Observed Signal · Jun 27, 2026 · Technical Walkthrough · Source: DEV Community · Impact: 2/5 · Sentiment: Positive
Solo-built production GitOps platform on AWS EKS
An infrastructure engineer documented building a production-style GitOps platform on AWS EKS around the Spring PetClinic microservices (7 services). The platform is fully provisioned with Terraform (remote state on S3 + DynamoDB) and uses GitHub Actions with OIDC to build Docker images and push to Amazon ECR. CI bumps image tags in a Helm values-driven chart; Argo CD reconciles the cluster (git as source of truth). Autoscaling is implemented at two layers (HPA for pods and Karpenter for nodes). Observability is provided by Prometheus, Grafana and Zipkin. The project is reproducible via a Makefile (provision, up, down). The author describes several production issues and fixes (tracing misconfiguration, CI tag mismatches, Argo CD vs HPA replica conflict, Karpenter IAM policy size) and publishes the infrastructure and app repos and a live demo URL.
Practical, reproducible walkthrough of a production-style GitOps platform demonstrating patterns (OIDC-auth CI, GitOps with Argo CD, Helm single-chart, HPA + Karpenter autoscaling, observability) useful to platform and DevOps teams; valuable technical guidance but not industry-shifting.
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Key Takeaways & Evidence Grounding
- The platform runs the Spring PetClinic microservices (7 services) on an EKS cluster named petclinic-prod in eu-central-1 (Kubernetes 1.33).
- Infrastructure is defined and provisioned with Terraform, using a remote state backend (S3 bucket + DynamoDB lock table) and reusable modules.
- CI uses GitHub Actions with OIDC to build Docker images, push them to Amazon ECR, and commit an image-tag bump to the Helm chart; Argo CD then syncs changes (GitOps).
- Autoscaling is implemented with Horizontal Pod Autoscaler (HPA) for pods and Karpenter for node provisioning; Karpenter produced a t3a.medium node in ~90 seconds during testing.
- Observability stack includes Prometheus (metrics), Grafana (visualization), and Zipkin (distributed tracing); the author documented root causes and fixes for tracing and deployment issues.
Connected Companies & Entities
3 Entities mapped“At a high level: a push to `main` triggers a GitHub Actions pipeline that builds and pushes Docker images to ECR, then commits a tag bump to...”
“All 7 services are built as Docker images and pushed to ECR, tagged with the git SHA....”
“Cloud | AWS (EKS, ECR, VPC, IAM, ALB, ACM, SQS)...”
Ontology Mapping & Concepts
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