Quick wins for a faster PC:
Scan for outdated or missing drivers - takes under a minuteDriver Scan →Repair Windows errors before they cause bigger problemsFix Now →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →You can add OpenTelemetry tracing to Dagster’s Python processes without editing asset code: install the OpenTelemetry Python distro and OTLP exporter, bootstrap instrumentation for supported libraries, configure the service name and trace endpoint, then launch each target process with opentelemetry-instrument. The key caveat is that Dagster work can run in separate processes, containers, or external tasks. Instrumenting the webserver does not automatically instrument a run worker, and library auto-instrumentation does not automatically create spans for your assets or ops.
What zero-code tracing does in a Dagster deployment
OpenTelemetry’s Python zero-code agent loads instrumentation at process startup and modifies supported library functions at runtime. This can produce spans for activity such as supported HTTP requests, database calls, or messaging operations without changing application source. The OpenTelemetry project describes this approach in its zero-code instrumentation overview.
That is not the same as a complete trace of Dagster execution. OpenTelemetry cautions that “Your application’s code, however, is not typically instrumented.” Consequently, an automatically created trace may show instrumented library calls but omit meaningful boundaries such as an asset, op, or business operation. If those boundaries are necessary to answer your debugging question, add code-based spans for them. Check the current Python instrumentation documentation and registry for the libraries and versions in your environment.
Install and configure the Python agent
Run these steps in the Python environment used by each Dagster process you want to trace. The endpoint and authentication values depend on your OTLP-compatible backend; use its documented values rather than assuming an example endpoint will work.
Crashes, No Sound, or Screen Glitches?
Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteWindows Errors? Fix Them Before They Spread
Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstall#1 Best Overall
-
Install the distro and OTLP exporter packages in the target environment:
pip install opentelemetry-distro opentelemetry-exporter-otlp. -
In that same environment, run
opentelemetry-bootstrap -a install. This detects installed libraries and adds matching instrumentation packages. Review what it installs and confirm the libraries you care about are supported. -
Configure a stable service identity, select the trace exporter, and set the backend’s OTLP traces endpoint. For example, set
OTEL_SERVICE_NAME,OTEL_TRACES_EXPORTER=otlp, andOTEL_EXPORTER_OTLP_TRACES_ENDPOINT. Configure any required credentials or other backend-specific settings as well. -
Start the Dagster-related Python entry point with
opentelemetry-instrumentso the agent loads in that interpreter. The Python guide documents both CLI and environment-variable configuration: OpenTelemetry Python zero-code instrumentation.Special offer. See more information about Outbyte and uninstall instructions. Please review EULA and Privacy policy. -
Check the trace backend for spans from the expected process. If traces stop at a process boundary, verify that the child process or external task has the packages installed, starts with the agent, receives the OTEL settings, and can reach the endpoint.
Put the agent where Dagster actually runs the work
Dagster execution topology determines which Python runtime must be instrumented. Its run-executor documentation describes in-process execution, multiprocess execution that launches steps in their own processes, and executors that send work to external systems such as Kubernetes pods, ECS tasks, Docker containers, or Celery tasks. Treat each separate runtime as an instrumentation target unless the deployment mechanism explicitly installs and starts the agent there.
| Execution or deployment case | Where to install and start the agent | What to verify |
|---|---|---|
| In-process execution | The Python environment and process running the Dagster code. | That the entry point serving or launching the work starts under opentelemetry-instrument and has the OTEL settings. |
| Multiprocess steps | The parent runtime and each step process that should emit spans; do not assume a child inherits the agent or configuration. | Inspect a step trace and confirm the child process has its own instrumentation startup, environment, and endpoint access. |
| External task or container execution | The image or runtime that executes the task, in addition to any Dagster service whose activity you also want to trace. | Confirm the external runtime includes the Python packages and startup wrapper and receives the service and exporter settings. |
| Docker Compose deployment | Each relevant service, code-location image, and run image or container. | Check the actual image used for the location’s runs, rather than only checking the webserver image. |
Dagster’s Docker Compose deployment guide describes separate webserver and daemon containers, code locations with their own image, and runs that typically execute in their own containers. In the documented example, a code-location image is used for runs launched for that location. Bake the agent into each image whose activity should appear in traces, and provide its configuration to that runtime.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Account for the Dagster deployment mode
The right place to inject the agent depends on whether you run Dagster OSS, Dagster+ Serverless, or Dagster+ Hybrid. These modes have different deployment and worker boundaries; use Dagster’s deployment overview to identify the runtime that executes your code, then verify how that mode supplies packages, environment variables, and startup configuration to it.
Best Value
Dagster’s dagster.yaml reference covers instance-level deployment configuration and the use of environment variables for values. It does not replace installing and loading the Python instrumentation agent inside each target interpreter.
Diagnose missing or incomplete spans
- You see Dagster service traces but not run traces: Check whether the run uses a distinct worker, step process, container, or external task. Install and start the agent in that runtime and pass it the OTEL configuration.
- You see library calls but no asset or op spans: That is a boundary the zero-code agent may not create. Add code-based instrumentation where application-level spans are needed.
- You see no expected library spans: Confirm that bootstrap installed the relevant instrumentation package, that the library version is supported, and that the target process actually starts under the agent.
- The process is instrumented but nothing arrives: Check the configured trace endpoint, backend authentication requirements, and network access from the emitting runtime.
There is no Dagster-specific tracing overhead or coverage measurement established in the cited official sources, so performance impact and span coverage should be assessed in your own deployment rather than inferred from a general claim. OpenTelemetry’s documentation overview says the framework is “supported by more than 90 observability vendors”; that is an ecosystem figure attributed to the OpenTelemetry project, whose page was last modified August 29, 2025—not a measure of Dagster compatibility. See OpenTelemetry documentation.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
