Easily collect telemetry like metrics and distributed traces from your services
OpenCensus and OpenTracing have merged to form OpenTelemetry, which serves as the next major version of OpenCensus and OpenTracing. OpenTelemetry will offer backwards compatibility with existing OpenCensus integrations, and we will continue to make security patches to existing OpenCensus libraries for two years.
What is OpenCensus?
We provide libraries for Go, Java, C#, Node.js, C++, Ruby, Erlang/Elixir, Python, Scala and PHP.
Supported backends include Azure Monitor, Datadog, Instana, Jaeger, SignalFX, Stackdriver, and Zipkin. You can also add support for other backends.
Who is behind it?OpenCensus originates from Google, where a set of libraries called Census are used to automatically capture traces and metrics from services. Since going open source, the project is now composed of a group of cloud providers, application performance management vendors, and open source contributors. The project is hosted on GitHuband all work occurs there.
What data can OpenCensus collect?Metrics are any quantifiable piece of data that you would like to track, such as latency in a service or database, request content length, or number of open file descriptors. Viewing graphs of your metrics can help you understand and gauge the performance and overall quality of your application and set of services.
Traces show you how a request propagates throughout your application or set of services. Viewing graphs of your traces can help you understand the bottlenecks in your architecture by visualizing how data flows between all of your services.
Other types of telemetry will be added to OpenCensus as the project matures. Logs will likely be added next.
In this section we will walk through what OpenCensus is, what problems it solves, and how it can help your project.
Or, if you are ready to integrate OpenCensus in to your project, visit the Quickstart.
OverviewOpenCensus provides observability for your microservices and monoliths alike by tracing requests as they propagate through services and capturing critical time-series metrics.
The core functionality of OpenCensus is the ability to collect traces and metrics from your app, display them locally, and send them to any analysis tool (also called a ‘backend’). However, OpenCensus provides more than just data insight. This page describes some of that functionality and points you to resources for building it into your app.
After instrumenting your code with OpenCensus, you will equip yourself with the ability to optimize the speed of your services, understand exactly how a request travels between your services, gather any useful metrics about your entire architecture, and more.
Features Context PropagationIn order to correlate activities and requests between services with an initial customer action, context (usually in the form of trace or correlation ID) must be propagated throughout your systems. Performing this automatically can be quite difficult, and a lack of automatic context propagation is often identified as the biggest blocker to an organization adopting distributed tracing. OpenCensus provides automatic context propagation across its supported languages and frameworks, and provides simple APIs for manually propagating or manipulating context.
OpenCensus supports several different context propagation formats, and is the reference implementation of the official W3C HTTP tracing header.
Distributed Trace CollectionOpenCensus captures and propagates distributed traces through your system, allowing you to visualize how customer requests flow across services, rapidly perform deep root cause analysis, and better analyze latency across a highly distributed set of services. OpenCensus includes functionality like context propagation and sampling out of the box and can interoperate with a variety of tracing systems. You can learn more about OpenCensus’ distributed tracing support here.
Time-series Metrics Collection