Use Case: Alert Suppression

From 1,000 Alerts to
1 Root Cause.

Stop the context-switching madness. Logsmith.ai correlates telemetry across your stack to silence the noise and surface actionable insights in seconds.

The Chaos

124 UNREAD ALERTS
CRITICAL: HTTP 500 Spike02:41:05 AM

Internal Server Error on endpoint /api/v1/checkout - Pod: worker-a21

CRITICAL: HTTP 500 Spike02:41:07 AM

Internal Server Error on endpoint /api/v1/checkout - Pod: worker-b44

WARNING: Latency Spike02:41:10 AM

Response time > 2000ms on US-EAST-1 cluster

CRITICAL: Pod OOMKilled02:41:12 AM

Memory limit reached for deployment: checkout-service

CRITICAL: HTTP 500 Spike02:41:15 AM

Logsmith Calm

1 ACTIONABLE RCA
Root Cause Identified
Generated in 1.2s

Postgres Connection Pool Exhaustion

124 alerts suppressed. All HTTP 500 errors and OOM events correlate to a connection leak in the checkout-service database driver.

Impacted ServicePayment Gateway
ResolutionScale Pool Size
+5
SRE Team notified via Slack

Engineering Health Metrics

Turning chaos into clarity isn't just about speed—it's about people.

92%
MTTR REDUCTION
100:1
NOISE RATIO
Deduplication efficiency
0%
FALSE POSITIVES
ML-verified causality
-85%
ENGINEER BURNOUT
Based on on-call pages

How the Correlation Engine works.

  • 1

    Ingestion & Tokenization

    Stream logs, metrics, and traces from CloudWatch, Datadog, or OpenTelemetry.

  • 2

    Causal Correlation

    Our LLM-trained model identifies dependencies across microservices in real-time.

  • 3

    Actionable Synthesis

    Instead of raw logs, we output a human-readable RCA with a suggested fix.

# Logsmith Engine Correlating...
[DETECT] 14:02:11 Latency spike on Auth Service
[DETECT] 14:02:12 Database connection timeout
[CORRELATE] Mapping upstream trace 0x3f2...
[SUCCESS] Pattern identified: Resource Contention
RCA Summary:
"Payment-service-v2 is leaking memory leading to garbage collection pauses that block DB connections."

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