📖 What is AWS Fargate?

AWS Fargate is a serverless compute engine for containers that works with both Amazon ECS and Amazon EKS. It eliminates the need to provision and manage servers, allowing you to specify and run containers without managing the underlying EC2 instances.

🥋 Sensei Says:

"Whenever you see the phrase 'serverless containers' in a scenario, Fargate is almost certainly the correct answer."

📚 Certification: AWS Certified Cloud Practitioner (CLF-C02)

🔑 What are the Key Concepts of AWS Fargate?

  • Serverless nature means you no longer need to provision, configure, or patch EC2 instances to run your containerized applications.
  • Fargate integrates with both Amazon ECS and Amazon EKS, providing a consistent serverless compute experience regardless of the orchestrator used.
  • Resource management is handled at the task level, where you specify the exact amount of vCPU and memory required for each container.
  • The pricing model is based on the resources requested for the running task, ensuring you only pay for what your containers actually use.

🎯 How does AWS Fargate appear on the CLF-C02 Exam?

A scenario might describe a company wanting to run Docker containers while minimizing operational overhead by avoiding the management, patching, and scaling of underlying virtual machine instances. In this case, Fargate is the ideal serverless solution.

You may be asked to identify the correct compute option for a developer who wants to deploy a containerized application quickly without the burden of managing, scaling, or patching a cluster of EC2 servers.

❓ Frequently Asked Questions

Does Fargate replace Amazon ECS or Amazon EKS?

No, Fargate is a launch type, not a replacement. ECS and EKS are the orchestration services that manage your containers, while Fargate is the serverless compute engine that executes them without requiring EC2 instances.


When should I use the EC2 launch type instead of Fargate?

Use the EC2 launch type when you require full control over the underlying server instances, need specific GPU hardware, or want to utilize existing Reserved Instances to optimize your long-term costs.

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