Reduce Alert Noise
Scenario
Your team receives 200+ alerts per week. Many are duplicates, low-priority, or non-actionable. Engineers are drowning in notifications and missing the alerts that actually matter.
How OpsWorker Helps
Unified Visibility
Alerts from AlertManager (Prometheus) and Datadog appear in one timeline in the OpsWorker portal. Grafana Alerting is supported when it sends alerts in AlertManager format; it is not a separate native source. Filter by severity, namespace, and cluster to understand your alert landscape.
Focused Investigation with AlertRules
Per-cluster AlertRules are the main noise control that ships today. They filter incoming alerts by namespace, label, and severity (regex matching), and decide which alerts trigger an investigation:
- Auto-investigate only critical alerts in production namespaces.
- Record everything else for visibility without triggering investigations.
Basic Deduplication
OpsWorker suppresses identical duplicate alerts: when two alerts share the same fingerprint and the same start second, the duplicate is dropped. This is exact-match dedup, not time-window suppression or silencing.
Daily Digest
The daily digest (per-cluster, delivered to Slack at 09:00 UTC, also written to S3 and viewable in the portal) summarizes the last 24 hours with day-over-day (2-day) deltas. Use it to spot which namespaces generate the most alerts and adjust your AlertRules accordingly.
Roadmap: Alert Correlation
Grouping multiple alerts from a single underlying issue into one incident is a planned feature, not available today. Each alert that passes your AlertRules currently spawns its own investigation; there is no incident entity or cross-alert correlation yet.
Outcome
- Focus on what matters: AlertRules scope investigations to actionable alerts only.
- Fewer duplicates: identical alerts (same fingerprint, same start second) are suppressed.
- Data-driven tuning: use the daily digest and portal visibility to refine your AlertRules.
- Reduced fatigue: better signal-to-noise without over-promising correlation that does not exist yet.