OpenTelemetry

OpenTelemetry: OpenTelemetry is an open source observability framework created when CNCF merged the OpenTracing and OpenCensus projects.[65] OpenTracing offers “consistent, expressive, vendor-neutral APIs for popular platforms”[66] while the Google-created OpenCensus project acts as a “collection of language-specific libraries for instrumenting an application, collecting stats (metrics), and exporting data to a supported backend.”[67] 

Under OpenTelemetry, the projects create a “complete telemetry system [that is] suitable for monitoring microservices and other types of modern, distributed systems — and [is] compatible with most major OSS and commercial backends.”[68] It is the “second most active” CNCF project.[69] In October 2020, AWS announced the public preview of its distro for OpenTelemetry.[70]

Wikipedia

https://opentelemetry.io describes OpenTelemetry as “a collection of APIs, SDKs, and tools. Use it to instrument, generate, collect, and export telemetry data (metrics, logs, and traces) to help you analyze your software’s performance and behavior.“

OpenTelemetry is generally available across several languages and is suitable for production use.

You can follow OpenTelemetry’s blog here: https://opentelemetry.io/blog/

OpenTelemetry enables comprehensive observability by integrating distributed tracing, metrics, and logs across various application layers and environments. Examples include:

Distributed Tracing

  • Tracking a request as it flows through multiple microservices, capturing spans for each service interaction, and visualizing the end-to-end latency and bottlenecks in systems like Jaeger or Zipkin.
  • Instrumenting HTTP handlers, database queries, and RPC calls to create trace data, which helps diagnose where failures or performance issues occur.

Metrics Collection

  • Gathering infrastructure metrics such as CPU, memory usage, and network I/O, as well as custom application metrics like request duration, error counts, and throughput.
  • Exporting metrics to platforms like Prometheus for real-time monitoring and alerting, enabling fast response to anomalies.

Logging Correlation

  • Enriching application logs with trace and span IDs so that developers can link logs directly to traces, making it easier to contextually analyze incidents.
  • Sending logs to log management systems like Loki or Elasticsearch, alongside metrics and trace data, for unified querying and troubleshooting.

K8s OpenTel example

  • In a Kubernetes-based microservice architecture, OpenTelemetry is used to instrument all services. Traces track requests between services, metrics capture latency and error rates, and logs include trace context. This comprehensive telemetry allows teams to visualize SLAs, quickly investigate outages, and correlate issues between signals for rapid root cause analysis.

These patterns demonstrate how OpenTelemetry provides a holistic observability solution beyond siloed tracing, metrics, or logging, improving visibility and accelerating issue resolution in distributed architectures.