📄️ OpenTelemetry
Complete introduction to OpenTelemetry (OTel): CNCF open source project for distributed systems observability, standardized telemetry collection, metrics, logs and distributed tracing with automatic and manual instrumentation.
📄️ Observability Concepts
Fundamental observability concepts: traces, metrics and logs for distributed systems. Differences between traditional monitoring and modern observability.
📄️ How Tracing Works
Understand how OpenTelemetry builds distributed traces: context propagation, trace ID, span ID, HTTP headers, automatic instrumentation, and how telemetry is shared between services.
📄️ Instrumentation vs Collection
Differences between instrumentation and collection in OpenTelemetry: automatic vs manual instrumentation, OpenTelemetry Collector as central hub, data processing, sidecar vs centralized and integration with observability systems.
📄️ Common Questions
Clarifications about OpenTelemetry: differences between Node Exporter and OTel, using Collector vs direct Exporters, hostmetrics, integration with Prometheus, Jaeger and Loki in production.
📄️ Grafana Cloud vs OpenTelemetry
Comparison between Grafana Cloud and OpenTelemetry: Grafana Agent as a bridge between local and cloud environments, integration with Prometheus, Loki, Tempo, and differences between collection approaches.
📄️ Grafana Agent and OpenTelemetry Operator
Grafana Agent vs OpenTelemetry Operator: differences between data collection and automatic instrumentation, sidecar configuration, custom resources, Grafana Cloud integration, and hybrid architecture.
📄️ Base Project
Base project to learn OpenTelemetry: Node.js application with Express, Redis, Docker Compose, auth and todo microservices, file structure, and development configuration.
📄️ Adding OpenTelemetry
How to add OpenTelemetry instrumentation to Node.js project: dependency installation, SDK configuration, automatic instrumentation, OTLP exporters, and trace configuration.
📄️ First Metrics
How to add metrics to an OpenTelemetry project: Prometheus configuration, endpoint scraping, metrics instrumentation, job configuration, and integration with the observability stack.
📄️ Metrics Types
Metrics types in OpenTelemetry: Counter, Gauge, Histogram, and UpDownCounter, their characteristics, use cases, and differences between each type.
📄️ Custom Metrics
Creating custom metrics with OpenTelemetry: histograms for latency, counters for requests, manual instrumentation, Express middleware, failure and latency simulation.
📄️ Logs and Traces
Correlation between logs and traces in OpenTelemetry: context propagation, unique identifiers, distributed debugging, span context, trace ID, error events, and log instrumentation.
📄️ Manual Spans
Manual span creation in OpenTelemetry: increasing tracing granularity, measuring specific operations, isolating critical code, advanced debugging, and detailed performance analysis.
📄️ Span Attributes
Span Attributes in OpenTelemetry: key-value set with detailed context, Jaeger tags, HTTP request information, database operations, distributed systems, and custom attributes.
📄️ SDK Configuration
Advanced OpenTelemetry SDK configuration: automatic instrumentation, available libraries, behavior customization, component deactivation, and trace optimization.
📄️ Resources
Resources in OpenTelemetry: execution environment metadata, difference between attributes and resources, environment auto-detection, cloud provider configuration and semantic conventions.
📄️ Sampling
Cost control with Sampling in OpenTelemetry: head vs tail sampling, sampling strategies, data volume control, sampler customization and resource optimization.
📄️ Performance
Performance and Context Propagation in OpenTelemetry: span flow, application impact, span processors, simple vs batch processing, optimized production configuration.
📄️ OpenTelemetry Collector
OpenTelemetry Collector vs SDK: differences between data generation and reception, telemetry processing, export, scalability and use as a bridge between vendor and local infrastructure.
📄️ Collector Processor
Collector Processors in OpenTelemetry: telemetry data processing, batch processor, resource processor, tail sampling, pipeline configuration and performance optimization.