Dockerizing Front-End Apps for AWS Lambda Hosting

Introduction

In the rapidly evolving landscape of software development, serverless architecture has emerged as a game-changer, offering unparalleled scalability, reduced operational overhead, and increased developer productivity. Among the myriad of serverless platforms, AWS Lambda stands out as a leading choice for deploying applications without the need to provision or manage servers.

One common scenario in modern web development is the need to host front-end applications in a serverless environment. Traditionally, front-end applications are served from web servers or content delivery networks (CDNs). However, with the advent of serverless technologies like AWS Lambda, developers have the opportunity to containerize their front-end applications using Docker and deploy them as serverless functions.

Advantages of Dockerizing Front-End Apps

1. Consistency Across Environments:

Docker containers encapsulate all dependencies, libraries, and runtime environments required for the front-end application. This ensures consistent behavior across different development, testing, and production environments, reducing the risk of “it works on my machine” issues.

2. Isolation and Dependency Management:

Docker containers provide isolation from the underlying host system, allowing front-end applications to run in a controlled environment without impacting other applications or services. Dependency management becomes more straightforward as dependencies are packaged within the container.

3. Portability:

Docker containers are lightweight and portable, making it easy to package and deploy front-end applications across different infrastructure environments, including local development machines, on-premises servers, and cloud platforms like AWS, Azure, or Google Cloud Platform.

4. Scalability:

Dockerized front-end applications can be scaled horizontally by deploying multiple containers across a cluster of hosts. Container orchestration platforms like Kubernetes or Docker Swarm simplify the management of containerized applications, enabling auto-scaling based on demand.

5. Efficient Resource Utilization:

Docker containers consume fewer resources compared to traditional virtual machines, leading to improved resource utilization and cost savings. Containers share the host system’s kernel, reducing overhead and allowing for higher container density on the same hardware.

6. Simplified Deployment and Rollback:

Docker containers provide a consistent deployment mechanism, allowing front-end applications to be packaged once and deployed anywhere with minimal configuration. Rollback to previous versions becomes easier as Docker images are versioned and can be tagged accordingly.

7. Faster Development Workflow:

Docker enables developers to create lightweight, reproducible development environments using Docker Compose or Dockerfile. This accelerates the development process by reducing setup time and ensuring that all team members work in identical environments.

8. Improved Collaboration:

Docker images serve as a standardized unit of software delivery, enabling seamless collaboration between development, operations, and QA teams. Developers can share Docker images via registries like Docker Hub or private repositories, ensuring consistent deployment across the entire software development lifecycle.

9. Microservices Architecture Enablement:

Docker containers facilitate the adoption of microservices architecture by encapsulating individual components of front-end applications into separate containers. This promotes modularity, scalability, and fault isolation, allowing for more flexible and resilient systems.

Step-by-Step Guide

Step 1: Install an Amazon EC2 instance and follow these steps

• AWS Configuration: Configure Amazon CLI with your access key and secret key.
• Install AWS CLI and Docker on the Amazon EC2 instance.
• Clone Code Repository: Use the following command to clone the code repository:
• Clone the repository using the HTTPS clone command provided for your repository.
• Navigate to Code Folder: Change the directory to the cloned code folder.
• Navigate to Events Folder: Inside the code folder, navigate to the events folder.

Step 2: Write a Docker file

• Create a Docker file in the root directory of your front-end application.
• Define a base image suitable for running Python applications.
• Copy your application files into the Docker image.
• Install any dependencies using Pip3/pip for python.
• Optionally, specify a command to run your application when the container starts (e.g., CMD [“lambda_function”, “lambda_handler”]).

Here is the example Docker file:

Step 3: Create a requirements.txt file listing the dependencies required to run the Python functions

Step 4: Edit the dbConnection.py file with the correct DB credentials

Replace the USER, PASSWORD, ENDPOINT, DATABASE with the correct credentials.

Step 5: Build the Docker Image

• Open a terminal or command prompt and navigate to the directory containing your Dockerfile.
• Run the command docker build -t <image-name> . to build the Docker image.

Replace <image-name> with a suitable name for your image.

Build the Docker Image with the following Command:

Step 6: Test the Docker Image Locally

• Once the image is built, run it locally using the command Docker run -itd img-id /bin/bash

Step 7: Create the Amazon ECR Repo

• aws ecr get-login-password –region ap-south-1 | docker login –username AWS –password-stdin 555792844483.dkr.ecr.ap-south-1.amazonaws.com
• docker build -t events-repo .
• docker tag img-id 555792844483.dkr.ecr.ap-south-1.amazonaws.com/events-repo:latest
• docker push 555792844483.dkr.ecr.ap-south-1.amazonaws.com/events-repo:latest

Once it is pushed, we can see the image in the Amazon ECR Repo

Step 8: We have to host it in AWS Lambda Function

Steps for hosting it in an AWS Lambda function:

1. Navigate to the AWS Lambda console and opt to create a function.
2. Select the container image option.
3. Assign the desired function name.
4. Choose the container image URI from the list of repositories.
5. Opt for the latest image available in the repository.
6. Modify the execution role as needed.
7. Create the function.
8. Verify the function’s output through testing.

Conclusion

By embracing Docker and AWS Lambda, developers can create consistent, portable, and scalable environments for deploying front-end applications. This enables faster development cycles, improved collaboration, and reduced operational overhead, ultimately leading to more efficient and resilient web applications.

As organizations continue to embrace cloud-native technologies and DevOps practices, Dockerizing front-end applications for AWS Lambda hosting emerges as a powerful strategy for building modern, cloud-native applications. Whether you’re developing single-page applications, progressive web apps, or static websites, the combination of Docker and AWS Lambda offers unparalleled flexibility, scalability, and cost-effectiveness.

Drop a query if you have any questions regarding Dockerizing front-end applications and we will get back to you quickly.

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