Course Outline
Foundations of AI-Enhanced Release Control
- Understanding feature flags and progressive delivery
- Core concepts of canary testing and staged exposure
- Where AI adds value in release workflows
Machine Learning Techniques for Rollout Decisions
- Baseline modeling of system and user behavior
- Anomaly detection approaches for early warning
- Training data considerations and feedback loops
Designing AI-Driven Feature Flag Strategies
- Dynamic flag rules informed by AI signals
- Exposure thresholds and automated score gates
- Adaptive increase, pause, or rollback logic
AI-Assisted Canary Analysis
- Evaluating canary vs. baseline performance
- Weighting metrics and creating AI-based risk scores
- Triggering automated decision pathways
Integrating AI Models into Release Pipelines
- Embedding AI checks in CI/CD stages
- Connecting feature flag systems to ML engines
- Managing pipelines for hybrid automated/manual workflows
Monitoring and Observability for AI Decision-Making
- Signals required for reliable AI inference
- Collecting performance, crash, and behavioral telemetry
- Closing the loop with continuous learning
Risk Management and Operational Governance
- Ensuring responsible automation in release decisions
- Defining human review conditions and override points
- Auditing AI-driven rollout actions
Scaling AI-Based Rollout Strategies Across Products
- Multi-team governance frameworks
- Reusable ML components and model standardization
- Cross-product telemetry normalization
Summary and Next Steps
Requirements
- An understanding of CI/CD workflows
- Experience with feature flag usage or deployment pipelines
- Familiarity with basic statistical or performance monitoring concepts
Audience
- Product engineers
- DevOps professionals
- Release engineers and technical leads
Delivery Options
Private Group Training
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- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from €4560 online delivery, based on a group of 2 delegates, €1440 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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