Automated Canary Analysis

Stop Bad Deployments Before Users Notice.

Delivery Shield's Deployment Assessment and Risk module analyzes real-time application behavior during canary releases, instantly detecting performance anomalies to orchestrate zero-touch rollbacks.

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Canary: v2.1.4

15m window vs Baseline

SCORE: 42 (FAIL)
CPU Utilization✓ PASS

Baseline

34.2%

Canary

35.1%

P99 Latency ANOMALY

Baseline

124ms

Canary

485ms

Auto-Rollback Triggered

Traffic drained from canary pods.

Replace Hope With Mathematical Certainty

Multi-Source Telemetry

Ingest metrics, logs, and traces from your entire observability stack simultaneously. Normalize data from Datadog, Prometheus, Splunk, and more.

Automated Canary Analysis

Eliminate eyeballing. A statistical engine compares hundreds of performance vectors between canary and baseline deployments over set time windows.

Zero-Touch Rollbacks

When performance risk exceeds your threshold, Delivery Shield automatically signals Argo or Spinnaker to reroute traffic and terminate the canary.

What You Get

Catch Bad Deploys Early

Behavioral anomalies surface during the canary window, before a regression ever reaches your full user base.

Replace Hope With Statistics

A weighted scoring engine compares canary to baseline across hundreds of metrics instead of manual dashboard-watching.

Automatic, Instant Rollback

When a canary fails its score, traffic drains and the release reverts with no human in the loop.

Reduce Alert Noise

Models account for natural traffic spikes and seasonality, so you never roll back a healthy release by mistake.

Works With Your Stack

Native integration with Datadog, Prometheus, New Relic, and more means no new telemetry pipeline to build.

Post-Rollout Validation

Verification continues after 100% rollout, watching for subtle degradations that only appear at full scale.

Stop Pushing Risky Code to Everyone

See how intelligent telemetry assessment safeguards every release.

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