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From zero to mastering, it contains everything from the very basics to advanced concepts such as sampling, security, and scaling for production.

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To keep your OpenTelemetry journey going, we created a 6-episode video series that brings you everything you need to know about OpenTelemetry.

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If you have any questions or issues with any of these steps, feel free to reach out to us via chat or join our OpenTelemetry Slack channel (part of the CNCF Slack). That’s about it for this OpenTelemetry Java guide, folks. Our ability to quickly solve issues and fix errors in production relies heavily on how we visualize traces and the ease with which we can filter out and deep dive into our data. This is how we send traces to Jaeger: Export to Jaegerġ) Run Jaeger locally with the following docker command docker run -d -name jaeger \ Jaeger UI is the most commonly used open-source to visualize traces. Jaeger Tracing is a suite of open source projects managing the entire distributed tracing “stack”: client, collector, and UI. Getting Started with OpenTelemetry Java and Jaeger Tracing Our ability to visualize trace data is where the true troubleshooting power of this technology comes into play.įor visualization, we’ll be using the open-source Jaeger Tracing and Aspecto. But we’re not here only to have beautiful spans in our console – it’s all about visualization. INFO io. - '/owners/ represents an https call to fetch an owner by ID.Īt this point, we created spans and log them to our console. Now, the final output should look something like the one below.

In terms of implementing OpenTelemetry Java instrumentation in our project to collect traces, we’re pretty much done (keep reading, there’s more to it). The above command will automatically instrument most common libraries. We mentioned instrumentations earlier, the libraries that actually allow us to gather data from our apps. A span would usually be the parent and/or the child of another span. An HTTP request or a database operation that spans over time.

Span: A span represents an action/operation that occurred in our system.

For this guide, here are the key terms you need to know: There is much more to learn about OpenTelemetry and if you want to dive deeper into its structure, follow this guide. It combines all three aspects needed for proper monitoring (leading with tracing, followed by metrics). Since its implementation for most modern programming languages, it has been growing in popularity and usage by developers everywhere. It allows us to be vendor-agnostic and not tied down to a single tool and ship our data to any dedicated location (e.g., backend, OpenTelemetry collector, supporting open sources, and more). Led by the CNCF (Cloud Native Computing Foundation, the foundation responsible for Kubernetes), it serves as a single library that gathers data under a single specification.

Ultimately, we use this data to understand and investigate our system’s behavior and troubleshoot and debug performance issues and errors. Instrumenting means capturing telemetry data from events and operations in our distributed system. OpenTelemetry enables us to instrument our distributed services. OpenTelemetry is a collection of SDKs and APIs – an open-source project – that allows us to collect, generate, and export logs, metrics, and traces (also known as the three pillars of observability). No prior OpenTelemetry knowledge is needed – we will cover the basics here.įor this OpenTelemetry Java example, we’ll be using the Spring Pet Clinic project, to save you some time setting up an example project. This is a practical guide that brings you just what you need to get started with OpenTelemetry Java.