WATCHLOG PRODUCT · AI
Start from a hypothesis,
not a blank screen.
AI-powered root cause scoring, cross-signal correlation, and natural language incident summaries — trained on your own observability data.
THE PROBLEM
Incidents start with a blank screen
and a firing alert.
An alert fires. You have metrics, logs, traces, and events — but no guidance on where to look first. Every engineer on the call starts from scratch. Correlation that should take 2 minutes takes 40. AI Analysis changes the starting point.
Cross-signal correlation is manual
Connecting a metric spike to a log pattern to a recent deploy requires someone who knows the entire system.
Root cause investigation takes too long
The first 30 minutes of an incident is often spent asking "which team owns this?" and "what changed recently?"
Institutional knowledge is a bottleneck
Senior engineers triage faster because they know the system. AI Analysis distributes that knowledge.
WHAT'S MONITORED
Everything AI Incident Analysis captures.
Real signals collected by the Watchlog Agent — available in your dashboard within 60 seconds of enabling.
Root cause scoring
Ranked list of likely causes with confidence percentage, affected services, and supporting evidence.
Cross-signal correlation
AI connects metric anomalies, log patterns, trace errors, and events that occurred in the same blast radius.
Natural language summaries
Human-readable incident report: what happened, what was affected, for how long, and what changed.
Fix suggestions
Ranked remediation actions with confidence scores and links to relevant runbooks.
Similar incident history
Surfaces past incidents that match the current pattern — so you start with the fix that already worked.
Blast radius mapping
Services, hosts, and users affected by the incident — automatically identified from signal correlation.
LIVE VIEW
AI root cause — evidence ranked.
Watchlog AI surfaces the most likely root cause within seconds of incident detection.
Elevated error rate on /api/checkout — 3.8× above baseline
Root Cause Analysis
Suggested Fix
Increase max_connections to 200 and enable PgBouncer pooling.
Deploy [email protected] from the runbooks library.
CAPABILITIES
What AI Incident Analysis gives you.
Confidence-ranked root causes
Every hypothesis ranked by supporting evidence — not a guess, a scored analysis.
Correlated evidence timeline
Visual timeline showing when each contributing signal changed relative to the incident.
Plain-language incident report
AI generates a briefing readable by any engineer — not just the person who built the service.
Automated fix suggestions
Ranked remediation steps based on what has worked for similar past incidents.
Historical incident matching
Find past incidents with matching signal patterns — copy the fix that already worked.
Blast radius estimation
AI maps which services, hosts, databases, and users are in the impact zone.
USE CASES
How engineering teams use AI Incident Analysis.
Database saturation incident
AI correlates: connection pool hit 200, query latency 10×, recent deploy changed ORM config, match to past incident #3820. MTTR: 8 min.
Memory leak investigation
Heap usage climbs over 4 hours. AI surfaces: deploy v3.2.0, specific service, missing garbage collection call. Engineers have a hypothesis before they even look at a trace.
Junior engineer incident response
First on-call shifts are terrifying. AI Analysis gives any engineer a starting point — and reduces escalations to senior staff.
Post-incident retrospective
AI incident report auto-generated and ready for the post-mortem. Timeline, root cause, impact scope, and resolution — in plain language.
PLATFORM FIT
AI Incident Analysis inside the Watchlog platform.
AI Analysis consumes signals from every Watchlog product — infrastructure metrics, logs, APM traces, RUM sessions, and Custom Events — to produce correlated root cause analysis.
QUICK START
Start AI Incident Analysis in under 2 minutes.
No YAML. No complex configuration. The Watchlog Agent handles discovery automatically.
Install the Agent
One curl command on your host. The Watchlog Agent starts immediately.
sudo apiKey="$WATCHLOG_API_KEY" server="$WATCHLOG_SERVER" MEMORY="300M" bash -c "$(curl -L https://watchlog.io/ubuntu/watchlog-script.sh)Enable AI Incident Analysis
AI Analysis activates automatically when Watchlog detects an incident. No additional setup required beyond enabling your chosen monitoring products.
Data appears in 60s
Root cause analysis appears within minutes of an incident being detected. It improves as Watchlog learns your systems baseline behavior.
GET STARTED
Start monitoring with AI Incident Analysis.
Root cause hypothesis in minutes. Reduce MTTR from hours to single-digit minutes.
Questions? Talk to us → [email protected]