Observed Signal · Jun 17, 2026 · Case Study · Source: DEV Community · Impact: 1/5 · Sentiment: Positive
Case Study: Deploying Spring Petclinic Microservices on AWS
A DevOps case study by Ebelechukwu Lucy Okafor describing the deployment of the Spring Petclinic microservices application to AWS as part of DMI (DevOps Micro Internship) Cohort 2. The author served as Co-Project Lead and App & Docker Lead, validating a Docker Compose stack locally, building linux/amd64 Docker images, tagging images with Git commit SHAs, authenticating and pushing images to Amazon ECR, and deploying services on AWS. The architecture included Config Server, Eureka discovery, an API gateway, multiple domain services and a GenAI service, and incorporated observability with Prometheus, Grafana and Zipkin. The post highlights technical challenges around multi-service containerization, lessons learned in automation and IaC, and recommended improvements such as stronger CI/CD and enhanced monitoring.
Technical case study describing a hands-on DevOps deployment and observability setup on AWS; useful as practical guidance but has limited, narrow industry impact for AdTech/MarTech.
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Key Takeaways & Evidence Grounding
- Author participated in DMI (DevOps Micro Internship) Cohort 2 and the team deployed the Spring Petclinic Microservices application on AWS.
- Author role: Co-Project Lead and App & Docker Lead, responsible for coordinating deployment and containerization tasks.
- Application architecture included: Config Server, Discovery Server (Eureka), API Gateway, Customers Service, Visits Service, Vets Service, GenAI Service, and Admin Server.
- Observability stack integrated: Prometheus, Grafana and Zipkin for monitoring and distributed tracing.
- Author validated Docker Compose locally, built Docker images for linux/amd64, tagged images with Git commit SHAs, authenticated Docker to Amazon ECR, and pushed images to ECR for AWS deployment.
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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.
End-to-End Containerized Deployment on AWS
A hands-on tutorial describing an end-to-end containerisation and deployment workflow: the author built a simple HTML web app, created a Dockerfile using the nginx base image, built a Docker image, tested it on an EC2 instance, pushed the image to Docker Hub, and deployed it to a Kubernetes Pod exposed via a NodePort service. The post documents command examples (docker build/run, docker push, kubectl apply) and the deployment flow from local files to a running container reachable through an EC2 public IP and nodePort (example: 30080). The author lists next learning steps including Deployments, ReplicaSets, Ingress, Secrets, autoscaling, CI/CD with GitHub Actions, and migrating to AWS EKS.
Blue-Green Deployment Pipeline on AWS EKS
A hands-on walkthrough demonstrating how to build a blue-green deployment pipeline on AWS EKS using Ubuntu and a terminal. The author provides exact commands, Kubernetes manifests, a multi-stage Dockerfile, and a GitHub Actions workflow that automates building, pushing to Amazon ECR, deploying to an idle environment, performing an internal health check, and switching traffic by patching the Service selector. The pipeline averages 29 seconds end-to-end, the traffic switch is under one second, and rollback under five seconds. The article also documents practical AWS-specific fixes (ELB hostnames, ECR node IAM policy), debugging tips, and a public repository (github.com/gbadedata/zero-downtime-bluegreen-eks). Recommended next steps include Prometheus/Grafana, canary releases, Terraform, and automated rollback triggers.
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