Incident correlation for platform teams
One incident.
Not three pages.
Infrawatch correlates the p99 spike, the pod OOMKill, and the upstream Helm change into a single incident timeline — before three on-call engineers are paged about the same root cause.
The problem every platform team knows
Your monitoring sees everything. It understands nothing.
Datadog fired. PagerDuty fired. Slack exploded. Three engineers pulled into the same incident from three different alert channels — each investigating a symptom, none seeing the cause. This is not a people problem. It's a signal quality problem.
- payments-cfg ConfigMap drift (T-8m)
- payments-worker OOMKill (T-6m)
- api-gateway p99 spike (T-4m)
How Infrawatch works
Ingest. Correlate. Surface.
Connect Prometheus, Datadog, or CloudWatch metrics alongside Kubernetes event streams and your GitOps pipeline via OTLP. The Helm chart deploys in under 10 minutes — no new instrumentation, no forklift.
The correlation graph links signals that share a topology relationship and fall within a configurable time window — matching service names, namespace boundaries, and deployment fingerprints across your signal streams in real time.
The on-call engineer gets one PagerDuty alert: the correlated incident with its full signal cluster, the config change that preceded it, and the runbook if one is attached. No duplicate pages. No parallel investigation threads.
What's under the hood
The six things platform teams actually need
Topology-aware correlation
Correlation windows respect upstream/downstream service relationships, shared namespaces, and deployment groups — not just time proximity. A cache OOMKill and a dependent API latency spike are linked automatically.
Config change fingerprinting
Every Helm release, Terraform apply, ArgoCD sync, and Kubernetes ConfigMap diff is fingerprinted and indexed against your incident timeline. When the same config pattern precedes multiple incidents, you'll see it.
Multi-source alert deduplication
When Prometheus, Datadog, and Alertmanager all fire for the same underlying condition, Infrawatch collapses them into a single incident card before they hit PagerDuty. Alert fatigue comes from tools that don't understand what they're seeing.
Tail latency correlation
p99 and p999 latency spikes are linked to infrastructure events in the same correlation window — so you have causal context before you open a trace. Chasing a slow p99 with no infra signal attached is a common time sink we eliminate.
Root cause heatmap
Post-incident analytics showing which signal types and config changes most reliably precede root causes across your last 90 days. Finds the 10% of causes behind 60% of your incidents.
OTLP-native ingestion
Infrawatch is built on the OpenTelemetry standard. Bring your existing OTLP exporters on gRPC or HTTP/protobuf — we ingest without re-instrumentation. Your investment in OTel instrumentation is preserved.
What platform teams say
Customer testimonials
We were running 6 separate runbooks for what Infrawatch surfaces as a single correlated incident. The reduction in context-switching alone paid for it in the first week.
Our on-call rotation was burning out on alert noise. Three months after deploying Infrawatch, night-time pages dropped by 60%. The team actually sleeps now.
The config change fingerprinting is what sold us. We'd been chasing a recurring incident for two months. Infrawatch showed us it correlated with a specific Helm chart change every time.
Works with your existing stack
Drop in alongside your existing stack
Infrawatch is a correlation layer, not a replacement. Your Prometheus setup, Grafana dashboards, and PagerDuty rotation stay exactly as-is.
Stop investigating symptoms.
Start finding causes.
Early access for platform teams managing 50+ microservices. Founder-led onboarding. Live the same day.