Elektrigo: Streamlining AWS DevOps and CloudFormation Success
Elektrigo's engineering team was spending significant time on manual infrastructure management and deployment coordination. A DevOps transformation delivered automated CI/CD, IaC standardization, and operational observability in 90 days.
The Challenge
“Elektrigo's product engineering team was managing AWS infrastructure through a combination of console-based manual changes, shell scripts, and partially complete CloudFormation templates. Deployments required coordinated manual steps across multiple engineers, took 4-6 hours, and frequently failed due to undocumented dependencies and configuration drift between environments. The team had no automated testing of infrastructure changes and limited observability into production system health. Release frequency was constrained to bi-weekly by deployment complexity.”
The Solution
Eficens delivered a DevOps transformation through three workstreams: IaC standardization (converting all infrastructure to complete, parameterized CloudFormation templates with environment-specific parameter files), CI/CD pipeline implementation (AWS CodePipeline with CodeBuild, automated testing, staged deployments with automated rollback), and observability buildout (CloudWatch dashboards, structured logging, distributed tracing with X-Ray, automated alerting for production health indicators).
Implementation
Infrastructure as Code Standardization
The IaC standardization workstream began with a complete infrastructure discovery: mapping every AWS resource in the production environment, documenting configuration, and identifying resources not reflected in existing CloudFormation templates. The discovery revealed significant configuration drift—over 40 production resources had been modified through the console without corresponding template updates. Eficens reconstructed accurate CloudFormation templates from the existing production configuration using CloudFormation Designer and manual verification, then implemented a drift detection workflow to prevent future drift.
CI/CD Pipeline Implementation
The CI/CD pipeline implemented a three-stage deployment model: Development (automated deployment on every push to a feature branch), Staging (automated deployment on merge to main, with automated integration tests), and Production (manual approval gate with automated deployment on approval). Each deployment stage ran CloudFormation change sets with automated review—flagging destructive changes for human review—before executing the deployment. Rollback procedures were automated: if a deployment failed health checks within 15 minutes, the pipeline automatically initiated rollback to the previous stable deployment. This automation eliminated the previous coordination overhead and reduced deployment time from 4-6 hours to 20-30 minutes.
Observability and Operational Readiness
The observability buildout standardized structured JSON logging across all application services, implemented distributed tracing with X-Ray for request flows across microservices, and created CloudWatch dashboards covering the key operational health indicators for each service. Automated alerts were configured for error rate, latency, and resource utilization thresholds, with integration to PagerDuty for on-call routing. The combination of structured logs, traces, and metrics reduced mean time to diagnosis for production incidents from hours (when engineers had to search through unstructured logs manually) to minutes (when structured queries and distributed traces immediately pointed to the failing component).
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