Case Study

Accelerating Feature Releases with CI/CD Using AWS CloudFormation to Achieve 99.9% Uptime for Abright Labs

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Software Development


AWS CloudFormation, Amazon S3, AWS IAM, AWS Lambda, Amazon CloudWatch, AWS CodePipeline, AWS CodeBuild, Amazon ECR, AWS AppSync


Enhanced monitoring and CI/CD with AWS, cut costs by 20%, speed updates, and ensure 99.9% uptime.

About the Client

Abright Lab is a software company specializing in multidisciplinary digital product expertise, focusing on user experience, design, and development. They collaborate with innovative companies, enhancing design and development capabilities to achieve measurable business objectives and establish robust development frameworks. 



Cost-saving monitoring and alerting solutions

1000 requests per second

Efficient service updates


Streamlined CI/CD pipeline

The Challenge

The client faces challenges with their expanding monolithic application, struggling with increased request volumes, testing needs, and deployment standards. Inadequate monitoring hampers performance optimization and operational efficiency. Moreover, infrastructure expansion is hindered by frequent update-related changes, exacerbated by a lack of suitable tools for monitoring and managing application logs.


  • Deploying applications across various environments, including development, staging, pre-production, and production. The coordination of these deployments is efficiently managed through AWS CloudFormation, which ensures consistent and rapid deployments for the infrastructure.  
  • Implemented CI/CD enhancement by deploying AWS CloudFormation templates for each microservice across distinct environments within AWS pipelines. 
  • Implemented AWS CloudFormation template to automate the deployment of OpenSearch, enabling seamless setup for real-time application monitoring, log analytics, and website search functionality. 
  • Implemented Amazon ECS Auto Scaling to enhance the availability of the application. During traffic spikes or sudden surges in demand, the service can quickly scale out by adding more tasks. This prevents application downtime. 
  • Routed all microservices endpoints to a single Application Load Balancer (ALB) using host-based routing, optimizing resource utilization without relying on the number of Amazon EC2 instances or AWS Fargate tasks. 
  • Implemented the setup of a REST API using AWS CloudFormation Template, with the automatic addition of resources as services are deployed. 
  • Implemented the Multi-AZ deployment of Amazon RDS service in the private subnet using AWS CloudFormation Template (CFT) to ensure enhanced security and network isolation. 
  • AWS Services used are Amazon ECS, Amazon ECR, Amazon CloudWatch, AWS Cognito, AWS IAM, Amazon OpenSearch, AWS Lambda, AWS CodePipeline, Amazon RDS, AWS Load Balancer, AWS Systems Manager, and  Amazon API Gateway.

The Results

Implemented enhanced monitoring, streamlined service updates, saving 30 minutes per update, and optimized CI/CD with AWS CloudFormation, resulting in faster feature releases and 99.9% uptime.

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