Fullstack Python: Containerizing Flask Apps and Deploying on AWS ECS

In modern software development, containerization is revolutionizing how we build, ship, and deploy applications. For fullstack Python developers, using Docker to containerize a Flask app and deploying it via Amazon ECS (Elastic Container Service) unlocks a powerful, scalable, and production-ready workflow. This blog will guide you through containerizing your Flask app and deploying it to AWS ECS with simplicity and clarity.


Why Containerize Your Flask App?

A container is a lightweight, standalone executable that includes everything needed to run your application—code, runtime, libraries, and environment variables. Here’s why containers are ideal for deployment:

Consistency: Run your app the same way in development, testing, and production.

Portability: Containers can run on any system that supports Docker.

Scalability: Easily scale your app with container orchestration services like ECS or Kubernetes.

Isolation: Each container runs in its own isolated environment.


Step 1: Containerize Your Flask App with Docker

Let’s assume your Flask app has a basic structure:


bash


/flask-app

│

├── app.py

├── requirements.txt

└── Dockerfile

Create requirements.txt

bash

Copy

Edit

flask

gunicorn

Create a Dockerfile

Dockerfile

Copy

Edit

# Use Python base image

FROM python:3.10-slim


# Set working directory

WORKDIR /app


# Copy files

COPY . /app


# Install dependencies

RUN pip install -r requirements.txt


# Expose port

EXPOSE 5000


# Run the app with Gunicorn

CMD ["gunicorn", "-b", "0.0.0.0:5000", "app:app"]

Build and Test Locally

bash

Copy

Edit

docker build -t flask-app .

docker run -p 5000:5000 flask-app


Step 2: Push Docker Image to Amazon ECR (Elastic Container Registry)

Create a Repository

Go to AWS ECR.


Create a private repository named flask-app.


Authenticate Docker to ECR

bash

Copy

Edit

aws ecr get-login-password --region <your-region> | \

docker login --username AWS --password-stdin <your-account-id>.dkr.ecr.<your-region>.amazonaws.com

Tag and Push Image

bash

Copy

Edit

docker tag flask-app:latest <your-ecr-repo-uri>:latest

docker push <your-ecr-repo-uri>:latest


Step 3: Deploy on AWS ECS (Fargate)

Create a Cluster

Go to ECS > Clusters.

Choose “Networking only” for Fargate.

Name your cluster and create.

Create a Task Definition

Launch type: Fargate

Container name: flask-app

Image URI: Use the ECR image you pushed

Port mapping: 5000 (container) → 80 (load balancer)


Create a Service

Choose your task definition

Select number of tasks (e.g., 1)

Attach a load balancer (optional but recommended)

Define security groups and networking


Step 4: Access Your App

Once the ECS service is running, the load balancer (or public IP of the task) will provide access to your Flask app. Visit the URL in your browser and you’ll see your app live!


Final Thoughts

Deploying Flask applications on AWS ECS with Docker may seem intimidating at first, but it's one of the most powerful and scalable solutions for cloud-native applications. It allows you to manage infrastructure efficiently, roll out updates seamlessly, and handle scaling automatically.

With this containerized workflow, your Flask app becomes cloud-ready, resilient, and production-grade—ideal for fullstack developers aiming to build and deploy applications the modern way.


Learn FullStack Python Training

Read More : Fullstack Flask: Deploying Flask Apps on AWS EC2

Read More : Fullstack Python: Using Prometheus and Grafana for Microservices Monitoring

Read More : Fullstack Flask: Scaling Microservices with Kubernetes Horizontal Pod Autoscaling


Visit Our IHUB Talent Training Institute in Hyderabad

Comments

Post a Comment

Popular posts from this blog

How to Use Tosca's Test Configuration Parameters

Tosca by Tricentis is a powerful model-based test automation tool widely used in enterprise environments for end-to-end testing. One of its most useful features is Test Configuration Parameters (TCPs), which provide flexibility and control in managing test execution. TCPs enable testers to create reusable test cases by passing dynamic values without hardcoding them. This significantly enhances test maintenance, scalability, and efficiency. In this blog, we’ll explore what Test Configuration Parameters are, how to create and use them, and the best practices to follow when working with TCPs in Tosca. What Are Test Configuration Parameters? Test Configuration Parameters are custom-defined key-value pairs that can be associated with test cases, test case folders, or execution lists in Tosca. They help manage configuration data such as environment URLs, browser types, credentials, or any other variable data that may differ across test runs. By using TCPs, you can avoid duplicating test case...
Read more

Using Hibernate ORM for Fullstack Java Data Management

In the world of fullstack Java development, managing data efficiently and seamlessly across the application is critical. One of the most powerful tools in the Java ecosystem for handling database operations is Hibernate ORM (Object-Relational Mapping). Hibernate simplifies the interaction between Java applications and relational databases, reducing boilerplate code and improving maintainability. This blog explores how Hibernate ORM works, why it’s widely used, and how it fits into the data management strategy of a fullstack Java application. What is Hibernate ORM? Hibernate ORM is an open-source Java framework that provides a powerful and flexible mechanism for mapping Java objects to database tables. It abstracts the low-level JDBC code, allowing developers to work with high-level object-oriented concepts. Instead of writing raw SQL queries, Hibernate allows developers to define database interactions using simple Java classes (also known as POJOs) and annotations or XML configurations...
Read more

Creating a Test Execution Report with Charts in Playwright

Modern test automation isn't just about running tests—it's also about presenting clear, visual feedback on test results. When working with Playwright, one of the most powerful end-to-end testing tools for modern web apps, generating detailed execution reports can help your team track progress, identify issues quickly, and make data-driven decisions. A visual report with charts brings your testing efforts to life. In this blog, we’ll walk through how to create a test execution report with charts using Playwright’s built-in capabilities along with third-party tools for enhanced visualization. Why Visual Reports Matter Plain text logs and console outputs are hard to parse at scale. A good report should answer questions like: How many tests passed or failed? What’s the overall success rate? Which tests are flaky or slow? How have test results changed over time? Visualizing this data with charts—like pie charts, bar graphs, or timelines—helps QA teams and stakeholders better underst...
Read more