Incidentary

When an alert fires across multiple services, the room splits before the investigation begins. Engineers open different dashboards, come up with different theories, and the first chunk of every incident is spent converging on a shared story instead of fixing anything. Incidentary removes that alignment phase. How it works: an open-source SDK records events continuously across your services, before any alert fires. When one arrives — via PagerDuty, a webhook, or a Slack command — Incidentary assembles the causal chain from data already captured in that window. By the time the war room opens, the artifact is ready. Everyone reads the same thing. The artifact is deterministic. Each step names its predecessor explicitly. Every event was recorded at runtime by the SDK. No inference, no probabilistic correlation, no AI slop. If a service wasn't instrumented, the gap appears honestly in the chain, labelled and explained. A few things worth knowing: - Installing the SDK on one service immediately surfaces your ghost services — dependencies that aren't instrumented — ranked by call volume. - For Kubernetes, there's a cluster operator (one Helm install, read-only ClusterRole) that maps pod crashes, OOMs, evictions, and deploy rollouts into the same causal chain as application traces. - It's not a replacement for Datadog or Grafana. It's a precursor. You read Incidentary first, then go to your existing tools knowing what you're looking for. - SDKs for Node.js, Python, Go, and .NET. OTLP ingest supported if you're on OpenTelemetry. Free plan: 200K causal events a month. Demo without signup at https://incidentary.com/demo.