This module guides learners through setting up a local development environment, with a focus on Windows users installing and using WSL. It covers essential tools, workflows, and resources to support hands-on learning and lab activities.

This module covers the fundamentals of observability in modern software systems, including the three pillars of metrics, logs, and traces, how to measure system performance, and how to apply service level indicators and objectives to manage reliability and risk.

This module provides hands-on experience in setting up and integrating key components of an observability stack, including Prometheus for metrics, Loki for logs, and Tempo for tracing. Learners will gain practical skills in deploying these tools and connecting them to a sample application for comprehensive monitoring and analysis.

This module introduces the core concepts of OpenTelemetry, covering its role in modern instrumentation, the distinction between API and SDK, and the importance of semantic conventions in standardizing telemetry data. Learners will gain an understanding of how to effectively implement and utilize OpenTelemetry in observability practices.

This module provides an in-depth look at the OpenTelemetry Collector, covering its architecture, deployment, and configuration. Learners will gain hands-on experience with setting up a development environment, deploying the collector, and validating data flow. It also includes practical labs to reinforce understanding of telemetry pipelines and monitoring.

This module covers the fundamentals of metrics instrumentation using OpenTelemetry, including auto-instrumentation, manual instrumentation, and exporting metrics to Prometheus. Learners will gain hands-on experience in defining custom business metrics and validating telemetry data for observability.

This module explores the fundamentals of trace instrumentation using OpenTelemetry, covering both auto-instrumentation and manual methods. Learners will gain hands-on experience in setting up, debugging, and maintaining distributed tracing in applications. The module emphasizes practical techniques for improving visibility and debugging performance issues.

This module provides an in-depth look at log instrumentation using OpenTelemetry, covering both auto-instrumentation and manual logging techniques. Learners will explore how to validate log setups, correlate logs with traces in Grafana, and manage configuration externally for better flexibility and maintainability.

This module explores the essential practices of instrumenting worker services for observability, focusing on metrics, logs, and traces. Learners will gain hands-on experience with auto-instrumentation techniques and understand how to integrate these with observability platforms. The module emphasizes context propagation and validation of telemetry in distributed systems.

This module covers the principles and practical implementation of context propagation in distributed systems, focusing on how to maintain trace visibility across different services. Learners will gain hands-on experience with injecting and extracting trace contexts in frontend and worker environments, ensuring seamless distributed tracing. The module also includes validation techniques and bidirectional propagation strategies.

This module focuses on advanced techniques for instrumenting software systems, including adding custom metrics, spans, and structured logging. Learners will explore how to enhance observability through tools like Redis exporters and environment-driven configurations. The content builds practical skills in monitoring, debugging, and improving system performance.

This module focuses on the process of deploying applications and observability tools using Kubernetes. Learners will gain hands-on experience with writing and validating Kubernetes manifests, as well as implementing best practices for configuration management and telemetry verification.