
Microservices deployment via Docker + Kubernetes
Why Choose This Project?
As applications grow, the monolithic approach becomes harder to manage and scale. Microservices architecture solves this by breaking the system into independent services that can be deployed, updated, and scaled separately.
This project demonstrates real-world DevOps practices by containerizing multiple services and deploying them using Kubernetes (K8s) with Docker, making it a great fit for Cloud Computing and DevOps portfolios.
What You Get
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Fully containerized microservices using Docker
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Kubernetes cluster with service discovery and networking
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Centralized configuration using ConfigMaps and Secrets
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Load balancing, auto-scaling, and self-healing containers
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CI/CD pipeline to deploy services automatically
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Monitoring and logging integration
Core Features
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Modular Microservices: Each service handles a single business logic (e.g., Auth, Product, Order, User)
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Dockerized Services: All services run in isolated containers
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Kubernetes Orchestration: Services deployed as K8s Deployments, exposed via Services
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API Gateway (like NGINX or Kong) for routing and authentication
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Service Discovery with Kubernetes DNS
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Secure Secrets & Configs: Stored using K8s Secrets and ConfigMaps
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Horizontal Pod Auto-scaling based on load
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Integrated Monitoring with Prometheus + Grafana
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Logging via Fluentd or ELK stack (optional)
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Rolling Updates & Rollbacks for safe deployments
Technology Stack
Layer | Technologies Used |
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Frontend (Optional) | React.js, Angular, or static HTML+Bootstrap |
Microservices | Node.js / Express, Python / Flask, GoLang / Gin |
Containerization | Docker, Docker Compose (for local setup) |
Orchestration | Kubernetes (minikube or cloud: GKE, EKS, AKS) |
API Gateway | NGINX / Kong / Istio |
Database | MongoDB / PostgreSQL / Redis |
CI/CD | GitHub Actions / Jenkins / GitLab CI |
Monitoring | Prometheus, Grafana, Loki, Fluentd |
Secrets Management | Kubernetes Secrets / HashiCorp Vault |
Architecture Flow
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Developers build each microservice independently.
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Docker is used to containerize each service.
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Kubernetes deploys each service with specified replicas.
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Services communicate internally via ClusterIP services and DNS.
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External access is routed through Ingress / API Gateway.
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Monitoring tools continuously watch performance and availability.
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CI/CD pipelines handle automatic builds, testing, and deployments.