Build the safeguards
Eight explained steps, a source example and a checkpoint at each decision.
Read the tutorialOpenTelemetry / Observability / SLOs
Start in your browser, then take the complete Request Tracing Lab into an independent local environment.
Download and extract the ZIP into a new folder. With Python 3 installed, open a terminal in that folder and run the command below. It serves only this package on loopback; opening index.html directly is insufficient for workers and WebAssembly.
python preview.pyOpen http://127.0.0.1:4210/ in your browser. Stop the server with Ctrl+C. The prebuilt preview needs no dependency installation and makes no automatic requests to another site. The source code and notices are included alongside it.
The commands below start in the extracted package root. Node-based examples require Node 24 or later; the Go adapter requires Go 1.27 or later; the Python adapter requires Python 3.11 or later. Install only the toolchain used by this lab. Exact dependency versions and the Node lockfile are in the download.
npm ci
npm test
node src/observability/server.mjsBoth versions return eight successful responses. The safeguarded trace contains the request, service and database spans under one trace ID. A long tail remains visible even though availability is 100%.
Read GETTING_STARTED.md for the native request examples and shutdown steps. Native servers bind to 127.0.0.1. The optional monitoring containers expose only loopback ports. They are a separate exercise from the browser preview.
Add a second concurrent dependency and show why child durations cannot simply be summed to explain total latency. Then define an eligible-event rule and test an alert against low-traffic and no-traffic periods.
Add the expected result first, reproduce the failure, repair it, then rerun the native and browser checks. Use npm run rebuild for the Node/browser examples. The Go package includes rebuild_wasm.py; the Python package includes refresh_source.py.
Capture the scenario, edition, input records, observed outcome and the test that checks it. Explain one alternative you rejected and why. Avoid converting a small local result into a throughput, security or accuracy claim about a production system.
Prefect’s platform opening explicitly includes service indicators, error budgets and OpenTelemetry-style monitoring.
Eight explained steps, a source example and a checkpoint at each decision.
Read the tutorialUnderstand where each pattern helps and which tradeoffs remain.
Compare approachesDownload the independent environment, run the native checks and try a specific extension.
Open the how-to guide