Harness Continuous Delivery: ML-Backed Deployment Verification

Harness automates canary & progressive delivery with Continuous Verification, using ML to analyze post-deploy telemetry and trigger safe rollbacks.

Core Features

• Anomaly Detection: Metrics/logs variance vs. baseline after deploy.
• Automated Rollback: Policy-based reversal on verified regressions.
• Cost Optimization AI: Identifies idle / over-provisioned resources.
• Pipeline Orchestration: Multi-env, canary, feature flag integration.

Use Cases

• Reducing risk in high-frequency releases.
• Controlling cloud spend via post-deploy usage insights.
• Standardizing safe deployment strategies (blue/green, canary).

Integrations

• Datadog, Prometheus, New Relic, Splunk, CloudWatch metrics.
• Kubernetes, serverless, and traditional VM targets.

Adoption Indicators

• Enterprise case studies citing failed deploy incident reductions.
• Recognized in software delivery automation market analyses.

Best For

• DevOps teams formalizing SLO-aware deployments.
• Organizations maturing from manual verification to ML-driven.

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