This module guides learners through the process of deploying Prometheus in a Kubernetes environment, focusing on infrastructure setup, operator configuration, and monitoring validation. Learners will gain practical experience using Linode Kubernetes Engine, with concepts transferable to other platforms. By the end, participants will be able to implement and verify a functional monitoring stack.

This module delves into the inner workings of Prometheus's data model, including how time series and samples are structured and managed within the TSDB. Learners will also gain hands-on experience with PromQL, exploring its syntax, subqueries, and advanced features for querying and analyzing monitoring data. By the end, you'll be equipped to optimize data storage and retrieval for effective monitoring and alerting.

This module delves into the mechanisms of service discovery in Prometheus, highlighting its dynamic monitoring capabilities in both cloud-native and traditional environments. Learners will explore standard and metric relabeling, as well as how to leverage custom HTTP service discovery endpoints for flexible infrastructure monitoring.

This module guides learners through configuring Prometheus alerting rules and mastering Alertmanager features such as alert grouping, routing, and templating. You will also explore strategies for high availability and best practices for testing alerting rules to ensure reliable and actionable notifications.

This module delves into advanced strategies for scaling and securing Prometheus monitoring systems. Learners will explore sharding to manage high cardinality, federation for unified data views, and techniques to achieve high availability. By the end, you'll be equipped to architect resilient and scalable monitoring solutions.

This module guides learners through advanced techniques for optimizing Prometheus performance, including managing cardinality, leveraging profiling tools, and tuning garbage collection. Learners will also discover how to set scrape and query limits to prevent performance bottlenecks and ensure efficient monitoring at scale.

This module introduces learners to the Node Exporter, a key tool for collecting system metrics in infrastructure monitoring. You will explore its default and specialized collectors, learn how to use the textfile collector, and gain troubleshooting skills to ensure effective data collection for Prometheus-based monitoring.

This module introduces the integration of remote storage solutions with Prometheus, focusing on remote write/read capabilities, and the deployment of VictoriaMetrics and Grafana Mimir for scalable monitoring. Learners will gain practical skills in configuring, deploying, and optimizing these systems within modern observability stacks.

This module introduces the core components of Thanos and demonstrates how to extend Prometheus for global, scalable monitoring. Learners will explore the deployment and configuration of Thanos Sidecar, Compactor, Query, Query Frontend, Store, Ruler, and Receiver to aggregate and optimize metrics across distributed environments. By the end, you'll understand how to build a robust, multi-region monitoring solution.

This module introduces Jsonnet as a powerful tool for generating and managing YAML configurations, emphasizing code reuse and maintainability. Learners will explore key Jsonnet features such as string interpolation, object inheritance, imports, and functions, and discover how to leverage Monitoring Mixins for scalable Prometheus monitoring setups.

This module guides learners through integrating Prometheus configuration validation and rule linting into CI pipelines using tools like promtool, Pint, and amtool. By automating these checks with GitHub Actions, you will enhance reliability and reduce errors in your monitoring infrastructure. Practical workflows and tool usage are demonstrated to streamline your DevOps processes.

This module introduces the fundamentals of defining and monitoring service-level objectives (SLOs) using Prometheus metrics. Learners will explore different types of SLOs, understand how to leverage open-source tools like Sloth and Pyrra, and gain practical skills for implementing effective reliability monitoring strategies.

This module introduces the principles of observability using OpenTelemetry and demonstrates how to integrate it with Prometheus for standardized telemetry data collection. Learners will explore the role of the OpenTelemetry Collector as an intermediary in telemetry pipelines and understand best practices for connecting these tools.

This module introduces learners to observability tools and techniques that go beyond Prometheus metrics, including the roles of logs and traces. You will explore the strengths and limitations of different observability signals and learn how to integrate them for comprehensive system monitoring.