Microservices & Event-Driven Architecture (EDA) Mastery

Metrics and Dashboards: Prometheus and Grafana

1 Views Updated 5/4/2026

Visualizing System Health

Logs tell you 'What' happened; Metrics tell you 'How' your system is feeling. Dashboards are the cockpit of your architectural engine.

1. Prometheus (The Collector)

Prometheus uses a 'Pull' model. It scrapes an `/metrics` endpoint on your .NET app every 15 seconds. It record **Quantities**: - CPU / Memory usage. - Active thread count. - HTTP request throughput and failure rates. - Database connection pool health.

2. Grafana (The Artist)

Grafana connects to Prometheus and turns the data into beautiful, real-time graphs. **Architect Tip:** A 'Red' dashboard in the office (or on a shared Slack channel) is the fastest way to alert the team that the latest deployment is causing a memory leak or a performance regression.

3. AlertManager

Don't stare at dashboards. Use **AlertManager** to trigger Slack/PagerDuty notifications when a metric crosses a dangerous threshold (e.g., 'Error rate > 5% for more than 2 minutes').

4. Interview Mastery

Q: "What are the 'Golden Signals' you monitor for every service?"

Architect Answer: "Google's 4 Golden Signals: **Latency** (time to complete), **Traffic** (demand/requests per second), **Errors** (rate of failure), and **Saturation** (how 'full' the service is, e.g., memory/CPU). If these four are healthy, the service is likely healthy."

Microservices & Event-Driven Architecture (EDA) Mastery
1. Foundations of Microservices
The Monolith to Microservices transition: When and why? Domain Driven Design (DDD): Bounded Contexts and Aggregates Database Per Service: Managing data consistency Service Discovery and Health Checks in .NET
2. Communication Patterns
Synchronous Communication: HTTP/gRPC and Service Mesh Asynchronous Communication: Message Brokers (RabbitMQ/Kafka) API Gateways: YARP (Yet Another Reverse Proxy) vs Ocelot Protobuf and Shared Contracts: Managing breaking changes
3. Event-Driven Architecture (EDA)
Introduction to EDA: Producers, Consumers, and Topics The Publisher/Subscriber Pattern in .NET Event Sourcing: Capturing every state change CQRS (Command Query Responsibility Segregation) with MediatR
4. Distributed Transactions & Resiliency
The Saga Pattern: Orchestration vs Choreography The Outbox Pattern: Ensuring reliable message delivery Idempotency: Preventing duplicate message processing Distributed Locking with Redis (Redlock)
5. Observability & Monitoring
Distributed Tracing with OpenTelemetry Centralized Logging: ELK Stack (Elasticsearch, Logstash, Kibana) Metrics and Dashboards: Prometheus and Grafana Correlation IDs: Tracking requests across services
6. Security & Identity
Centralized Authentication: IdentityServer4 & Duende Identity OAuth2 and OIDC Flow for Microservices API Key Management and Rate Limiting Mutual TLS (mTLS) for Internal Service-to-Service Security
7. Infrastructure & Deployment
Containerization: Production-grade Dockerfiles Kubernetes for .NET: Pods, Services, and Ingress Helm Charts: Managing complex deployments Blue-Green and Canary Deployments in K8s
8. FAANG Microservices Case Studies
Case Study: Designing a Global Notification Engine (Reliability at Scale) Case Study: Building a High-Performance Logging Pipeline (PB/Day)