such as  Facebook, Twitter, or Amazon, with SAML identity solutions, or by using your  own identity system. In addition, Amazon Cognito enables you to save data  locally on users’ devices, allowing your applications to work even when the  devices are offline. You can then synchronize data across users’ devices so  that their app experience remains consistent regardless of the device they use.

With Amazon Cognito, you can focus on creating great app experiences instead  of worrying about building, securing, and scaling a solution to handle user  management, authentication, and sync across devices.

Amazon Pinpoint

Amazon Pinpoint makes it easy to send targeted messages to your customers  through multiple engagement channels. Examples of targeted campaigns are  promotional alerts and customer retention campaigns, and transactional  messages are messages such as order confirmations and password reset  messages.

You can integrate Amazon Pinpoint into your mobile and web apps to capture  usage data to provide you with insight into how customers interact with your  apps. Amazon Pinpoint also tracks the ways that your customers respond to the  messages you send—for example, by showing you the number of messages  that were delivered, opened, or clicked. 

You can develop custom audience segments and send them pre-scheduled  targeted campaigns via email, SMS, and push notifications. Targeted  campaigns are useful for sending promotional or educational content to re engage and retain your users. 

You can send transactional messages using the console or the Amazon  Pinpoint REST API. Transactional campaigns can be sent via email, SMS, push  notifications, and voice messages. You can also use the API to build custom  applications that deliver campaign and transactional messages.

AWS Device Farm

AWS Device Farm is an app testing service that lets you test and interact with  your Android, iOS, and web apps on many devices at once, or reproduce issues  on a device in real time. View video, screenshots, logs, and performance data  to pinpoint and fix issues before shipping your app.

AWS AppSync

AWS AppSync is a serverless back-end for mobile, web, and enterprise  applications.

AWS AppSync makes it easy to build data driven mobile and web applications  by handling securely all the application data management tasks like online and  offline data access, data synchronization, and data manipulation across multiple  data sources. AWS AppSync uses GraphQL, an API query language designed  to build client applications by providing an intuitive and flexible syntax for  describing their data requirement.

Networking and Content Delivery

Amazon VPC

Amazon Virtual Private Cloud (Amazon VPC) lets you provision a logically  isolated section of the AWS Cloud where you can launch AWS resources in a  virtual network that you define. You have complete control over your virtual  networking environment, including selection of your own IP address range,  creation of subnets, and configuration of route tables and network gateways.  You can use both IPv4 and IPv6 in your VPC for secure and easy access to  resources and applications.

You can easily customize the network configuration for your VPC. For example,  you can create a public- facing subnet for your web servers that has access to  the Internet, and place your backend systems, such as databases or application  servers, in a private-facing subnet with no Internet access. You can leverage  multiple layers of security (including security groups and network access control  lists) to help control access to EC2 instances in each subnet.

Additionally, you can create a hardware virtual private network (VPN)  connection between your corporate data center and your VPC and leverage the  AWS Cloud as an extension of your corporate data center.

Amazon CloudFront

Amazon CloudFront is a fast content delivery network (CDN) service that  securely delivers data, videos, applications, and APIs to customers globally with  low latency, high transfer speeds, all within a developer-friendly environment.  CloudFront is integrated with AWS – both physical locations that are directly  connected to the AWS global infrastructure, as well as other AWS services.  CloudFront works seamlessly with services including AWS Shield for DDoS  mitigation, Amazon S3, Elastic Load Balancing or Amazon EC2 as origins for  your applications, and Lambda@Edge to run custom code closer to customers’  users and to customize the user experience.

You can get started with the Content Delivery Network in minutes, using the  same AWS tools that you’re already familiar with: APIs, AWS Management  Console, AWS CloudFormation, CLIs, and SDKs. Amazon’s CDN offers a  simple, pay-as-you-go pricing model with no upfront fees or required long-term

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contracts, and support for the CDN is included in your existing AWS Support  subscription.

Amazon Route 53

Amazon Route 53 is a highly available and scalable cloud Domain Name  System (DNS) web service. It is designed to give developers and businesses  an extremely reliable and cost-effective way to route end users to Internet  applications by translating human readable names, such as www.example.com,  into the numeric IP addresses, such as 192.0.2.1, that computers use to  connect to each other. Amazon Route 53 is fully compliant with IPv6 as well.

Amazon Route 53 effectively connects user requests to infrastructure running in  AWS—such as EC2 instances, Elastic Load Balancing load balancers, or  Amazon S3 buckets—and can also be used to route users to infrastructure  outside of AWS. You can use Amazon Route 53 to configure DNS health  checks to route traffic to healthy endpoints or to independently monitor the  health of your application and its endpoints. Amazon Route 53 traffic flow  makes it easy for you to manage traffic globally through a variety of routing  types, including latency-based routing, Geo DNS, and weighted round robin— all of which can be combined with DNS Failover in order to enable a variety of  low-latency, fault-tolerant architectures. Using Amazon Route 53 traffic flow’s  simple visual editor, you can easily manage how your end users are routed to  your application’s endpoints—whether in a single AWS Region or distributed  around the globe. Amazon Route 53 also offers Domain Name Registration— you can purchase and manage domain names such as example.com and  Amazon Route 53 will automatically configure DNS settings for your domains.

AWS PrivateLink

AWS PrivateLink simplifies the security of data shared with cloud-based  applications by eliminating the exposure of data to the public Internet. AWS  PrivateLink provides private connectivity between VPCs, AWS services, and  on-premises applications, securely on the Amazon network. AWS PrivateLink  makes it easy to connect services across different accounts and VPCs to  significantly simplify the network architecture.

AWS Direct Connect

AWS Direct Connect makes it easy to establish a dedicated network connection  from your premises to AWS. Using AWS Direct Connect, you can establish private connectivity between AWS and your data center, office, or co-location  environment, which in many cases can reduce your network costs, increase  bandwidth throughput, and provide a more consistent network experience than  Internet-based connections.

AWS Direct Connect lets you establish a dedicated network connection  between your network and one of the AWS Direct Connect locations. Using  industry standard 802.1Q virtual LANS (VLANs), this dedicated connection can  be partitioned into multiple virtual interfaces. This allows you to use the same  connection to access public resources, such as objects stored in Amazon S3  using public IP address space, and private resources such as EC2 instances running within a VPC using private IP address space, while maintaining network  separation between the public and private environments. Virtual interfaces can  be reconfigured at any time to meet your changing needs.

AWS Global Accelerator

AWS Global Accelerator is a networking service that improves the availability  and performance of the applications that you offer to your global users.

Today, if you deliver applications to your global users over the public internet,  your users might face inconsistent availability and performance as they traverse  through multiple public networks to reach your application. These public  networks are often congested and each hop can introduce availability and  performance risk. AWS Global Accelerator uses the highly available and  congestion-free AWS global network to direct internet traffic from your users to  your applications on AWS, making your users’ experience more consistent.

To improve the availability of your application, you must monitor the health of  your application endpoints and route traffic only to healthy endpoints. AWS  Global Accelerator improves application availability by continuously monitoring  the health of your application endpoints and routing traffic to the closest healthy  endpoints.

AWS Global Accelerator also makes it easier to manage your global  applications by providing static IP addresses that act as a fixed entry point to  your application hosted on AWS which eliminates the complexity of managing  specific IP addresses for different AWS Regions and Availability Zones. AWS  Global Accelerator is easy to set up, configure and manage.

Amazon API Gateway

Amazon API Gateway is a fully managed service that makes it easy for  developers to create, publish, maintain, monitor, and secure APIs at any scale.  With a few clicks in the AWS Management Console, you can create an API that  acts as a “front door” for applications to access data, business logic, or  functionality from your back-end services, such as workloads running on  Amazon EC2, code running on AWS Lambda, or any web application. Amazon  API Gateway handles all the tasks involved in accepting and processing up to  hundreds of thousands of concurrent API calls, including traffic management,  authorization and access control, monitoring, and API version management.

AWS Transit Gateway

AWS Transit Gateway is a service that enables customers to connect their  Amazon Virtual Private Clouds (VPCs) and their on-premises networks to a  single gateway. As you grow the number of workloads running on AWS, you  need to be able to scale your networks across multiple accounts and Amazon  VPCs to keep up with the growth. Today, you can connect pairs of Amazon  VPCs using peering. However, managing point-to-point connectivity across  many Amazon VPCs, without the ability to centrally manage the connectivity  policies, can be operationally costly and cumbersome. For on-premises  connectivity, you need to attach your AWS VPN to each individual Amazon  VPC. This solution can be time consuming to build and hard to manage when  the number of VPCs grows into the hundreds.

With AWS Transit Gateway, you only have to create and manage a single  connection from the central gateway in to each Amazon VPC, on-premises data  center, or remote office across your network. Transit Gateway acts as a hub  that controls how traffic is routed among all the connected networks which act  like spokes. This hub and spoke model significantly simplifies management and  reduces operational costs because each network only has to connect to the  Transit Gateway and not to every other network. Any new VPC is simply  connected to the Transit Gateway and is then automatically available to every  other network that is connected to the Transit Gateway. This ease of  connectivity makes it easy to scale your network as you grow.

AWS App Mesh

AWS App Mesh makes it easy to monitor and control microservices running on  AWS. App Mesh standardizes how your microservices communicate, giving you  end-to-end visibility and helping to ensure high-availability for your applications.

Modern applications are often composed of multiple microservices that each  perform a specific function. This architecture helps to increase the availability  and scalability of the application by allowing each component to scale  independently based on demand, and automatically degrading functionality  when a component fails instead of going offline. Each microservice interacts  with all the other microservices through an API. As the number of microservices  grows within an application, it becomes increasingly difficult to pinpoint the  exact location of errors, re-route traffic after failures, and safely deploy code  changes. Previously, this has required you to build monitoring and control logic  directly into your code and redeploy your microservices every time there are  changes.

AWS App Mesh makes it easy to run microservices by providing consistent  visibility and network traffic controls for every microservice in an application.  App Mesh removes the need to update application code to change how  monitoring data is collected or traffic is routed between microservices. App  Mesh configures each microservice to export monitoring data and implements  consistent communications control logic across your application. This makes it  easy to quickly pinpoint the exact location of errors and automatically re-route  network traffic when there are failures or when code changes need to be  deployed.

You can use App Mesh with Amazon ECS and Amazon EKS to better run  containerized microservices at scale. App Mesh uses the open source Envoy  proxy, making it compatible with a wide range of AWS partner and open source  tools for monitoring microservices.

AWS Cloud Map

AWS Cloud Map is a cloud resource discovery service. With Cloud Map, you  can define custom names for your application resources, and it maintains the  updated location of these dynamically changing resources. This increases your  application availability because your web service always discovers the most up to-date locations of its resources.

Modern applications are typically composed of multiple services that are  accessible over an API and perform a specific function. Each service interacts  with a variety of other resources such as databases, queues, object stores, and  customer-defined microservices, and they also need to be able to find the  location of all the infrastructure resources on which it depends, in order to  function. You typically manually manage all these resource names and their  locations within the application code. However, manual resource management  becomes time consuming and error-prone as the number of dependent  infrastructure resources increases or the number of microservices dynamically  scale up and down based on traffic. You can also use third-party service  discovery products, but this requires installing and managing additional  software and infrastructure.

Cloud Map allows you to register any application resources such as databases,  queues, microservices, and other cloud resources with custom names. Cloud  Map then constantly checks the health of resources to make sure the location is  up-to-date. The application can then query the registry for the location of the  resources needed based on the application version and deployment  environment.

Elastic Load Balancing

Elastic Load Balancing (ELB) automatically distributes incoming application  traffic across multiple targets, such as Amazon EC2 instances, containers, and  IP addresses. It can handle the varying load of your application traffic in a single  Availability Zone or across multiple Availability Zones. Elastic Load Balancing  offers three types of load balancers that all feature the high availability,  automatic scaling, and robust security necessary to make your applications fault  tolerant.

• Application Load Balancer is best suited for load balancing of HTTP and  HTTPS traffic and provides advanced request routing targeted at the  delivery of modern application architectures, including microservices and  containers. Operating at the individual request level (Layer 7),  Application Load Balancer routes traffic to targets within Amazon Virtual  Private Cloud (Amazon VPC) based on the content of the request.

• Network Load Balancer is best suited for load balancing of TCP traffic  where extreme performance is required. Operating at the connection  level (Layer 4), Network Load Balancer routes traffic to targets within  Amazon Virtual Private Cloud (Amazon VPC) and is capable of handling  millions of requests per second while maintaining ultra-low latencies.  Network Load Balancer is also optimized to handle sudden and volatile  traffic patterns.

• Classic Load Balancer provides basic load balancing across multiple  Amazon EC2 instances and operates at both the request level and  connection level. Classic Load Balancer is intended for applications that  were built within the EC2-Classic network.

Robotics

AWS RoboMaker

AWS RoboMaker is a service that makes it easy to develop, test, and deploy  intelligent robotics applications at scale. RoboMaker extends the most widely  used open-source robotics software framework, Robot Operating System  (ROS), with connectivity to cloud services. This includes AWS machine learning  services, monitoring services, and analytics services that enable a robot to  stream data, navigate, communicate, comprehend, and learn. RoboMaker  provides a robotics development environment for application development, a  robotics simulation service to accelerate application testing, and a robotics fleet  management service for remote application deployment, update, and  management.

Robots are machines that sense, compute, and take action. Robots need  instructions to accomplish tasks, and these instructions come in the form of  applications that developers code to determine how the robot will behave.  Receiving and processing sensor data, controlling actuators for movement, and  performing a specific task are all functions that are typically automated by these  intelligent robotics applications. Intelligent robots are being increasingly used in  warehouses to distribute inventory, in homes to carry out tedious housework,  and in retail stores to provide customer service. Robotics applications use  machine learning in order to perform more complex tasks like recognizing an  object or face, having a conversation with a person, following a spoken  command, or navigating autonomously. Until now, developing, testing, and  deploying intelligent robotics applications was difficult and time consuming.

Global Infrastructure

AWS serves over a million active customers in more than 190 countries. We are  steadily expanding global infrastructure to help our customers achieve lower  latency and higher throughput, and to ensure that their data resides only in the  AWS Region they specify. As our customers grow their businesses, AWS will  continue to provide infrastructure that meets their global requirements.

The AWS Cloud infrastructure is built around AWS Regions and Availability  Zones. An AWS Region is a physical location in the world where we have  multiple Availability Zones. Availability Zones consist of one or more discrete  data centers, each with redundant power, networking, and connectivity, housed  in separate facilities. These Availability Zones offer you the ability to operate  production applications and databases that are more highly available, fault  tolerant, and scalable than would be possible from a single data center. The  AWS Cloud operates in over 60 Availability Zones within over 20 geographic  Regions around the world, with announced plans for more Availability Zones  and Regions. For more information on the AWS Cloud Availability Zones and  AWS Regions, see AWS Global Infrastructure.

Each Amazon Region is designed to be completely isolated from the other  Amazon Regions. This achieves the greatest possible fault tolerance and  stability. Each Availability Zone is isolated, but the Availability Zones in a  Region are connected through low-latency links. AWS provides you with the  flexibility to place instances and store data within multiple geographic regions  as well as across multiple Availability Zones within each AWS Region. Each  Availability Zone is designed as an independent failure zone. This means that  Availability Zones are physically separated within a typical metropolitan region  and are located in lower risk flood plains (specific flood zone categorization  varies by AWS Region). In addition to discrete uninterruptable power supply  (UPS) and onsite backup generation facilities, data centers located in different  Availability Zones are designed to be supplied by independent substations to  reduce the risk of an event on the power grid impacting more than one  Availability Zone. Availability Zones are all redundantly connected to multiple  tier-1 transit providers.

Security and Compliance

Security

Cloud security at AWS is the highest priority. As an AWS customer, you will  benefit from a data center and network architecture built to meet the  requirements of the most security-sensitive organizations. Security in the cloud  is much like security in your on-premises data centers—only without the costs  of maintaining facilities and hardware. In the cloud, you don’t have to manage  physical servers or storage devices. Instead, you use software-based security  tools to monitor and protect the flow of information into and of out of your cloud  resources.

An advantage of the AWS Cloud is that it allows you to scale and innovate,  while maintaining a secure environment and paying only for the services you  use. This means that you can have the security you need at a lower cost than in  an on-premises environment.

As an AWS customer you inherit all the best practices of AWS policies,  architecture, and operational processes built to satisfy the requirements of our  most security-sensitive customers. Get the flexibility and agility you need in  security controls.

The AWS Cloud enables a shared responsibility model. While AWS manages  security of the cloud, you are responsible for security in the cloud. This means  that you retain control of the security you choose to implement to protect your  own content, platform, applications, systems, and networks no differently than  you would in an on-site data center.

AWS provides you with guidance and expertise through online resources,  personnel, and partners. AWS provides you with advisories for current issues,  plus you have the opportunity to work with AWS when you encounter security  issues.

You get access to hundreds of tools and features to help you to meet your  security objectives. AWS provides security-specific tools and features across  network security, configuration management, access control, and data  encryption.

Finally, AWS environments are continuously audited, with certifications from  accreditation bodies across geographies and verticals. In the AWS environment, you can take advantage of automated tools for asset inventory  and privileged access reporting.

Benefits of AWS Security

• Keep Your Data Safe: The AWS infrastructure puts strong safeguards in  place to help protect your privacy. All data is stored in highly secure  AWS data centers.

• Meet Compliance Requirements: AWS manages dozens of  compliance programs in its infrastructure. This means that segments of  your compliance have already been completed.

• Save Money: Cut costs by using AWS data centers. Maintain the  highest standard of security without having to manage your own facility

• Scale Quickly: Security scales with your AWS Cloud usage. No matter  the size of your business, the AWS infrastructure is designed to keep  your data safe.

Compliance

AWS Cloud Compliance enables you to understand the robust controls in place  at AWS to maintain security and data protection in the cloud. As systems are  built on top of AWS Cloud infrastructure, compliance responsibilities will be  shared. By tying together governance-focused, audit-friendly service features  with applicable compliance or audit standards, AWS Compliance enablers build  on traditional programs. This helps customers to establish and operate in an  AWS security control environment.

The IT infrastructure that AWS provides to its customers is designed and  managed in alignment with best security practices and a variety of IT security  standards. The following is a partial list of assurance programs with which AWS  complies:

• SOC 1/ISAE 3402, SOC 2, SOC 3

• FISMA, DIACAP, and FedRAMP

• PCI DSS Level 1

• ISO 9001, ISO 27001, ISO 27017, ISO 27018

AWS provides customers a wide range of information on its IT control  environment in whitepapers, reports, certifications, accreditations, and other  third-party attestations. More information is available in the Risk and  Compliance whitepaper and the AWS Security Center.