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Shapematrix Devops On AWS


Building DevOps on AWS

jbthechamp | September 9, 2020


Company Name
Case Study Title
Building DevOps on AWS

Company Info

Building DevOps on AWS

The Shape Matrix system uses geometric shapes to generate an infinite number of visually appealing 2D and 3D marks – Shapetags – that serve as secure, serialized, hard-to-clone identifiers for physical and digital objects. Shapetags are quickly authenticated with off-the-shelf mobile devices, impossible to decode without authorized access, yet easily recognizable by humans.

Development Environments

As Shapematrix realized improvements in implementation productivity and quality of the development process, the amount of time required to manually configure its environment was burdensome. Triumph Tech recognized Shapematrix needed a more robust automated solution with AI to restore valuable productivity and hasten the time to market.

The below diagram illustrates the end result of this endeavor:

As a smaller startup business with a team of two developers, Shapematrix didn’t have IT staff nor budget to support a large software deployment effort. Triumph Tech determined that an automated cloud deployment solution using CloudFormation and Terraform would clear a significant amount of time when deploying the core components.

Triumph Tech chose AWS to provide infrastructure as code (IaC) using CloudFormation in combination with Terraform. Triumph Tech implemented CloudFormation to deploy a virtual private cloud (VPC) with two private and two public subnets along with two network address translation (NAT) gateways for high availability.

Additionally, CloudFormation was used to deploy RDS Postegres, an ECS cluster, 2 task definitions, 2 Fargate services, and an RDS Postegres jump box.

Lastly, the integration of Codepipeline and AWS Fargate accelerated the deployment process and eliminated the need for manual configuration.

Why Amazon Web Services

Shapematrix contended with the amount of staffing resource time needed to deploy a new environment. We chose Amazon Web Services because it is the most customizable cloud in the world and the DevOps options are unparalleled. DevOps on AWS provides all the tools for a complete DevOps Solution in one place. AWS reduced the deployment time for a new environment, so developers can work on their products.

Outcomes of Project & Success Metrics

When we started the project, we calculated the time it would take to manually deploy required components using the AWS Console plus the time needed to build, compile, and deploy two Fargate services. Total time: 12 Hours.

Then we calculated the time to deploy core components via CloudFormation with Terraform. The total time: 30 minutes.

Lastly, building and deploying the Fargate services took 10 minutes while integrated with Codepipeline, instead of over 1.5 hours manually.

Lessons Learned

Automated solutions are the optimal way to deploy core cloud components. They not only save valuable time, but also save significant amounts of money.

AWS Thinkbox Deadline Summary

Rendering on-premise versus cloud

Automated solutions are the optimal way to deploy core cloud components. They not only save valuable time, but also save significant amounts of money.