5.4 Performance Optimisation - JoshuaJewell/IDApTIK GitHub Wiki
⚡ Performance Optimization – IDApTIK
🎯 Goal: Maximize efficiency without sacrificing adaptability
We focus on execution stability, rollback responsiveness, and minimal latency impact.
🔬 Key Optimization Areas
🔥 Execution Pipeline Refinement → Fine-tuning JIT behavior, memory strategy, and event processing
🔥 Rollback Enforcement Profiling → Adaptive load balancing based on fault severity and execution dependencies
🔥 Telemetry Hook Integration → Structured tracking without performance penalties
🔥 WASM, GraphQL, Redis Optimization → Streamlining multiplayer interactions for smooth data handling
🔄 Continuous Performance Testing
🚀 Benchmarking rollback efficiency across parallel execution paths
🚀 Profiling execution latency and resource utilization
🚀 Refining anomaly detection strategies for seamless recovery