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OpenTelemetry: Syllabus
Mastering OpenTelemetry: System Monitoring and Observability for Data Engineering
OpenTelemetry is an open-source observability framework that provides powerful tools for monitoring, tracing, and logging distributed applications. This book provides a hands-on approach to OpenTelemetry, covering real-time monitoring, distributed tracing, and integration with data engineering stacks for enhanced observability.
Module 1: Introduction to Observability and OpenTelemetry
- Understanding the fundamentals of observability
- The role of OpenTelemetry in modern system monitoring
- Comparing OpenTelemetry with Prometheus, Grafana, and Jaeger
- Installing and setting up OpenTelemetry SDKs and collectors
Module 2: OpenTelemetry Architecture and Components
- Key components: Traces, Metrics, and Logs
- Understanding OpenTelemetry SDKs and APIs
- OpenTelemetry Protocol (OTLP) and exporters
- Working with the OpenTelemetry Collector
Module 3: Instrumenting Applications with OpenTelemetry
- Auto-instrumentation vs. manual instrumentation
- Instrumenting Python, Java, and Go applications
- Using OpenTelemetry SDKs for custom instrumentation
- Exporting telemetry data to visualization tools
Module 4: Distributed Tracing with OpenTelemetry
- Understanding spans, traces, and context propagation
- Implementing distributed tracing in microservices
- Integrating OpenTelemetry with Jaeger and Zipkin
- Analyzing trace data for performance bottlenecks
Module 5: Metrics Collection and Performance Monitoring
- Understanding OpenTelemetry Metrics API
- Collecting system and application metrics
- Configuring Prometheus and Grafana for visualization
- Setting up alerts for real-time anomaly detection
Module 6: Centralized Logging with OpenTelemetry
- Logging architecture in OpenTelemetry
- Integrating OpenTelemetry with Loki, Elasticsearch, and Fluentd
- Correlating logs with traces and metrics
- Best practices for log aggregation and storage
Module 7: Deploying OpenTelemetry in Production
- Running OpenTelemetry in Kubernetes
- Configuring high availability and scalability
- Securing telemetry data with authentication and encryption
- Monitoring and troubleshooting OpenTelemetry components
Module 8: Observability for Data Engineering Stacks
- Implementing OpenTelemetry for Apache Kafka
- Monitoring Apache Spark jobs with OpenTelemetry
- Integrating OpenTelemetry with MinIO for object storage observability
- Using OpenTelemetry with PostgreSQL for database performance monitoring
Hands-On Projects
Project 1: Implementing Distributed Tracing in a Microservices Architecture
- Instrument a multi-service application with OpenTelemetry
- Visualize traces in Jaeger and troubleshoot performance issues
- Implement context propagation for end-to-end observability
Project 2: Real-Time Metrics Collection for a Streaming Data Pipeline
- Collect real-time metrics from an Apache Kafka pipeline
- Export metrics to Prometheus and visualize with Grafana
- Set up alerting rules for high-latency detection
Project 3: Centralized Logging for a Data Processing Workflow
- Configure OpenTelemetry for structured logging
- Integrate OpenTelemetry with Loki and Elasticsearch
- Correlate logs, traces, and metrics for root cause analysis
Project 4: Monitoring Apache Spark Jobs with OpenTelemetry
- Instrument Apache Spark for performance monitoring
- Track Spark job execution and resource utilization
- Generate automated alerts for failed or slow-running jobs
Project 5: Full-Stack Observability for a Data Engineering Pipeline
- Deploy OpenTelemetry in a Kubernetes-based data pipeline
- Integrate OpenTelemetry with Spark, Kafka, and MinIO
- Build a real-time observability dashboard in Grafana