Serverless Architecture with AWS Fargate

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Serverless Computing Architecture with AWS Fargate

Applications that run with microservice architecture are becoming more popular, efficient, and innovative - serverless computing architecture takes this a step further by taking care of the need to provision, scale, and maintain servers in order to run your applications. With AWS Fargate, organizations can take advantage of the serverless computing architecture to implement applications with convenience, leaving behind the need to manage clusters and enabling seamless scaling of the applications. 

Learn more about how to set up a microservice architecture to implement serverless computing, and read an interesting use case with AWS Fargate below.

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Migrating Applications from Monolithic to Microservice on AWS

Microservices allow for flexibility and scalability, and the transition from monolithic applications to microservices in the cloud is becoming a forward-thinking strategy for many companies. There are a few elements to the migration including security and compliance, the actual application containerization, database migration, and setting up a CI/CD Pipeline.

A simple example of this migration is from Telia, a Europe-based telecom provider with customers all across the globe. They used AWS Fargate for deployment, which removed the need for their developers to manage the infrastructure and allowed them to focus on the business logic instead. The architecture of their migration is shown below, and more details of how this migration was executed can be found here

Making an Impact with Serverless Compute Architecture

Serverless Compute Architecture allows for a number of different use cases depending on the needs of the organization. It can be used for machine learning, like using AWS Fargate to build a serverless Twitter reader, or for creating an entirely new platform, as END did in order to become more efficient. 

END.'s New Platform Runs on AWS Fargate at its Core

For the men's clothing brand, END., deployments were one of the biggest pain points that engineers had - their two-person DevOps team existed as a bottleneck when it came to go-live. A more efficient process was necessary to remedy the bottleneck, which was done through a Continuous Integration, Continuous Deployment (CI/CD) Pipeline, and by deploying the application on AWS Fargate. The automation through the CI/CD Pipeline in combination with AWS Fargate removing the need to manage the infrastructure enabled END.'s DevOps team to focus on building the applications to meet their customers' needs quickly and efficiently.

Their process can be found in the diagram below, and details about END.'s execution can be found here.

Building a Serverless Twitter Reader with AWS Fargate

Once the migration to microservices is complete, and the new serverless architecture is set up with AWS Fargate, the process of building and deploying applications becomes more efficient. In this post on the AWS Blog, the steps are laid out to learn how to build a serverless Twitter reader with the architecture shown below.

Learn more about AWS Fargate, Amazon ECS, and Containers on AWS!

Security on AWS Fargate

Observability on AWS Fargate

Machine Learning with AWS Fargate

CI/CD with AWS Fargate