MongoDB Replication Lag Incident — Incident Report
May 2, 2026 · Prepared for: [Your Organization]
Severity
P2
Service outage
1h 15min
Peak error rate
—
Users impacted
Finance ops + internal dashboards
Status
Resolved
Context
Incident verdict
Failure chain detected from production logs and cited evidence lines.
Generated from real production signals. Logs, Slack context, and monitoring traces are correlated before RCA and fix guidance.
May 2, 2026 · Prepared for: [Your Organization]
Severity
P2
Service outage
1h 15min
Peak error rate
—
Users impacted
Finance ops + internal dashboards
Status
Resolved
On November 6, 2025, MongoDB replica set rs-prod showed secondary replication lag peaking at 740 seconds. Applications using readPreference secondaryPreferred read stale pricing documents, causing inconsistent quotes. Root cause: foreground index build on pricing.skus (collection scan ~420M docs) monopolized primary I/O and oplog entries replicated slower than primary insert rate during rebuild.
mongo-sec-bPrimary: Index build mode incompatible with replica load — foreground build + heavy write load → oplog apply bottleneck.
Contributing: No maxTimeMS guard on analytics queries competing for IOPS.
P2, MTTR 1h 15m, financial data staleness risk mitigated by forcing primary reads.
{"t":{"$date":"2025-11-06T15:03:01Z"},"s":"I","c":"REPL","id":601252,"ctx":"replwriter","msg":"applied op delay","attr":{"delaySecs":612}}
2025-11-06T15:04:22.011Z W STORAGE Creating index idx_sku_hash - foreground build may block writes on large collections
Treat index builds as cross-region replication events, not local DDL.
This page is a real-format example so teams can evaluate the full flow before login: input signals, evidence-backed RCA, Ask ProdRescue follow-up, and optional GitHub actions by plan.
1) Inputs & context
All plans can paste logs directly. With Slack connected (Pro / Team), pull threads or channels from war rooms and keep that context in one evidence-backed report.
2) Evidence-backed RCA
Timeline, root cause, impact, and action items are generated with citations tied to real log lines (e.g. [1], [6], [8]) so teams can verify every claim.
3) Ask ProdRescue
On report pages, users can ask follow-up questions like "why this happened", "show the evidence", or "suggest a fix" and get incident-context answers grounded in report data.
4) GitHub actions (plan-aware)
Team: connect repo, import commits, run manual deploy analysis, add webhook automation, and submit suggested fixes for review on GitHub (no auto-merge).
Get answers. Find the fix.
Suggested Fix (preview)
- payment.Amount
+ if payment == nil {
+ return ErrInvalidPayment
+ }
+ amount := payment.AmountChange preview
fix(incident-mongodb-): apply suggested remediation
Team plan can publish the change for review on GitHub. No auto-merge.
Had a similar incident?
Paste your logs in the workspace — ProdRescue cites every claim to an evidence line. First analysis free; no credit card required.
Paste your logs