Garanti del Talento

dgt_k8s07 – Monitoring

Course Title: dgt_k8s07 – Monitoring

Overview:

In Kubernetes (k8s), monitoring is needed to verify that applications and clusters operate correctly. The “dgt_k8s07 – Monitoring” course covers how monitoring solutions built on Prometheus, Grafana, and Alertmanager work within a Kubernetes environment, and how to put those solutions in place by instructing an AI agent in natural language.

Here the approach is concrete: once you understand the Prometheus data model, scraping and alert routing, you ask the machine to install the stack, to build a dashboard showing pod restarts per namespace, or to page the on-call team when error rates stay high for five minutes. Then you read the PromQL, the alert rules and the routing tree it wrote, check that they really measure what you asked for, and fix the thresholds or labels it got wrong.

Course Objectives:

  • Understand the Basics: Learn why monitoring is needed in a Kubernetes ecosystem.
  • Learn Key Tools: Study the functionalities of Prometheus for metrics collection, Grafana for data visualization, and Alertmanager for alert management.
  • Operational Proficiency: Learn to direct the machine to deploy and configure these tools through the Prometheus Stack Operator, and to verify that the deployment is correct.
  • Integration Skills: Understand how these monitoring components fit together in a Kubernetes cluster well enough to review and validate every integration the machine performs.

Course Modules:

  1. Introduction to Kubernetes Monitoring:
  2. Importance of monitoring in containerized environments.

  3. Overview of challenges in monitoring Kubernetes clusters.

  4. Prometheus: Metrics Collection and Analysis:

  5. Introduction to Prometheus architecture and data model.
  6. Scraping metrics from Kubernetes components: what to ask for and how to check the targets.

  7. Reading and validating the PromQL queries the machine writes for metric analysis.

  8. Grafana: Visualization and Dashboards:

  9. Grafana within a Kubernetes cluster.
  10. Describing the custom dashboards you need to visualize Kubernetes metrics and reviewing the panels produced.

  11. Best practices for dashboard design and usage.

  12. Alertmanager: Alert Management:

  13. Alert routing, deduplication, and grouping in Alertmanager.
  14. Alert rules in Prometheus that trigger notifications: specifying conditions and checking the generated rules.

  15. Integrating with notification channels like email, Slack, or PagerDuty.

  16. Prometheus Stack Operator:

  17. Importance of using the Prometheus Stack Operator to simplify deployments.
  18. How the Prometheus Stack Operator is deployed, step by step, so you can guide and verify the process.

  19. Managing a complete stack (Prometheus, Grafana, Alertmanager) with minimal manual intervention.

  20. Advanced Monitoring Techniques:

  21. Service monitoring, node-level metrics, and application-specific metrics.
  22. Using recording rules for optimized query performance.

  23. Enhancing alerting strategies with multi-tiered alert policies.

  24. Natural-language Lab Exercises:

  25. Practical exercises in which you instruct the machine to deploy and configure the Prometheus Stack in a Kubernetes cluster, then verify targets, rules and dashboards.

  26. Real-world scenarios in which you request dashboards and alerts that mimic production environments and catch what the machine got wrong.

  27. Best Practices and Optimization:

  28. Optimizing resource usage for monitoring components.
  29. Security considerations when deploying monitoring solutions.
  30. Scaling the monitoring stack with growing clusters and workloads.

Target Audience:

This course is designed for DevOps professionals, system administrators, Kubernetes practitioners, and IT engineers who work on cloud-native application monitoring. Prior knowledge of Kubernetes basics is recommended but not mandatory, as the course covers the essential concepts where necessary.

Course Outcome:

By the end of this course, participants will be able to have a fully functional monitoring stack based on Prometheus, Grafana, and Alertmanager deployed in a Kubernetes environment purely through natural-language instructions, and to verify every query, rule and dashboard it contains. They will understand how the Prometheus Stack Operator simplifies deployment and how to ensure comprehensive visibility into their applications and infrastructure.
The students can push their exercises to the Academy DevOps & SRE Git project. For this module, create a folder with your username as its name in the following subfolder: https://github.com/Garanti-Del-Talento/gdt_academy/tree/main/dgt_k8s07__monitoring