Building Scalable Microservices: Pre-Production to Production Flow

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Building scalable applications with microservices demands a structured approach from development to deployment. Below is a detailed breakdown of the workflow, including key tools and commands.

Pre-Production Flow

1. API Definition

  • Tools: OpenAPI, Postman
  • Commands:
    Generate OpenAPI docs (Swagger) 
swagger-cli bundle api-spec.yaml -o openapi.json

2. Microservices Development

  • Frameworks: Java (Spring Boot), Node.js, React
  • Testing: Jenkins, JUnit
  • Commands:
    Run JUnit tests (Maven) 
mvn test

3. Containerization

  • Tools: Docker, Kubernetes
  • Commands:
    Build Docker image 
docker build -t my-service:1.0 .

Push to registry 
docker push my-registry/my-service:1.0

Deploy to Kubernetes 
kubectl apply -f deployment.yaml

Production Flow

1. Traffic Routing

  • Tools: NGINX, Cloudflare (CDN)
  • Commands:
    Reload NGINX config 
sudo nginx -s reload

2. API Gateway & Service Discovery

  • Tools: Spring Boot, Netflix Eureka
  • Commands:
    Start Eureka server 
java -jar eureka-server.jar

3. Database & Caching

  • Tools: Redis, Elasticsearch, Kafka

  • Commands:

    Check Redis status 
redis-cli ping

Elasticsearch health check 
curl -X GET "localhost:9200/_cluster/health"

4. Monitoring & Logging

  • Tools: Prometheus, Grafana, Kubernetes Dashboard

  • Commands:

    Check Kubernetes pods 
kubectl get pods

View logs 
kubectl logs <pod-name>

You Should Know:

  • CI/CD Automation

    Jenkins pipeline example (Jenkinsfile) 
pipeline { 
agent any 
stages { 
stage('Build') { 
steps { sh 'mvn clean package' } 
} 
stage('Deploy') { 
steps { sh 'kubectl apply -f k8s/' } 
} 
} 
}

  • Kubernetes Scaling

    Scale a deployment 
kubectl scale deployment my-app --replicas=5

  • Debugging Kafka

    List Kafka topics 
kafka-topics.sh --list --bootstrap-server localhost:9092

What Undercode Say:

Microservices architecture thrives on automation, observability, and modularity. Key takeaways:
– Use Docker & Kubernetes for seamless deployments.
– Implement API gateways (Eureka, Zuul) for traffic management.
– Monitor with Prometheus & Grafana for real-time insights.
– Ensure CI/CD pipelines (Jenkins, GitLab CI) for rapid iterations.

Expected Output:

A fully automated, scalable microservices ecosystem with:

✔ Zero-downtime deployments

✔ Real-time monitoring

✔ High availability via Kubernetes

Prediction:

Microservices will increasingly adopt AI-driven auto-scaling and serverless integration, reducing manual orchestration efforts.

Relevant URLs:

IT/Security Reporter URL:

Reported By: Goyalshalini Building – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅

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