Amazon Elastic Container Service (ECS) is a fully managed container orchestration service that simplifies your deployment, management, and scaling of containerized applications. Whether you are new to Amazon ECS or you already have a use case in mind, choose your own path and follow the curated learning steps to get started.
Learning path 1: Get started with Amazon ECS 101
New to Amazon ECS? Follow this learning path to learn about the features, benefits, and use cases of Amazon ECS. Learn how to launch a frontend and multiple backend services, to deploy, manage, and scale modern container enabled applications, to create task definitions, and leverage Amazon ECS Blueprints to build and deploy a various features on top of Amazon ECS.
Amazon ECS makes it easy to run and scale containerized workloads on AWS. Learn how to create task definitions to run containers using Amazon ECS.
This whitepaper provides guidance for application lifecycle management, security, and architectural software design patterns for container-based applications on AWS.
This last module is designed for Terraform centric developers. In this workshop, you will learn how to leverage Amazon ECS Blueprints to build and deploy various features on top of Amazon ECS.
Learning path 2: Run microservices with serverless containers using Amazon ECS with AWS Fargate
AWS Fargate offers serverless compute to run containers with Amazon ECS, and is the easiest way to launch and run containers on AWS. Follow this path to learn how to break a monolithic application into microservices, run these microservices on Amazon ECS without having to provision or manage Amazon EC2 instances, and leverage Amazon ECS Blueprints to provide solutions addressing CI/CD, observability, security, and cost efficiency.
In this workshop, we will launch a frontend and multiple backend services on Amazon Elastic Container Service, and explore how you might adopt this workflow into your environment.
With Amazon ECS and AWS Fargate, users don't need to manage any middleware, any Amazon EC2 instances, or host OS. Amazon ECS Solution Blueprints, gives you a jumpstart and allows you to learn-by-doing. It codifies best practices, well-designed architecture patterns, and provides end-to-end solutions addressing CI/CD, observability, security, and cost efficiency.
To wrap, take this course to learn how to gain observability into your applications running on Amazon ECS. You will learn how to collect metrics, logs, and traces at the system and application level. Finally, learn how to apply this to identify and correct problems.
Learning path 3: Scale and run web applications
If you’re looking to automatically scale and run your containerized web applications, this is the path for you. Learn how automatic scaling on Amazon ECS works, and how to build and manage applications at scale, in multiple Availability Zones with the performance, scale, reliability, and availability of AWS.
Learn how to make infrastructure choices to support your containerized enterprise applications running on Amazon ECS. In this course, you will learn how to scope requirements based on your application, select the best architecture to support your application, and design reusable infrastructure patterns that are secure, performant, and resilient.
In this course, you will learn how to manage enterprise applications running at scale on Amazon ECS, to build environments that can scale in or out quickly and safely. You will also learn how to differentiate application scaling from infrastructure scaling, and perform testing to identify the best metric for scaling your application.
For more details about how things work under the hood of Amazon ECS and to view best practices to make sure your application is secure, performant, and resilient, use the Official Amazon ECS User Guide and Best Practices to get up to scale quickly.
Learning path 4: Deploy advanced applications using Amazon ECS on Amazon EC2
Need greater control of your Amazon EC2 instances to either support compliance and governance, or just enjoy broader customization options? Follow this learning path to learn how to build, deploy, scale, and manage advanced applications using Amazon ECS on Amazon EC2, optimize cost and performance, take advantage of advanced networking options, run GPU workloads and more.
In this pattern, you will see how to deploy Amazon EC2 instances that have GPUs and use the Amazon GPU Optimized AMI to give your containers access to an attached GPU for hardware acceleration of your computations.
GPUs are designed for general purpose tasks, and therefore aren’t always the most cost effective technique for accelerating your machine learning tasks. In this pattern, learn how to setup AWS Inferentia hardware, and use the AWS Deep Learning Container to run an AWS Neuron powered environment that makes use of purpose-built hardware that accelerates model training and inference, at a cost/performance ratio that beats GPU in many cases.
How do you manage updates and patches to Amazon EC2 hosts when your containers are running across a fleet of Amazon EC2 instances? This pattern demonstrates how to do patches and rolling upgrades to your underlying capacity while avoiding downtime for your applications.
More digital learning with Amazon ECS
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Using containers and microservices effectively usually means there's an image registry being used for deployments. This course introduces you to the Amazon Elastic Container Registry (ECR) and gives examples about how it can be used with Amazon ECS.
Learn more about how to troubleshoot the deployment and performance of your Amazon ECS-based services and how to dig in to get the logs and data you need to keep your applications performing as expected.
Ready to move beyond the UI and start using Amazon ECS more programmatically? This course introduces you too AWS Copilot, a tool for deploying apps and services in a more repeatable, coordinated, and orchestrated way.
When things go wrong, a platform's ability to help customers understand what has happened and how to resolve it becomes key. This course will dig into how to monitor and log performance inside Amazon ECS, and how to optimize the performance of running workloads.