Fargate serverless containers in AWS - Step-by-Step Execution

Process Flow - Fargate serverless containers

Define Container Image

↓

Create Task Definition

↓

Configure Fargate Service

↓

Launch Containers on Fargate

↓

AWS Manages Infrastructure

↓

Containers Run Serverless

↓

Scale Automatically Based on Load

This flow shows how you define a container, create a task, configure a Fargate service, and AWS runs your containers serverless, managing infrastructure and scaling automatically.

Execution Sample

AWS

1. Define container image
2. Create ECS task definition with Fargate launch type
3. Create ECS service using Fargate
4. AWS launches containers serverless
5. Containers run without managing servers

This sequence shows the steps to deploy containers on AWS Fargate, which runs them without you managing servers.

Process Table

Step	Action	Input/Config	AWS Response	Result
1	Define container image	Docker image URL	Image stored in registry	Ready to use image
2	Create task definition	Task JSON with container and Fargate launch type	Task definition registered	Task ready for launch
3	Create ECS service	Service config with desired count	Service created	Service ready to run tasks
4	Launch containers	Service starts tasks	Fargate provisions compute	Containers running serverless
5	Run containers	Containers start	AWS manages servers	Containers serve requests
6	Scale containers	Load increases	Fargate adds tasks	More containers running
7	Scale down	Load decreases	Fargate removes tasks	Fewer containers running
8	Stop service	User stops service	Tasks stopped	No containers running

💡 Service stopped or scaled to zero, no containers running

Status Tracker

Variable	Start	After Step 2	After Step 4	After Step 6	Final
Container Image	undefined	defined	used	used	used
Task Definition	undefined	registered	active	active	active
Service Desired Count	0	0	1	3	0
Running Containers	0	0	1	3	0

Key Moments - 3 Insights

Why don't I need to manage servers when using Fargate?

Because AWS Fargate provisions and manages the compute resources automatically as shown in steps 4 and 5 of the execution_table.

How does scaling happen automatically?

When load increases, Fargate adds more containers (step 6), and when load decreases, it removes containers (step 7), all managed by AWS.

What is the role of the task definition?

The task definition (step 2) tells AWS what container image to run and how, acting like a recipe for launching containers.

Visual Quiz - 3 Questions

Look at the execution_table, at which step does AWS start running containers serverless?

A Step 2

B Step 6

C Step 4

D Step 8

💡 Hint

Check the 'AWS Response' and 'Result' columns at step 4 in the execution_table.

According to variable_tracker, what is the desired count of containers after step 6?

A 3

B 1

C 0

D Undefined

💡 Hint

Look at the 'Service Desired Count' row under 'After Step 6' in variable_tracker.

If you stop the service, what happens to running containers according to the execution_table?

A They keep running

B They stop

C They scale up

D They restart automatically

💡 Hint

See step 8 in the execution_table under 'Result'.

Concept Snapshot

AWS Fargate runs containers serverless.
You define a container image and task definition.
Create a service with desired count.
AWS manages servers and scales automatically.
No need to manage EC2 instances.
Containers run and scale based on load.

Full Transcript

AWS Fargate lets you run containers without managing servers. First, you define your container image. Then, you create a task definition specifying the container and Fargate launch type. Next, you create an ECS service with a desired number of containers. AWS Fargate launches and runs your containers serverless, managing the underlying infrastructure. It automatically scales the number of containers based on load. When you stop the service, containers stop running. This process simplifies container deployment by removing server management.

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