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Supported Runtimes

Odigos provides automatic instrumentations for the following runtimes:

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Enrich with OpenTelemetry APIs

Odigos automatically generates data for open-source libraries and frameworks. Additional trace spans, metrics datapoints and log records can be added using the OpenTelemetry APIs. Odigos will automatically capture this data and deliver it to the chosen destination alongside the automatically generated data.

Select a language to learn how to enrich your data with OpenTelemetry APIs:

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Instrumentation Flow:

1. User selects a workload to auto instrument by creating a Source object (per workload or per namespace).
2. Odigos instrumentor component watches for changes with Source objects, and creates a relative InstrumentationConfig object.
3. Odigos odiglet component watches for changes with the InstrumentationConfig objects, and runs a runtime inspection on running pods to detect the programming language for every container.
4. Odigos instrumentor component watches for changes with the InstrumentationConfig object, and adds a resource request into each pod spec of all relevant containers in the workload manifest. These resource requests are called Instrumentation Devices.
5. Kubernetes detects the changes in the manifest, and rollout-restarts the pods with the new Instrumentation Devices.
6. New pods are scheduled and started. Odiglet resolves the resource request by mounting the auto instrumentation code and relevant environment variables into the container.
7. The auto instrumentation code starts the OpenTelemetry SDK and sends telemetry data to the odigos pipeline.

In case of a failure to instrument a workload, Odigos will disable the instrumentation and rollback the workload, This behaviour can be disabled by running bash odigos config set rollback-disabled true or via the helm chart autoRollback.disabled=false