Fargate serverless containers in AWS - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ service_behavior

intermediate

Fargate Task Networking Mode

Which networking mode does AWS Fargate use to run containers securely and isolate them from other tasks?

A AWSVPC mode, assigning each task its own elastic network interface

B Bridge mode, sharing the host's network stack

C None, Fargate tasks do not use networking

D Host mode, directly using the host's network interface

💡 Hint

Think about how Fargate isolates tasks for security and networking.

AWS Fargate uses AWSVPC mode which assigns each task its own elastic network interface (ENI). This provides task-level isolation and allows tasks to have their own IP addresses.

❓ Architecture

intermediate

Scaling Fargate Tasks Automatically

You want your Fargate service to automatically add more tasks when CPU usage is high and reduce tasks when CPU usage is low. Which AWS service should you configure to achieve this?

A AWS CloudFormation stack updates

B AWS Lambda functions triggered by CloudWatch alarms

C AWS Auto Scaling with ECS Service Auto Scaling policies

D AWS Elastic Load Balancer health checks

💡 Hint

Consider the service that manages container scaling based on metrics.

To scale Fargate tasks automatically, you configure AWS Auto Scaling with ECS Service Auto Scaling policies that respond to CloudWatch metrics like CPU usage.

❓ security

advanced

IAM Role for Fargate Task Execution

Which IAM role is required for a Fargate task to pull container images from Amazon ECR and send logs to CloudWatch Logs?

A Administrator Access role assigned to the user

B Task Role attached to the ECS service

C Instance Profile role attached to the EC2 instance

D Execution Role specified in the task definition

💡 Hint

This role allows the task to perform actions needed to start and monitor containers.

The Execution Role is specified in the task definition and grants permissions to pull images from ECR and send logs to CloudWatch Logs.

❓ Configuration

advanced

Fargate Task CPU and Memory Configuration

You want to run a Fargate task with 2 vCPU and 4 GB memory. Which of the following CPU and memory combinations is valid for Fargate?

A CPU: 1024, Memory: 2048

B CPU: 2048, Memory: 4096

C CPU: 4096, Memory: 2048

D CPU: 512, Memory: 8192

💡 Hint

Check AWS Fargate allowed CPU and memory combinations.

Fargate requires specific CPU and memory combinations. For 2 vCPU, valid memory values include 4 GB (4096 MB). Option B matches this.

✅ Best Practice

expert

Securing Sensitive Data in Fargate Tasks

What is the best practice to provide sensitive information like database passwords to a Fargate task securely?

A Store the password in AWS Secrets Manager and reference it in the task definition

B Pass the password as plain text in the ECS RunTask API call

C Write the password to a file inside the container at runtime

D Hardcode the password in the container image environment variables

💡 Hint

Think about AWS services designed for managing secrets securely.

Using AWS Secrets Manager to store and reference sensitive data in the task definition is the best practice. It avoids hardcoding and keeps secrets encrypted and managed.

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