From deployment context
to verified recovery.
RKH is developing an AI DevOps Engineer that helps software teams connect deployment changes, infrastructure signals, and application behavior to investigate incidents, prepare remediation plans, and verify recovery.
Human approval for high-impact actions.
INC-1048payments-serviceDEP-2841- 10:14Error rate increased from 0.3% to 12.8%.
- 10:15A deployment (DEP-2841) was detected.
- 10:16A configuration difference was identified.
- 10:18Database connection exhaustion became a leading hypothesis.
DATABASE_POOL_SIZE changed from 50 to 5.
- ›Error increase occurred shortly after deployment.
- ›Configuration change is visible in the illustrative deployment diff.
- ›Database connection exhaustion is a plausible explanation.
- ›Additional evidence is required before treating the root cause as confirmed.
Restore the previous configuration and validate the service.
Sample data. No live telemetry.
Your dashboards show what happened.
Your team still needs to find out why.
Disconnected signals
Slow investigations
Fragile recovery workflows
From first signal to verified recovery.
The product is designed to connect incident detection, operational evidence, investigation, controlled remediation, and post-action verification.
Plan
Approval pendingDraft a specific corrective change, its expected impact, preconditions and rollback path, ready for human review.
Understand every change that reaches production.
Connect release context with service health to help engineers investigate risky changes before small problems become larger incidents.
- Service
- payments-service
- Environment
- Production
- Commit
- 3f8a9c2
- Change
- Update payment DB config
Possible contributing factors
- Configuration changesPresent
- Database migrationsNone found
- Dependency changesNone found
- Critical service exposureElevated
- Health signals after deploymentPresent
Go from an alert to an evidence-backed explanation.
Help engineers understand which changes correlate with a failure, which hypotheses are supported by available evidence, and what to investigate next.
INC-1048CriticalCheckout error spike
- Environment
- Production
- Affected service
- payments-service
- Customer impact
- Potential payment failures
- Status
- Evidence review complete — illustrative
- 10:14
Error rate increased from 0.3% to 12.8%.
- 10:15
A deployment (DEP-2841) was detected.
- 10:16
A configuration difference was identified.
- 10:18
Database connection exhaustion became a leading hypothesis.
Checkout error rate on payments-service rose from 0.3% to 12.8% at 10:14. Database client errors report connection acquisition timeouts.
Diagnose the issue. Prepare the fix.
Keep production under control.
The product is designed to prepare corrective actions with supporting evidence, expose potential impact, and respect the approval policies your team defines.
Proposed change
Expected impact
Preconditions
Rollback
Don't stop at the fix. Check that it worked.
After an action, compare health checks and key signals against the pre-incident baseline, and state plainly whether the evidence supports recovery.
Built for environments where mistakes are expensive.
Security controls are part of the product design. RKH does not claim any certifications at this stage.
Least-privilege access
Human approval
Audit trail
Credential handling
Designed to connect to the tools you already run.
All integrations below are planned. None are live yet.
From deployment context to verified recovery.
Walk through a sample incident in the interactive demo, or request a guided session with the RKH team.