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Implement distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks.
Passed 22 of 22 test cases with the skill, and 21 of 22 without it.
1 fixed21 passed either way0 still failing0 broke
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A test case the skill fixed. Same model, same prompt, with and without the skill.
When configuring trace sampling for a high-volume production microservice cluster, what target sampling percentage range is recommended to keep CPU overhead below 1%?
| Checked | Without skill | With skill |
|---|---|---|
| The response recommends a sampling rate between 1% and 10%. | Missed | Passed |
The instructions your model reads when the skill loads.
Implement distributed tracing with Jaeger and Tempo for request flow visibility across microservices.
Track requests across distributed systems to understand latency, dependencies, and failure points.
Trace (Request ID: abc123)
↓
Span (frontend) [100ms]
↓
Span (api-gateway) [80ms]
├→ Span (auth-service) [10ms]
└→ Span (user-service) [60ms]
└→ Span (database) [40ms]
test cases passed, vs 21 / 22 without
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