Memory Leak Detection Technologies Documentation

This directory contains comprehensive documentation for 23 different memory leak detection technologies, each with detailed implementation plans for system-agent integration, production examples, and academic references.

Quick Navigation

🟢 Production-Ready (Low Overhead)

• Memory-Technologies-Production-Ready-Page-Fault-Tracing - <1% overhead, eBPF-based page fault monitoring
• Memory-Technologies-Production-Ready-PSI-Metrics - 0% overhead, Pressure Stall Information monitoring
• Memory-Technologies-Production-Ready-Brk-Mmap-Tracing - <1% overhead, system call tracing
• Memory-Technologies-Production-Ready-Jemalloc-Profiling - ~4% overhead, statistical sampling profiler
• Memory-Technologies-Production-Ready-TCMalloc-Profiling - ~5% overhead, Google's allocator profiler
• Memory-Technologies-Production-Ready-Mimalloc-Profiling - ~2% overhead, Microsoft's lightweight allocator
• Memory-Technologies-Production-Ready-Hardware-PMC - 0% overhead, CPU performance counters

🟡 Production-Limited (Moderate Overhead)

• Memory-Technologies-Production-Limited-SWAT-Statistical - <5% overhead, Microsoft's stale object detection
• Memory-Technologies-Production-Limited-PRECOG-ML - ~1% overhead, machine learning detection
• Memory-Technologies-Production-Limited-BCC-Memleak-Sampled - 10-30% overhead, sampled eBPF tracing
• Memory-Technologies-Production-Limited-Bytehound - ~20% overhead, Rust-based complete tracking
• Memory-Technologies-Production-Limited-Time-Series-Analysis - 0-5% overhead, statistical analysis

🔴 Development-Only (High Overhead)

• Memory-Technologies-Development-Only-Valgrind-Massif - 2000% overhead, comprehensive heap profiling
• Memory-Technologies-Development-Only-Heaptrack - 50-100% overhead, heap memory profiler
• Memory-Technologies-Development-Only-ASan - 200-300% overhead, AddressSanitizer
• Memory-Technologies-Development-Only-LSan - 150-200% overhead, LeakSanitizer
• Memory-Technologies-Development-Only-BCC-Memleak-Full - 30-400% overhead, complete malloc/free tracing

🔬 Research Prototypes

• Memory-Technologies-Research-Prototypes-LeakGuard - 5-10% overhead, zero false positives
• Memory-Technologies-Research-Prototypes-Gencount - 5-15% overhead, age distribution analysis
• Memory-Technologies-Research-Prototypes-Sleigh - 10-20% overhead, stale object detection

☁️ Platform-Specific

• Memory-Technologies-Platform-Specific-Parca - Kubernetes continuous profiling platform
• Memory-Technologies-Platform-Specific-Pixie - Kubernetes-native observability
• Memory-Technologies-Platform-Specific-Pyroscope - Multi-language continuous profiling

Technology Categories

By Detection Method

Direct Allocation Tracking:

• BCC memleak (full and sampled)
• ByteHound
• Valgrind/Massif
• Heaptrack
• ASAN/LSAN

Statistical Profiling:

• jemalloc
• tcmalloc
• mimalloc
• SWAT

Indirect Signals:

• Page fault tracing
• PSI metrics
• Hardware PMCs
• brk/mmap tracing

Pattern Analysis:

• Time series analysis
• Precog ML
• LeakGuard
• GenCount
• Sleigh

By Deployment Model

Always-On Monitoring:

• PSI + Metrics
• Page fault tracing
• Hardware PMCs
• brk/mmap tracing

Triggered Profiling:

• jemalloc/tcmalloc
• BCC memleak (sampled)
• ByteHound

Continuous Profiling Platforms:

• Parca
• Pixie
• Pyroscope

Development/CI Only:

• Valgrind
• ASAN/LSAN
• Heaptrack

Three-Layer Detection Strategy

Based on the research, the optimal approach combines multiple technologies:

Layer 1: Continuous Monitoring (Always On)

• Primary: Memory-Technologies-Production-Ready-PSI-Metrics + Memory-Technologies-Production-Ready-Page-Fault-Tracing
• Overhead: <1%
• Purpose: Early warning and anomaly detection

Layer 2: Triggered Investigation (On Anomaly)

• Primary: Memory-Technologies-Production-Ready-Jemalloc-Profiling or Memory-Technologies-Production-Ready-TCMalloc-Profiling
• Overhead: 4-5%
• Duration: 5-10 minutes
• Purpose: Identify leak sources with stack traces

Layer 3: Deep Analysis (Critical Issues)

• Primary: Memory-Technologies-Production-Limited-Bytehound or Memory-Technologies-Production-Limited-BCC-Memleak-Sampled
• Overhead: 20-30%
• Duration: Brief periods
• Purpose: Complete tracking for root cause analysis

Selection Guide

For Different Scenarios

If you need...	Use this technology	Why
Zero overhead monitoring	Memory-Technologies-Production-Ready-Hardware-PMC or Memory-Technologies-Production-Ready-PSI-Metrics	Hardware-native or kernel tracking
Production profiling	Memory-Technologies-Production-Ready-Jemalloc-Profiling	Best overhead/accuracy trade-off
Kubernetes monitoring	Memory-Technologies-Platform-Specific-Pixie or Memory-Technologies-Platform-Specific-Parca	Native K8s integration
Development debugging	Memory-Technologies-Development-Only-Valgrind-Massif	Most comprehensive
Quick leak check	Memory-Technologies-Production-Ready-Page-Fault-Tracing	Low overhead, good signals
Statistical analysis	Memory-Technologies-Production-Limited-SWAT-Statistical	Proven at Microsoft
Complete tracking	Memory-Technologies-Production-Limited-Bytehound	100% allocation coverage

Performance vs Accuracy Trade-offs

High Accuracy, High Overhead:
  Valgrind > ASAN/LSAN > Heaptrack > ByteHound > BCC full

Balanced (Production-suitable):
  jemalloc ≈ tcmalloc > SWAT > Parca/Pixie > BCC sampled

Low Overhead, Lower Accuracy:
  Hardware PMCs ≈ PSI < Page faults < brk/mmap < Time series

Implementation Status

Status	Count	Technologies
✅ Production Ready	10	PSI, Page faults, jemalloc, tcmalloc, mimalloc, PMCs, SWAT, brk/mmap, Time series, Continuous platforms
⚠️ Limited Production	6	BCC sampled, ByteHound, Precog, Research prototypes
❌ Development Only	7	Valgrind, Heaptrack, ASAN, LSAN, BCC full

Key Findings

1. Page fault tracing is underutilized - Provides excellent signals at <1% overhead
2. Modern allocators are production-ready - jemalloc/tcmalloc's 4-5% overhead is acceptable
3. Hardware PMCs offer zero overhead - But require expertise to interpret
4. Statistical approaches work - SWAT proves <5% overhead is achievable
5. Layered approach is optimal - No single tool solves all cases

References

• Memory-Technologies-Comparison-Matrix - Complete comparison matrix
• Memory-Technologies-Findings-Summary - Research findings summary
• Memory-Technologies-PMC-Research-Papers-Bibliography - Academic papers and references

Contributing

When adding new technologies:

1. Follow the established document template
2. Include production examples where available
3. Provide implementation code for system-agent
4. Add academic references and benchmarks
5. Update this index and the comparison matrix