Expand description
ML-based parameter optimization for chaos scenarios
Uses Bayesian optimization and historical data to recommend optimal chaos parameters that balance effectiveness and system stability.
Structs§
- Expected
Impact - Expected impact of parameter change
- Objective
Weights - Weights for multi-objective optimization
- Optimization
Recommendation - Parameter optimization recommendation
- Optimizer
Config - Optimizer configuration
- Orchestration
Run - Historical orchestration run
- Parameter
Bounds - Parameter bounds
- Parameter
Optimizer - ML-based parameter optimizer
- RunMetrics
- Run metrics
Enums§
- Optimization
Objective - Optimization objective