Table of Contents

Deploying a Microservices App on AWS ECS Fargate

Meta Description

Learn how to deploy a microservices-based application on AWS ECS Fargate using Docker, Application Load Balancer, and Amazon VPC. This guide walks you through the process of containerizing services, setting up ECS tasks, and enabling seamless scaling.

Introduction

Microservices architecture promotes building applications as a collection of loosely coupled services. AWS ECS Fargate makes deploying and managing containerized microservices easier by eliminating the need to manage servers. This post provides a step-by-step guide to deploying a microservices app on ECS Fargate.

Architecture Overview

[ Client ]
   |
[ Application Load Balancer ]
   |
[ ECS Fargate Services (Service A, Service B, etc.) ]
   |
[ RDS / DynamoDB / S3 / Other AWS Services ]

Each microservice runs as a separate ECS service using its task definition. Services can communicate internally via VPC networking.

Prerequisites

AWS account with admin-level access
Docker installed locally
Familiarity with ECS, IAM, and networking concepts
Microservices app ready (Node.js, Python, Go, etc.)

Step 1: Containerize Your Microservices

Ensure each service has a Dockerfile. Example for a Node.js service:

# Dockerfile
FROM node:20-alpine
WORKDIR /app
COPY . .
RUN npm install --production
CMD ["node", "server.js"]

Then build and push to Amazon ECR:

aws ecr create-repository --repository-name service-a
$(aws ecr get-login-password --region your-region | docker login --username AWS --password-stdin <account>.dkr.ecr.your-region.amazonaws.com)
docker build -t service-a .
docker tag service-a:latest <account>.dkr.ecr.your-region.amazonaws.com/service-a:latest
docker push <account>.dkr.ecr.your-region.amazonaws.com/service-a:latest

Repeat for each microservice.

Step 2: Create a VPC and Subnets

You can use the default VPC or create a new one with public and private subnets for better isolation.

Ensure subnets span multiple AZs
Create security groups for ALB and ECS services

Step 3: Create ECS Cluster

Go to the ECS console:

Choose “Fargate” launch type
Create a new cluster (e.g., microservices-cluster)

Step 4: Define Task Definitions

For each service, define:

Docker image URL (from ECR)
Port mappings
CPU & memory
Environment variables (DB_URL, API_KEY, etc.)
Logging configuration (CloudWatch Logs)

Example snippet:

"containerDefinitions": [
  {
    "name": "service-a",
    "image": "<your-ecr-url>",
    "portMappings": [{"containerPort": 3000}],
    "environment": [{"name": "NODE_ENV", "value": "production"}]
  }
]

Step 5: Create ECS Services for Each Microservice

Navigate to your ECS Cluster
Create a new Fargate Service for each task definition
Enable Auto Scaling if needed
Select the appropriate subnet and security group

Step 6: Set Up an Application Load Balancer (ALB)

Create an ALB with at least 2 subnets in different AZs
Create target groups for each microservice
Configure listener rules (e.g., /api/users → service A, /api/orders → service B)
Register ECS services for the appropriate target groups

Step 7: Internal Service-to-Service Communication

If services need to talk to each other:

Ensure they’re in the same VPC
Use service discovery (Cloud Map) or internal ALB DNS names
Configure security groups to allow traffic between services

Step 8: Logging and Monitoring

Enable CloudWatch Logs in task definitions
Use CloudWatch Metrics for ECS services
Set up alarms for CPU/memory thresholds

Step 9: CI/CD Pipeline (Optional but Recommended)

Use GitHub Actions, AWS CodePipeline, or GitLab CI
Automate Docker builds, ECR pushes, and ECS service updates
Use aws ecs update-service --force-new-deployment to trigger redeploys

Final Thoughts & Best Practices

Use separate task definitions per service
Store secrets in AWS Secrets Manager or Parameter Store
Use ECS Service Auto Scaling for high-traffic services
Keep container images lean and secure
Regularly rotate IAM credentials and secrets

Useful Resources

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