Title: Quiz 13 — Observability at Scale: LangSmith, OpenLLMetry, and MLflow
Course: AIINFRA 301: Production RAG & LLMOps — Observability and Evaluation > Section: Week 13 — Observability at Scale: LangSmith, OpenLLMetry, and MLflow

Q: OpenLLMetry ships its own built-in UI and evaluation dashboard alongside its instrumentation library.
- True
- False
A: False

Q: Which LangSmith 2026 tier requires a custom Enterprise contract to self-host?
- Developer
- Plus
- Enterprise
- All tiers support self-hosting equally
A: Enterprise

Q: What is the free LangSmith Developer tier's base trace limit per month?
Feedback: Sample/expected answer: 5,000 base traces/month

Q: What one line of code enables MLflow autologging for a LangChain/LangGraph application?
- `mlflow.start_run()`
- `mlflow.langchain.autolog()`
- `mlflow.log_trace()`
- `mlflow.enable_tracing()`
A: `mlflow.langchain.autolog()`

Q: At production scale, you should capture the exact same full-verbosity traces for every request as you do in a dev environment.
- True
- False
A: False

Q: Name the two-part install/init pattern used to add OpenLLMetry instrumentation to a Python app.
Feedback: Sample/expected answer: `pip install traceloop-sdk`****, then call ****`Traceloop.init()`

Q: How long are LangSmith's extended (long-retention) traces kept, compared to base traces at 14 days?
- 30 days
- 90 days
- 400 days
- Indefinitely
A: 400 days

Q: Because OpenLLMetry, LangSmith, and MLflow all compete for the same use case, a team should pick exactly one and never combine them.
- True
- False
A: False