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Quickly Locate Root Cause of Business Error Rate Anomalies

UCIndex: UC02

Challenge: Error Alerts Are Noisy, Difficult to Quickly Locate Root Cause​

In distributed systems, error rate spikes are a common challenge.

  • Frequent alerts: When a service's error rate suddenly increases, it often triggers numerous alerts with high noise levels.
  • Cumbersome process, low efficiency: Engineers often have to search through massive logs for exception stack traces, or repeatedly compare call traces to gradually narrow down the scope, which is time-consuming and inefficient.

Solution: Integrated Diagnosis of Multi-Source Data​

Syncause can automatically query connected logs and call traces based on environmental information when request error rates occur, quickly analyze root causes, and provide detailed reports and evidence, such as root causes:

  • Application layer exceptions → certain code segments frequently throwing errors
  • Resource bottlenecks → database connection pool exhaustion causing request failures
  • Dependency anomalies → downstream service timeouts/500 errors propagating
  • Network issues → TCP retransmissions or DNS resolution failures

You only need to ask one question:

Why did the error rate of the checkout service suddenly increase?

Syncause will automatically combine kernel-level data, logs, and call traces to provide clear analysis in minutes.

Effects and Value​

  • Minute-level error source identification — no more burying your head in logs or staring at dashboards
  • Reduced alert noise — jumping directly from "there are errors" to "why errors occurred"
  • Natural language interaction — one question to get the complete causal chain
  • Cross-layer visibility — application, resources, dependencies, network, full-link transparency

Usage Steps​

  1. Open Syncause and start communicating with the SRE Agent
  2. Ask directly in natural language:
Why did the checkout service error rate suddenly increase?
  1. Syncause automatically performs analysis:
    • Collects eBPF kernel data, checks call traces and logs
    • Identifies error patterns (application exceptions, dependency failures, network errors, etc.)
    • Provides root causes and evidence chains

(Screenshot example)

  1. Get final conclusions and visual evidence:
    • Charts show error rate curves highly correlated with database connection pool wait time curves
    • Log fragments display typical "connection timeout" error stack traces

(Screenshot example)

Want to experience it right away? Enter our online sandbox, manually trigger a failure, and see how Syncause helps you pinpoint the root cause in minutes.