A Case Study on Infrastructure Transformation and DevOps

A Case Study on Infrastructure Transformation and DevOps Adoption for Improved Efficiency and Cost Optimization

Table of Contents

About Customer:

        Design Everest is a technology-enabled managed marketplace for the architecture, engineering and construction (AEC) industry. We connect owners with architects, engineers and contractors, while utilizing automation and project management to simplify the complex pre-construction process. Currently providing architecture and engineering services in California, Design Everest plans to expand its services offered to build the next generation AEC platform nationally soon. 

         At Design Everest, challenges galvanize us into finding solutions, and our success is driven by our software and business model innovations. Over the years, we’ve been reinventing the massive pre-construction process, with a TAM of $100 Billion+ in the US alone, and have reached a critical growth stage where our model is poised to disrupt the entire AEC marketplace. 

The Challenges Faced by Customer:​​

Design Everest identified scalability issues in the underlying application hosting platform. The infrastructure supporting the product needed refinement to support customer growth and remove single points of failure. 

Customer was burning more money on the GCP platform and wanted to switch to reliable, efficient and cost effective hyper scaler. The development team also had a desire to adopt a new methodology to foster good DevOps practices. 

The Solution Provided to Customer:

        CloudArmee team recommended to deploy their application and infra through CI/CD, Existing systems were refactored, re-platformed, and re-designed. 

  • Creating an IT systems roadmap 
  • Product strategy 
  • Practical transformation design 
  • Mapping out the user interface 
  • Seamless amalgamation of all products into one


The solution delivered a two-stage transformation design and defined the target state through an execution plan. Stage-I orchestrated the review current applications and architecture even as consolidating their functionalities into one platform. Stage II comprised understanding business imperatives, future trajectory of the transformation strategy, defining the target-state operating model based on potential efficiencies, and strategy implementation. 


  • Frame– Setting up program management, foundational technology components, tools & processes, and governance across architecture, data, integration, quality assurance, and change adoption. 
  • Design & Develop– Agile sprints that work on backlogs specific to each product stream. 
  • Implement – Consolidation, packaging, and release management of the output of sprints, aligning to the high-level plan, and ensuring seamless onboarding, transitioning, and adoption readiness. ​ 
  • Improve – Ensuring that the implemented product is supported, continuously optimized, and improved to achieve business outcomes effectively. ​ 


Benefits Achieved by the Customer:


  • Faster Time to Market: CI/CD enables rapid software development and deployment cycles. By automating the build, test, and deployment processes, developers can quickly iterate and release new features, reducing the time it takes to deliver software updates to end-users. 


  • Improved Software Quality: Continuous Integration ensures that code changes are integrated and tested frequently, catching bugs and issues early in the development process. Automated testing helps maintain a high level of software quality by running comprehensive tests on each code commit, reducing the risk of introducing bugs into the production environment. 


  • Enhanced Collaboration: CI/CD fosters collaboration among development teams by providing a standardized and automated workflow. It enables multiple developers to work on different features concurrently and integrates their changes seamlessly. This promotes teamwork, reduces conflicts, and enhances overall productivity. 


  • Increased Agility: With CI/CD, developers can quickly respond to market demands and customer feedback by delivering updates and bug fixes rapidly. The ability to iterate and release software more frequently allows businesses to stay competitive, adapt to changing requirements, and seize new opportunities. 


  • Infrastructure as Code (IaC): AWS CI/CD often incorporates Infrastructure as Code practices, enabling the automation of infrastructure provisioning and configuration. This ensures consistent and reproducible environments across different stages of the development lifecycle, reducing the risk of configuration drift and improving overall system stability. 


  • Cost Savings: CI/CD helps optimize resource usage by automating the provisioning and deprovisioning of resources as needed. This eliminates the need for manual intervention and reduces costs associated with idle or underutilized infrastructure. Additionally, early bug detection and quicker feedback cycles result in cost savings by reducing the time and effort spent on bug fixing and troubleshooting in production. 


  • Continuous Delivery: CI/CD pipelines facilitate continuous delivery, allowing businesses to release software updates to production environments reliably and with minimal downtime. By automating the deployment process, rollbacks and recovery from issues become faster and more straightforward, minimizing the impact on end-users. 


  • Scalability and Flexibility: AWS CI/CD leverages cloud infrastructure, providing the ability to scale resources up or down based on workload requirements. This scalability ensures that development and testing environments can match production environments, leading to more accurate testing and reducing the risk of performance-related issues in production. 


   Overall, AWS CI/CD offers customers a streamlined, efficient, and automated approach to software development, testing, and deployment. It helps teams deliver high-quality software faster, respond to market demands rapidly, and achieve greater agility in an increasingly competitive landscape. 

Tech Stack:

Amazon Beanstalk Amazon API Gateway Amazon Appflow 
Amazon S3 Amazon RDS Amazon DMS 
AWS Redshift AWS WAF Amazon CloudFormation 
Amazon SNS Amazon MQ Amazon Lambda