AI that finds the deploy
that caused the incident.
Upload deployment logs, incident reports or CI/CD pipeline data. OpsOracle AI scores your DORA metrics, correlates deployments to incidents, flags your highest-risk services — and tells your team exactly what to fix. In under 30 seconds.
DevOps AI Capabilities
Built for SREs and platform engineers
Not a generic AI. Every engine is calibrated on DevOps signals — DORA benchmarks, deploy-to-incident patterns, rollback frequencies.
DORA Metrics Scoring
Score your deployment data against DORA Elite/High/Medium/Low benchmarks. AI flags which services are dragging down deployment frequency, change failure rate, MTTR and lead time.
Deploy-to-Incident Correlation
Detect which deployments caused incidents by correlating deploy timestamps with incident start times per service. AI names the exact release that triggered each P1 or P2.
Change Failure Rate Analysis
Calculate per-service change failure rate from your deploy logs. Identify the top 2–3 high-risk services responsible for most rollbacks so you know where to focus stabilization effort.
MTTR Trend Detection
Track mean time to recovery trends across incidents. AI flags when MTTR is worsening for a service and correlates it with team on-call patterns, deploy volume or infrastructure changes.
Pipeline Health Analysis
Parse CI/CD pipeline data to surface flaky test patterns, slow build stages and recurring failure modes. AI identifies which pipeline steps are blocking deployments most often.
Deployment Risk Forecasting
Score the risk of each service before it deploys based on recent failure history, change volume and incident correlation. AI recommends canary, full rollout, or hold.
Real Pain → AI Solves It
Your team faces these every week.
OpsOracle names them and fixes them.
Actual AI output from real DevOps data. Upload your report and get this analysis in under 30 seconds.
The Pain
Friday deploy went out. By Monday morning: 3 P1s, 2 rollbacks, on-call engineer missed the whole weekend.
Raw data signal
payment-service FAILED 25min | Rollback: YES | INC-004 P1 Payment down | MTTR: 105min | deploy→incident gap: 12min
OpsOracle AI Output
payment-service has failed 2 of its last 3 production deploys — both causing P1 incidents within 15 minutes. MTTR averages 105 min vs 60 min DORA Elite target. Change failure rate: 50% (DORA Elite is <15%).
[THIS WEEK] Action
Freeze payment-service feature deploys until post-incident review is complete. Enforce staging → canary → production gate with 30-minute soak time before full rollout.
Expected impact: Prevent next P1 incident: estimated $4,200 revenue downtime cost + on-call burden eliminated
The Pain
We don't know our change failure rate. Half the team thinks deploys are fine. The other half dreads Fridays.
Raw data signal
Deploys: 8 total | FAILED: 4 (50%) | Rollbacks: 4 | P1 caused: 3 | P2 caused: 1 | Avg MTTR: 124min
OpsOracle AI Output
4 of 8 production deployments failed this week — 50% change failure rate. auth-service, api-gateway, notification-service, and payment-service all had failures. DORA Elite benchmark: <15%. You are 3× over.
[THIS WEEK] Action
SRE lead to instrument deployment success/failure tracking per service in your observability stack this week. Target: per-service change failure rate visible in dashboard within 5 days.
Expected impact: Visibility enables you to isolate the 1–2 high-risk services driving 80% of failures
The Pain
api-gateway went down for 100 minutes. Root cause analysis took 3 days. By then, 2 more deploys had gone out.
Raw data signal
api-gateway deploy FAILED | INC-002 P1 502 errors 100pct traffic | MTTR: 100min | Root cause: deploy regression
OpsOracle AI Output
api-gateway P1 had 100-minute MTTR but 3-day RCA cycle — meaning the signal was visible in deploy logs immediately but not acted on. Two more api-gateway deploys went out before root cause was documented.
[THIS WEEK] Action
Platform team to wire deploy failure → automatic 15-min hold on subsequent same-service deploys. Add pre-deploy check: last deploy status must be SUCCESS before new release proceeds.
Expected impact: Prevent cascading failures: next api-gateway P1 caught in 5 min instead of 100 min
14-day Pro trial · No credit card · Results in 30 seconds
How DevOps teams use OpsOracle AI
Upload deploy logs or pipeline data
Export your CI/CD pipeline history, deployment events, or incident log as CSV. OpsOracle reads any format — no schema required.
AI scores DORA metrics and risk
Change failure rate, MTTR, deployment frequency and lead time scored per service against DORA benchmarks. Deploy-to-incident correlation mapped automatically.
Act before the next Friday deploy
Three specific actions — THIS WEEK / THIS MONTH / NEXT QUARTER — each naming the service, the change, and the dollar cost of fixing it.
Stop doing postmortems. Start preventing incidents.
Upload your deployment log now — OpsOracle AI returns DORA scores, deploy-to-incident correlation and change failure analysis in seconds.
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