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Error rate spike: +340%
Correlated with deployment v2.8.1
NullReferenceException
UserService.cs:142 — first seen 3m ago
MR #847 created on GitLab
Null check added, CI passing
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When a monitor or heartbeat is linked to telemetry and error tracking sources, Mihari correlates signals to identify the root cause automatically. If the error clears or the deployment rolls back, the incident is resolved without human intervention.
- Link monitors and heartbeats to telemetry sources (logs, metrics, traces)
- Connect error tracking to automatically identify the faulty code path
- Correlate deployment events with error spikes to pinpoint the root cause
- Auto-resolve incidents when the root cause is remediated or rolled back
- Reduce mean time to resolution (MTTR) by eliminating manual triage
Linked Sources
Telemetry - Logs & Metrics
api-gateway / production
Error Tracking
api-gateway / Sentry
GitHub Repository
acme/api-gateway
Error spike correlates with deployment v2.8.1 (deployed 14:30 UTC). NullReferenceException in UserService.cs:142 matches the HTTP 503 pattern from telemetry logs.
acme/api-gateway
main
acme/frontend-app
main
// UserService.cs:142
- var user = _repo.GetById(id);
- return user.Profile.Name;
+ var user = _repo.GetById(id);
+ if (user?.Profile == null) return null;
+ return user.Profile.Name;
Auto-patch incidents with commits and merge requests
Connect your GitHub, GitLab, or Bitbucket account, then link monitors and sources to a repository. When an incident is detected and the root cause identified, Mihari can automatically create a commit and a merge request to patch the issue.
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Learn from every incident with structured postmortems
After an incident is resolved, Mihari generates a comprehensive, blameless postmortem pre-filled with the timeline, root cause analysis, severity matrix, and action items. Export it or use our template to run your own post-incident review.
- Blameless postmortems auto-generated from the incident timeline and telemetry data
- Severity matrix with customer impact, time to identification, and time to resolution
- Root cause analysis pre-filled using the 5 Whys technique
- Short-term and long-term action items with assignees and deadlines
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Summary
On March 18, 2026 at 14:32 UTC, the API Gateway monitor detected HTTP 503 errors across US East and EU West regions. The incident was automatically correlated with a NullReferenceException in UserService.cs introduced in deployment v2.8.1.
Severity Assessment
Customer Impact
High
Severity
Critical
Time to Identification
2 min
Time to Resolution
23 min
Timeline
Monitor api-gateway-health detected HTTP 503 from US East, EU West
Incident INC-3012 created. Escalation policy "Production Critical" triggered.
Telemetry correlation: error rate +340% since deployment v2.8.1
Error tracking: NullReferenceException in UserService.cs:142
Auto-patch: MR !847 created on acme/api-gateway (null check fix)
MR !847 merged after CI validation and team approval
All regions reporting HTTP 200. Incident auto-resolved.
Root Cause Analysis
Deployment v2.8.1 introduced a code path in UserService.GetProfile() that did not handle null user profiles. The 5 Whys analysis traces the root cause to missing integration tests for the profile lookup flow.
Action Items
The complete incident lifecycle, automated
From the first alert to the final postmortem, every step is connected and intelligent.
Detection
Monitors and heartbeats detect anomalies in real-time across all your services and endpoints.
Correlation
Telemetry logs, metrics, and error tracking data are correlated to identify the root cause automatically.
Resolution
A fix commit and merge request are created on your linked Git repository. CI validates the patch before merge.
Postmortem
A blameless postmortem is generated with the complete timeline, root cause analysis, and actionable improvements.
Incidents resolved faster, insights preserved
Automated incident management reduces MTTR and ensures every outage leads to concrete improvements.
80%
Incidents auto-resolved
<5m
Avg. time to identify
100%
Postmortems documented
3x
Fewer recurring incidents
Frequently asked questions
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