Microservices Mastery

Health Checks: Monitoring system vitals in real-time

1 Views Updated 5/4/2026

Health Checks

Just because a .NET process is "Running" doesn't mean it is healthy. If the API survived but the Database connection is broken, the service is useless. Health Checks allow your infrastructure (Kubernetes, F5, Azure) to know if a service is actually capable of doing its job.

1. Liveness vs Readiness

  • Liveness: "Am I alive?" If this fails, K8s will physically restart the container. (Checks if the process is stuck in a loop).
  • Readiness: "Am I ready to handle traffic?" If this fails, K8s stops sending user traffic to this Pod but *doesn't* restart it. (Checks DB connection, Redis connection, etc).

2. HealthCheckUI

In .NET, we use the Microsoft.Extensions.Diagnostics.HealthChecks package. We can also add a dashboard (AspNetCore.HealthChecks.UI) that shows a "Green/Red" status for every microservice in the ecosystem on a single screen.

4. Interview Mastery

Q: "Why should a Health Check NEVER perform heavy business logic?"

Architect Answer: "Health checks are called frequently (usually every 10 seconds). If your health check performs a complex SQL JOIN or calls 5 other services, it will put unnecessary load on your system. A health check should be 'Shallow'—just verify that the socket can open and the basic connection is alive. If the health check itself causes a bottleneck, it might lead to a false-positive failure and trigger an unnecessary restart loop."

Microservices Mastery
1. Distributed Systems Fundamentals
Monolith vs Microservices: When to migrate? The 12-Factor App Methodology for Cloud-Native Apps Database Per Service: Handling distributed data consistency
2. Containerization & Orchestration
Docker Essentials: Building efficient .NET images Docker Compose: Orchestrating a multi-service environment Kubernetes Architecture: Pods, Services, and Deployments K8s ConfigMaps & Secrets: Managing environment variables Helm Charts: Packaging your microservices for K8s
3. Service Communication
Synchronous vs Asynchronous Communication: Pros and Cons REST APIs in a Microservices World: Best Practices Mastering gRPC: High-performance binary communication API Gateways: Implementing Ocelot for single-entry access BFF Pattern: Backend-for-Frontend (Mobile vs Web)
4. Event-Driven Architecture
Message Brokers: Introduction to RabbitMQ & Azure Service Bus Pub/Sub Pattern: Implementing MassTransit for .NET The Outbox Pattern: Ensuring 100% data consistency Dead Letter Queues: Handling message failure gracefully Distributed Transactions: The Saga Pattern (State Machines)
5. Resilience & Scalability
Distributed Caching with Redis: Optimizing global state Service Discovery: IdentityServer4 & Consul Load Balancing: Nginx vs Ingress Controllers The Sidecar Pattern: Offloading cross-cutting concerns
6. Observability & Security
Distributed Logging with Serilog & SEQ Distributed Tracing: OpenTelemetry & Jaeger Health Checks: Monitoring system vitals in real-time OAuth2 & OpenID Connect: Centralized Identity (AuthN/AuthZ) Rate Limiting & Throttling: Protecting your services
7. Advanced Cloud Topics
Infrastructure as Code (IaC): Introduction to Terraform CI/CD Pipelines for Microservices (GitHub Actions/Azure DevOps) C# Architect Interview: Microservices & System Design Focus