My Notes

06 - Monitoring and Observability

3 min read

Monitoring and Observability

📊 Progress Tracking

TABLE WITHOUT ID
  "📈 Progress" as " ",
  length(filter(file.tasks, (t) => t.completed)) + "/" + length(file.tasks) + " tasks" as "Completed",
  round(length(filter(file.tasks, (t) => t.completed)) / length(file.tasks) * 100) + "%" as "Progress"
WHERE file.path = this.file.path

📋 Module Overview

Implement comprehensive monitoring, logging, and observability solutions

🎯 Learning Objectives

  • Master monitoring fundamentals
  • Master prometheus & grafana
  • Master logging & centralization
  • Master distributed tracing
  • Master cloud-native monitoring
  • Master monitoring projects

📚 Tasks & Exercises

1. Monitoring Fundamentals

  • Task 1.1: Monitoring vs observability concepts
  • Task 2.2: Metrics, logs, and traces (three pillars)
  • Task 3.3: SLIs, SLOs, and error budgets
  • Task 4.4: Alerting strategies and escalation
  • Task 5.5: Incident response and post-mortems

Practice: Complete practical exercises for monitoring fundamentals

2. Prometheus & Grafana

  • Task 1.1: Prometheus installation and configuration
  • Task 2.2: PromQL query language
  • Task 3.3: Service discovery and scraping
  • Task 4.4: Grafana dashboard creation
  • Task 5.5: Alertmanager setup and routing

Practice: Complete practical exercises for prometheus & grafana

3. Logging & Centralization

  • Task 1.1: ELK Stack (Elasticsearch, Logstash, Kibana)
  • Task 2.2: Fluentd/Fluent Bit for log collection
  • Task 3.3: Structured logging best practices
  • Task 4.4: Log aggregation and parsing
  • Task 5.5: Log retention and rotation

Practice: Complete practical exercises for logging & centralization

4. Distributed Tracing

  • Task 1.1: OpenTelemetry fundamentals
  • Task 2.2: Jaeger tracing implementation
  • Task 3.3: Zipkin setup and configuration
  • Task 4.4: Trace sampling and performance
  • Task 5.5: Correlation IDs and request tracking

Practice: Complete practical exercises for distributed tracing

5. Cloud-Native Monitoring

  • Task 1.1: Kubernetes monitoring with Prometheus
  • Task 2.2: Application Performance Monitoring (APM)
  • Task 3.3: Infrastructure monitoring with Datadog/New Relic
  • Task 4.4: Custom metrics and dashboards
  • Task 5.5: Cost monitoring and optimization

Practice: Complete practical exercises for cloud-native monitoring

6. Monitoring Projects

  • Task 1.1: Set up complete monitoring stack for Kubernetes
  • Task 2.2: Create comprehensive Grafana dashboards
  • Task 3.3: Implement distributed tracing for microservices
  • Task 4.4: Build alerting and incident response workflow

Practice: Complete practical exercises for monitoring projects

📖 Resources

Required Reading

Optional Materials

  • Explore additional resources as needed
  • Practice with real-world examples
  • Join community discussions

✅ Completion Criteria

Mark this module complete when you can:

  • Successfully complete all monitoring fundamentals tasks

  • Successfully complete all prometheus & grafana tasks

  • Successfully complete all logging & centralization tasks

  • Successfully complete all distributed tracing tasks

  • Successfully complete all cloud-native monitoring tasks

  • Successfully complete all monitoring projects tasks

  • Apply concepts in practical scenarios

  • Explain key concepts to others

📝 Notes Section

Use this space for your personal notes and insights while learning

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