Enterprise CD platform with ML-based deployment verification (AIDA). Auto-detects performance and quality regressions during canary deployments by comparing metrics against historical baselines, then triggers rollback when anomalies exceed thresholds. Predictive deployment risk scoring analyzes code change characteristics to flag high-risk releases before they ship.
| Tier | Price | Includes |
|---|---|---|
Free SaaS | Free | CD + 2,000 Cloud Credits/month, small teams |
Team | Paid; enterprise AI modules included | — |
Enterprise | Contact sales | — |
Harness CD verifies canary deployments with ML and predicts release risk before deploy.
AIDA reads metric, log, and trace baselines during a canary, detects regressions against historical norms, and triggers automatic rollback when anomalies cross threshold. A separate predictive risk score analyzes the change set itself (file count, test coverage delta, dependency churn) and flags high-risk releases proactively, before any traffic shifts.
Who it's for. Platform teams of 20 to 100 engineers running frequent Kubernetes deployments where a bad ship costs revenue or SLOs. The common case: a payments canary takes 5 percent of traffic, AIDA notices p99 latency drifting 40ms above baseline, and rolls back inside 90 seconds before the SLO is breached.
Tradeoffs. Harness is a large opinionated platform; adopting it means migrating off Argo CD, Spinnaker, or Jenkins to its pipeline model. The AI is locked to Harness's verification engine; you cannot bring your own anomaly detector. Enterprise pricing is a sales conversation. Free SaaS tier is real but limited to small teams.
Compare: Argo Rollouts, Spinnaker, Octopus Deploy, OpsMx ISD
