Raxol.Performance.PredictiveOptimizer (Raxol v2.0.1)

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Predictive performance optimizer using telemetry data.

Monitors system performance patterns and predictively optimizes:

  • Cache warming based on usage patterns
  • Buffer pre-allocation for anticipated operations
  • Rendering pipeline optimization based on workload
  • Adaptive cache sizing based on memory pressure

Uses machine learning-inspired techniques:

  • Pattern recognition for operation sequences
  • Predictive pre-fetching
  • Adaptive thresholds
  • Workload classification

Summary

Functions

Returns a specification to start this module under a supervisor.

Get optimization recommendations based on current patterns.

Trigger predictive optimization based on current patterns.

Record a telemetry event for analysis.

Functions

child_spec(init_arg)

Returns a specification to start this module under a supervisor.

See Supervisor.

get_recommendations()

Get optimization recommendations based on current patterns.

optimize()

Trigger predictive optimization based on current patterns.

record_event(event_name, measurements, metadata)

Record a telemetry event for analysis.

start_link(init_opts \\ [])