Platform
A drift-aware observability core for modern engineering teams.
Driftdog starts with durable telemetry storage, service-aware querying, threshold evaluation, incident timelines, and deterministic drift events.
Drift detection
Catch behavior changes while they are still explainable.
The first Driftdog engine uses baseline comparison and change correlation before any advanced automation. Every finding explains what moved, how far it moved, and where to inspect next.
Compare current service behavior against recent baselines.
Classify drift severity with deterministic scoring first.
Correlate metric movement with deployment and config-change events.
Link each finding back to metrics, logs, and active incidents.
OpenTelemetry-ready
Bring existing telemetry into a drift-aware workflow.
The core data model is prepared for service-scoped logs, metrics, traces, alerts, incidents, and drift events so teams can adopt Driftdog without abandoning existing telemetry standards.
OpenTelemetry-aligned logs, metrics, and traces
Service, environment, and organization context on every signal
JSONB attributes for flexible telemetry details
FastAPI ingestion paths for phased integration
Request demo
See how drift changes incident response.
Walk through Driftdog with a production-style scenario spanning logs, metrics, alerts, incidents, deployments, and deterministic drift findings.