Background

Blackbird needed a cost-effective, highly available, and scalable solution to host their client’s website and CMS. One of their main requirements was the ability to deploy this solution for multiple clients with minimal changes.

Proposed Solution

We created a standardized modular terraform code in order to deploy blackbirds’s solution. The terraform code can be reused to deploy the solution whenever needed.

We used AWS ECS clusters in order to host the application’s various components, each cluster is configured with auto-scaling based on the Amazon CloudWatch CPUUtilization metric.

We configured AWS CodePipeline for each cluster in order to deploy changes to the application, by creating a new image on AWS ECR and utilizing the updated image to launch our new application version.

In order to host our data, we opted for the use of AWS RDS, which provided us with a highly available managed database solution.

Metrics for Success

Our design provided Blackbird with a solution that matched all their requirements. The modularity of the Terraform code simplified the need for repetitive deployments of the solution.

Using various AWS services provided us with a highly available and scalable solution, by configuring the auto-scaling policy to add capacity whenever the CPUUtilization metric is exceeded we ensure that the application is resilient and able to serve any amount of traffic it gets.

Streamlining the application’s deployment with AWS CodePipeline, allowed the development team to deploy and test changes faster, while ensuring no interruption in the application while deploying. 

Conclusion

Our solution provided Blackbird with a robust, scalable, and cost-effective system that meets all their key requirements. By leveraging modular Terraform code and AWS services such as ECS, RDS, and CodePipeline, we streamlined the deployment process for multiple clients, ensuring high availability and the ability to scale automatically with traffic demands. This architecture allowed for faster deployments, minimized downtime, and improved overall operational efficiency.