Page 4 of 8~112 min topic

LLM tracing lab

Validate outputs and schemas

Executable checks prove every span carries trace_id + redacted attrs; prompts sampled ≤ 1% on fixtures — including the known misshape behind TRACE-ORPHAN-441.

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Schema and policy checks

Add executable validation at the trust boundaries of OpenTelemetry traces across retrieve → rerank → generate for support answers. Reject unknown fields where they matter, bound string sizes, and coerce only after auth/signature checks when raw bytes are security-relevant. Invariant under test: every span carries trace_id + redacted attrs; prompts sampled ≤ 1%. A TypeScript type or Python annotation is not runtime validation — pair them with parsers.

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Golden and adversarial fixtures

Automate the fixtures from setup, including a recreation of TRACE-ORPHAN-441. Assert both the visible error and the absence of side effects (no provider call, no queue write, no flag flip). Where metrics matter, assert label enums stay bounded.

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Implementation artifact

assert span.get_span_context().is_valid
assert "user.email" not in span.attributes

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Gate semantics

Document which failures are client mistakes (4xx) versus operator/config mistakes (5xx/503). Oracle still stands: fixture question produces 3 child spans; total latency attributes sum within 5% of root. Validation should make accidental “success with empty body” impossible for on-call engineer debugging a slow groundedness miss.

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Stage depth

Property ideas: shuffled field order, Unicode edges, maximum-length strings, and replayed timestamps. Where money, identity, or citations matter, assertion messages should cite the field name. Do not snapshot entire provider payloads in tests; assert semantically. If validation fails open “to keep the demo working,” you have inverted the lab. Tie at least one CI job to the TRACE-ORPHAN-441 fixture so main cannot regress silently. Re-read every span carries trace_id + redacted attrs; prompts sampled ≤ 1% after each new parser — convenience helpers love to bypass it.

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Field notes for `llm-tracing-lab` / `validation`

Table-drive status codes and error codes so reviewers see coverage at a glance. Include a Unicode normalization case if user text is accepted. Verify that oversized bodies fail before CPU-heavy work. Where digests or versions are pinned, assert mismatch behavior. Keep golden files small enough to read in review. CI should fail on skipped tests that mark the incident fixture as xfail without a ticket link. In this chapter the product is OpenTelemetry traces across retrieve → rerank → generate for support answers, the human stakeholder is on-call engineer debugging a slow groundedness miss, and the incident id you design against is TRACE-ORPHAN-441. Re-state the oracle in your notes — fixture question produces 3 child spans; total latency attributes sum within 5% of root — and keep the invariant visible: every span carries trace_id + redacted attrs; prompts sampled ≤ 1%. Track trace_completeness ≥ 0.99 and p95_end_to_end_ms ≤ 2500 as the scoreboard. Surface under change control: POST /v1/support/answer. If you only have forty minutes, finish the fixture for missing parent context → orphan spans, cannot join retrieve to answer before polishing UI. Promotion language stays ternary: promote, hold, or roll back based on evidence, not hope.

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Before you start

Why this matters

List three fixtures: one golden success, one schema/auth reject, and one regression for TRACE-ORPHAN-441. For each, write the exact assertion (status, code, metric, or citation) that must turn red if broken.

In the wild

See how this idea shows up as a product and a company — then come back to the lesson. Skills transfer across vendors.

Check your understanding

Page assessment

Answer from memory. Completion is saved from this evidence, not from opening the next page.

1. Do parsers run before side effects?
2. Is TRACE-ORPHAN-441 represented as a fixture?
3. Are side-effect absences asserted?

All responses are required.