AI in Deployment & Release Engineering
Assess how AI enhances deployment safety, risk assessment, and release optimisation.
Sample assessment questions for each level:
- Level -1: “Is AI deliberately excluded from deployment and release processes?”
- Level 0: “Are AI deployment tools used inconsistently across projects or teams?”
- Level 1: “Has the team identified specific deployment challenges AI could address?”
- Level 2: “Are basic AI tools used to analyse deployment logs or flag potential issues?”
- Level 3: “Is deployment risk assessed using AI-based change analysis?”
- Level 4: “Does AI detect deployment failures or anomalies in real-time?”
- Level 5: “Are blue-green or canary deployments controlled through AI-based decision logic?”
Key metrics to track:
- Deployment risk accuracy: Percentage of AI-identified high-risk deployments that experience issues
- Deployment failure reduction: Percentage decrease in failed deployments after AI implementation
- Release rollback frequency: Reduction in rollbacks with AI-assessed deployments
- Automated remediation rate: Percentage of deployment issues automatically resolved by AI
- Deployment frequency: Increase in safe deployment cadence with AI assistance
