Microservices Mastery

Distributed Logging with Serilog & SEQ

1 Views Updated 5/4/2026

Distributed Logging

In a monolith, you look at one log file. In microservices, a single user request might span 10 services. If you have 10 separate log files, debugging a single error becomes impossible. Distributed Logging centralizes all logs into one searchable database.

1. Structured Logging (Serilog)

Never log simple strings like Log("User logged in"). Use Structured Logging: Log("User {UserId} logged in from {Ip}", user.Id, ip). This allows you to filter and query your logs like a database (e.g., "Show me all errors for User #55 across all services").

2. Centralized Sink (SEQ / ELK)

Every microservice sends its logs over the network to a central server. SEQ is a popular choice for .NET developers because it is easy to set up and provides a powerful UI for filtering logs by CorrelationId.

4. Interview Mastery

Q: "What is a CorrelationId and why is it the most important part of distributed logging?"

Architect Answer: "A CorrelationId is a unique GUID generated at the very first entry point (the API Gateway). This ID is passed in the header of every internal HTTP or Message call. When every service includes this ID in its logs, we can search for that one ID in SEQ and see the entire 'Life Story' of a request as it travelled through the system, even if it touched 20 different servers. Without CorrelationIds, distributed debugging is just guesswork."

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