Fargate serverless containers in AWS - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is AWS Fargate?

AWS Fargate is a serverless compute engine for containers that lets you run containers without managing servers or clusters.

beginner

How does Fargate simplify container management?

Fargate removes the need to provision, configure, or scale virtual machines. You just define your container and Fargate runs it for you.

intermediate

What are the main components you need to run a container on Fargate?

You need a task definition (which describes your container), and a cluster where Fargate runs your tasks.

intermediate

Can you explain the difference between Fargate and EC2 launch types?

Fargate runs containers without managing servers, while EC2 launch type requires you to manage the underlying virtual machines.

beginner

What is a key benefit of using Fargate for scaling containers?

Fargate automatically scales your containers based on demand without manual intervention on infrastructure.

What does AWS Fargate eliminate the need for?

A Managing servers or clusters

B Writing container code

C Using containers

D Creating task definitions

Fargate removes the need to manage servers or clusters by running containers serverlessly.

Which component describes your container configuration in Fargate?

A Cluster

B Task definition

C Load balancer

D Security group

The task definition specifies the container image, CPU, memory, and other settings.

How does Fargate handle scaling?

A It does not support scaling

B You manually add servers

C It automatically scales containers based on demand

D You must configure auto-scaling groups

Fargate automatically scales containers without manual server management.

Which launch type requires you to manage the underlying virtual machines?

A EC2 launch type

B Fargate

C Lambda

D S3

EC2 launch type requires managing the virtual machines that run containers.

What is a cluster in AWS Fargate?

A A group of servers you manage

B A database service

C A container image repository

D A logical grouping where Fargate runs your tasks

A cluster is a logical grouping of tasks and services where Fargate runs your containers.

Describe how AWS Fargate helps you run containers without managing servers.

Think about what you don't have to do when using Fargate.

Explain the difference between Fargate and EC2 launch types for running containers.

Compare who manages the servers in each case.

Practice

1. What is the main benefit of using AWS Fargate for running containers?

easy

A. You have to configure virtual machines yourself.

B. You must manually scale the containers.

C. You need to install and maintain the operating system.

D. You don't need to manage servers or clusters.

Solution

1. Step 1: Understand Fargate's serverless nature

   AWS Fargate runs containers without requiring you to manage the underlying servers or clusters.

2. Step 2: Compare options

   The other options describe manual management tasks that Fargate removes for you.

3. Final Answer:

   You don't need to manage servers or clusters. -> Option D

4. Quick Check:

   Serverless container management = A [OK]

Hint: Fargate means no server management needed [OK]

Common Mistakes:

• Thinking you must manage servers manually
• Confusing Fargate with EC2 instances
• Assuming you handle OS updates

2. Which of the following is the correct way to specify CPU and memory for a Fargate task definition?

easy

A. "cpu": 512, "memory": 1024

B. "cpu": "512", "memory": "1024"

C. "cpu": "0.5", "memory": "1GB"

D. "cpu": "512MB", "memory": "1GB"

Solution

1. Step 1: Check Fargate task definition format

   Fargate expects CPU and memory as strings representing CPU units and MiB memory, e.g., "512" and "1024".

2. Step 2: Evaluate options

   "cpu": "512", "memory": "1024" uses strings with numeric values, which is correct. Using numbers instead of strings is incorrect. Decimal values for CPU or units like GB/MB are invalid.

3. Final Answer:

   "cpu": "512", "memory": "1024" -> Option B

4. Quick Check:

   CPU and memory as strings = B [OK]

Hint: CPU and memory must be strings in task definition [OK]

Common Mistakes:

• Using numbers instead of strings
• Adding units like MB or GB
• Using decimal numbers for CPU

3. Given this Fargate task definition snippet:

{"cpu": "256", "memory": "512", "containerDefinitions": [{"name": "app", "image": "myapp:latest"}]}

What happens if you try to run this task with 1024 MiB memory requested in the service?

medium

A. The task runs with 512 MiB memory as defined in the task.

B. The task runs but may be terminated if it exceeds 512 MiB.

C. The task fails to start due to memory mismatch.

D. The service overrides the task memory to 1024 MiB automatically.

Solution

1. Step 1: Understand memory settings in Fargate

   Memory is defined in the task definition and must match the service configuration; mismatches cause failures.

2. Step 2: Analyze the mismatch

   The task requests 512 MiB, but the service requests 1024 MiB, causing a conflict and preventing the task from starting.

3. Final Answer:

   The task fails to start due to memory mismatch. -> Option C

4. Quick Check:

   Memory mismatch causes failure = D [OK]

Hint: Task and service memory must match exactly [OK]

Common Mistakes:

• Assuming service overrides task memory
• Thinking task runs with lower memory
• Ignoring mismatch errors

4. You created a Fargate service but the tasks keep failing with "RESOURCE:MEMORY" errors. What is the most likely cause?

medium

A. The task definition requests more memory than the Fargate platform allows.

B. The container image is missing from the registry.

C. The service is not attached to a load balancer.

D. The CPU units are set too high.

Solution

1. Step 1: Understand RESOURCE:MEMORY errors

   This error means the task requested more memory than available or allowed by Fargate limits.

2. Step 2: Evaluate other options

   Missing images cause different errors, load balancer issues don't cause memory errors, and CPU settings affect CPU, not memory.

3. Final Answer:

   The task definition requests more memory than the Fargate platform allows. -> Option A

4. Quick Check:

   Memory error means memory request too high = C [OK]

Hint: Memory errors usually mean request exceeds limits [OK]

Common Mistakes:

• Blaming missing container images
• Confusing CPU and memory errors
• Ignoring platform memory limits

5. You want to run a web app on Fargate that needs 2 containers: one for the app and one for logging. How should you configure the task definition to ensure both containers run together and share CPU and memory?

hard

A. Define both containers in the same task definition with combined CPU and memory settings.

B. Create two separate task definitions and run two Fargate services.

C. Run one container on Fargate and the other on EC2 instances.

D. Use one container and add logging as a sidecar process inside it.

Solution

1. Step 1: Understand multi-container tasks in Fargate

   Fargate supports multiple containers in one task definition sharing CPU and memory.

2. Step 2: Evaluate options for running two containers together

   Defining both containers in the same task definition with combined CPU and memory settings ensures they run together and share resources. Separating into different task definitions or services loses shared resource benefits and co-location. Adding logging as a sidecar process inside the app mixes concerns, which is not best practice.

3. Final Answer:

   Define both containers in the same task definition with combined CPU and memory settings. -> Option A

4. Quick Check:

   Multi-container task = single task definition with both containers [OK]

Hint: Use one task definition for multiple containers sharing resources [OK]

Common Mistakes:

• Splitting containers into separate tasks unnecessarily
• Mixing logging inside app container
• Running containers on different platforms