Fullstack Flask: Deploying Microservices on AWS ECS

As modern applications scale, microservices have become the go-to architectural style for building and deploying scalable, maintainable, and flexible systems. For Python developers, Flask is a lightweight framework perfect for microservices. Pair that with AWS ECS (Elastic Container Service), and you’ve got a powerful infrastructure to deploy and manage your services. In this blog, we’ll explore how to take a fullstack Flask microservice from local development to live deployment on AWS ECS.


Why Flask for Microservices?

Flask’s minimalism and extensibility make it ideal for microservices. Each service can run independently, handle specific tasks (e.g., user authentication, order processing, payments), and communicate via APIs. Flask lets you quickly build RESTful APIs with less overhead.

Combine it with a frontend (like React or Vue), and you have a complete fullstack microservice structure.


Containerizing Flask with Docker

Before deploying to AWS ECS, you need to containerize your Flask application.


Create a Dockerfile:


dockerfile


FROM python:3.9

WORKDIR /app

COPY requirements.txt .

RUN pip install -r requirements.txt

COPY . .

CMD ["python", "app.py"]

Build and Tag the Docker Image:


bash


docker build -t flask-microservice .

Test Locally:


bash


docker run -p 5000:5000 flask-microservice

If it works locally, you’re ready to deploy it to AWS.


Deploying on AWS ECS

AWS ECS (Elastic Container Service) lets you run Docker containers in a managed cluster. You can choose between Fargate (serverless) or EC2 (virtual machine-based) launch types. We’ll focus on Fargate for its simplicity.


Step 1: Push Image to ECR (Elastic Container Registry)

Create a repository in ECR.

Authenticate Docker to AWS:


bash

aws ecr get-login-password | docker login --username AWS --password-stdin <aws_account_id>.dkr.ecr.region.amazonaws.com

Tag and Push the Image:


bash


docker tag flask-microservice <your_ecr_repo_uri>

docker push <your_ecr_repo_uri>

Step 2: Configure ECS

Create a Cluster using AWS ECS Console.

Define a Task Definition:

Set memory, CPU, and container settings.

Use the image URI from ECR.

Configure port mappings (e.g., 5000:5000).

Create a Service:

Choose Fargate.

Attach a Load Balancer for public access (optional but recommended).

Auto-scale based on demand.

Frontend Integration

For a fullstack setup:


Host the frontend (e.g., React) on S3 + CloudFront or Amplify.


Use API Gateway or directly connect the frontend to your Flask microservices through the ECS Load Balancer URL.


Monitoring and Logging

Enable CloudWatch Logs to capture application logs and set up alarms for high CPU/memory usage. This ensures observability across your microservices.


Conclusion

Deploying fullstack Flask microservices on AWS ECS offers a robust, scalable foundation for modern applications. With Docker, ECS Fargate, and ECR, you can manage containerized services with ease, ensuring each part of your application can scale independently.

Whether you're building a SaaS platform, an e-commerce app, or an internal tool, this deployment model sets you up for long-term success.



Learn FullStack Python Training

Read More : Fullstack Python Microservices: Using Kafka for Event-Driven Architecture
Read More : Fullstack Flask and React: Communication Between Microservices via APIs

Read More : Flask and RabbitMQ: Building Message Queue-Based Microservices

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