By implementing service registry, use load balancers, and add circuit breakers for resilience.

To architect a scalable microservices system:

• Use an API Gateway for routing and access control

• Service discovery via tools like Consul, Eureka, or Kubernetes DNS

• Load balancing with Envoy, NGINX, or built-in cloud balancers

• Container orchestration using Kubernetes for scaling and resilience

• Centralized logging and monitoring (e.g., ELK, Prometheus + Grafana)

• Resilience patterns: retries, circuit breakers, timeouts for fault tolerance

This setup ensures scalability, reliability, and maintainability.

You design a scalable microservices system by running your services on a container orchestrator like Kubernetes so you get built-in service discovery (kube-dns), automated scheduling, pod-level health checks, and horizontal scaling, then add a service mesh (Istio or Linkerd) or an edge/load balancer (Ingress with an external LB or cloud L4/L7) to handle traffic routing, retries, circuit breakers, canaries, and observability; make each service stateless where possible, use readiness and liveness probes so the platform only routes to healthy instances, expose stable service names (or use headless services for direct pod discovery when needed), autoscale via HPA/VPA based on CPU/memory or custom metrics, and front your cluster with an API gateway or CDN for global load balancing and caching—add centralized logging, tracing (OpenTelemetry), and metrics (Prometheus + Grafana) to detect hotspots, and apply rate limits, quotas, and graceful shutdown to avoid overload and cascading failures. A minimal Kubernetes example that shows a Deployment with probes and a ClusterIP Service to enable discovery and load balancing looks like this:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-service
spec:
  replicas: 3
  selector: { matchLabels: { app: my-service } }
  template:
    metadata: { labels: { app: my-service } }
    spec:
      containers:
      - name: app
        image: your-registry/my-service:latest
        ports: [{ containerPort: 8080 }]
        readinessProbe:
          httpGet: { path: /healthz, port: 8080 }
          initialDelaySeconds: 5
          periodSeconds: 10
        livenessProbe:
          httpGet: { path: /live, port: 8080 }
          initialDelaySeconds: 15
          periodSeconds: 20
---
apiVersion: v1
kind: Service
metadata:
  name: my-service
spec:
  selector: { app: my-service }
  ports: [{ port: 80, targetPort: 8080 }]
  type: ClusterIP

Use a service registry for automatic service discovery, deploy a load balancer (like Nginx or Envoy) to distribute traffic, and design microservices to be stateless with horizontal scaling, plus implement health checks and retries for reliability.

Scalable Microservices Architecture with Service Discovery & Load Balancing

Microservices: Split functionality into independent, stateless services.

Service Discovery: Use tools like Consul or Kubernetes DNS for dynamic service lookup.

Load Balancing: Distribute traffic with client-side libraries or proxies like NGINX and Envoy.

API Gateway: Centralize routing, security, and rate limiting.

Service Mesh (optional): Add advanced traffic control and observability (Istio, Linkerd).

Container Orchestration: Use Kubernetes for scaling and self-healing.

Monitoring & Logging: Centralize logs and metrics for health and performance tracking.