Raxol.Performance.AdaptiveOptimizer (Raxol v2.0.1)

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Adaptive performance optimizer that responds to real-world usage patterns.

This module implements production-ready optimizations based on telemetry data:

  • Dynamic resource allocation based on workload patterns
  • Adaptive cache tuning with machine learning principles
  • Performance threshold adjustment based on historical data
  • Predictive scaling for high-load scenarios
  • Memory pressure management with intelligent eviction

Summary

Functions

Returns a specification to start this module under a supervisor.

Configure adaptive thresholds for specific metrics.

Get current optimization state and recommendations.

Manually trigger adaptive optimization based on current patterns.

Functions

child_spec(init_arg)

Returns a specification to start this module under a supervisor.

See Supervisor.

configure_thresholds(thresholds)

Configure adaptive thresholds for specific metrics.

get_optimization_status()

Get current optimization state and recommendations.

handle_manager_cast(msg, state)

Callback implementation for Raxol.Core.Behaviours.BaseManager.handle_manager_cast/2.

optimize_now()

Manually trigger adaptive optimization based on current patterns.

start_link(init_opts \\ [])