is quickly becoming the industry standard for observability. The release of the specification established a standardized way to handle traces, metrics and logs, reducing the need for multiple integrations or major rewrites as monitoring distributed solutions and interoperability requirements grow. As OpenTelemetry expands to support logs and profiling, OTLP ensures a consistent transport format across all telemetry data, simplifying instrumentation and making full-stack observability more accessible and scalable for microservices architectures.
Adopted by vendors like , and , OTLP enables organizations to build flexible, vendor-agnostic observability stacks without being locked into proprietary solutions. It supports gzip and zstd compression, reducing telemetry data size and lowering bandwidth usage ¡ª a key advantage for environments handling high volumes of telemetry data. Designed for long-term growth, OTLP ensures OpenTelemetry remains a robust and future-proof standard, solidifying its position as the de-facto choice for telemetry transport.
We've been using as a solution for a while now and recommended trying it in previous editions. Its ability to seamlessly capture, instrument and manage telemetry data across various services and applications has improved our observability stack. OpenTelemetry's flexibility and compatibility with diverse environments have made it a valuable addition to our toolkit. We're now particularly curious about the recent release of the specification, which includes both gRPC and HTTP. This protocol standardizes the format and transmission of telemetry data, promoting interoperability and simplifying integrations with other monitoring and analysis tools. As we continue to explore the integration potential of the protocol, we're evaluating its long-term impact on our monitoring and observability strategy and on the general monitoring landscape.
is an open source observability project that merges and . The OpenTelemetry project includes , libraries, agents, and other components needed to capture telemetry from services to better observe, manage and debug them. It covers the three pillars of observability ¡ª distributed tracing, metrics and logging (currently in beta) ¡ª and its specification connects these three pieces through ; thus you can use metrics to pinpoint a problem, locate the corresponding traces to discover where the problem occured, and ultimately study the corresponding logs to find the exact root cause. OpenTelemetry components can be connected to back-end observability systems such as Prometheus and Jaeger among . Formation of OpenTracing is a positive step toward the convergence of standardization and the simplification of tooling.
As monolithic applications are being replaced with more complex (micro)service ecosystems, tracing requests across multiple services is becoming the norm. With majority contribution from LightStep and Uber is rapidly becoming the de facto standard for distributed tracing. There is a growing number of supporting OpenTracing standard, including Zipkin, Instana, and . OpenTracing currently provides vendor-neutral implementation in multiple languages including: Go, JavaScript, Java, Python, Objective-C, C#, C++, Ruby and PHP.
As monolithic applications are being replaced with more complex (micro)service ecosystems, tracing requests across multiple services is becoming the norm. With majority contribution from LightStep and Uber is rapidly becoming the de facto standard for distributed tracing. There is a growing number of supporting OpenTracing standard, including Zipkin, Instana, and . OpenTracing currently provides vendor-neutral implementation in multiple languages including: Go, JavaScript, Java, Python, Objective-C, C#, C++, Ruby and PHP.
