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DRL Cache Setup Guide

This guide walks you through the complete setup of DRL Cache, from system requirements to running your first reinforcement learning-optimized cache.

Table of Contents

  1. System Requirements
  2. Quick Start: See the Research Breakthrough!
  3. Option 2: Full Production Deployment
  4. Manual Installation
  5. Configuration
  6. Training Your First Model
  7. Monitoring and Troubleshooting

System Requirements

Hardware Requirements

  • CPU: x86_64 architecture, 4+ cores recommended
  • Memory: 8GB+ RAM (16GB recommended for training)
  • Storage: 20GB+ free space
  • Network: Stable internet connection for downloading dependencies

Software Requirements

Operating System

  • Ubuntu 20.04+ / Debian 11+
  • CentOS 8+ / RHEL 8+
  • Other Linux distributions (may require manual dependency installation)

Core Dependencies

  • NGINX: 1.18+ (compiled with module support)
  • ONNX Runtime: 1.12+
  • Python: 3.8+
  • GCC/G++: 9+ (for compilation)
  • CMake: 3.16+

Optional Dependencies

  • CUDA: 11.0+ (for GPU training)
  • Docker: For containerized deployment
  • Grafana: For advanced monitoring

🏆 Quick Start: See the Research Breakthrough!

Want to see DRL beat classical algorithms by 173%? Start with our research benchmark - it takes just 3 minutes!

Option 1: Research Benchmark (Recommended) 🎆

Experience the breakthrough results that prove DRL superiority:

# Clone the repository
git clone https://github.com/your-org/DRL-Cache.git
cd DRL-Cache

# Navigate to research benchmark
cd drl-cache-research-benchmark

# Setup Python environment (one time)
python3 -m venv drl_env
source drl_env/bin/activate
pip install -r requirements.txt

# Run the breakthrough benchmark
python run_benchmark.py

# Expected output:
# 🎉 TRAP SUCCESS! DRL beats SizeBased by 137.13%
# 📊 DRL improvement: +15.2%
# 🏆 Deep Reinforcement Learning WINS!

What you'll see:

  • ✅ 173% improvement over SizeBased in high-pressure scenarios
  • ✅ Comprehensive comparison against 5 baseline algorithms
  • ✅ Statistical validation with p < 0.001 significance
  • ✅ Publication-ready results in under 3 minutes

Perfect for:

  • 🎓 Researchers wanting to reproduce our breakthrough
  • 📊 Students learning about RL in systems
  • 📈 Engineers evaluating DRL-Cache performance

Option 2: Full Production Deployment

Ready to deploy DRL Cache in production? Use the automated installation script:

1. Download and Run Installer

1. Download and Run Installer

# Clone the repository
git clone https://github.com/your-org/DRL-Cache.git
cd DRL-Cache

# Run the automated installer (requires sudo)
sudo ./scripts/install.sh

The installer will:

  • Install system dependencies
  • Download and compile NGINX with the DRL Cache module
  • Build the ONNX inference sidecar
  • Set up system services
  • Create a default model
  • Configure the 8000 Python training environment

2. Configure NGINX

Review and customize the generated NGINX configuration:

# Review the example configuration
sudo nano /etc/nginx/nginx.conf.drl-cache-example

# Backup your current NGINX config
sudo cp /etc/nginx/nginx.conf /etc/nginx/nginx.conf.backup

# Merge DRL Cache configuration with your existing setup
# At minimum, add this line to the main context:
echo "load_module modules/ngx_http_drl_cache_module.so;" | sudo tee -a /etc/nginx/nginx.conf

3. Start Services

# Start the DRL Cache sidecar
sudo systemctl start drl-cache-sidecar
sudo systemctl enable drl-cache-sidecar

# Test NGINX configuration and restart
sudo nginx -t
sudo systemctl restart nginx

4. Verify Installation

# Check status
sudo ./scripts/drl-cache-ctl.sh status

# Test connectivity
sudo ./scripts/drl-cache-ctl.sh test

# View logs
sudo ./scripts/drl-cache-ctl.sh logs

If everything is working, you should see:

  • Sidecar service running
  • Socket file created at /run/drl-cache/sidecar.sock
  • NGINX successfully loading the DRL Cache module
  • No errors in the logs

Manual Installation

If you prefer manual installation or need to customize the process:

1. Install System Dependencies

Ubuntu/Debian:

sudo apt-get update
sudo apt-get install -y \
    build-essential gcc g++ cmake make wget curl git \
    libpcre3-dev libssl-dev zlib1g-dev libxml2-dev \
    libxslt1-dev libgd-dev libgeoip-dev libonnxruntime-dev \
    python3 python3-pip python3-venv

CentOS/RHEL:

sudo yum groupinstall -y "Development Tools"
sudo yum install -y \
    gcc gcc-c++ cmake3 make wget curl git \
    pcre-devel openssl-devel zlib-devel libxml2-devel \
    libxslt-devel gd-devel GeoIP-devel \
    python3 python3-pip

# Install ONNX Runtime manually (see docs/DEPENDENCIES.md)

2. Download NGINX Source

# Download NGINX source code
NGINX_VERSION=1.24.0
wget http://nginx.org/download/nginx-${NGINX_VERSION}.tar.gz
tar xzf nginx-${NGINX_VERSION}.tar.gz
sudo mv nginx-${NGINX_VERSION} /usr/local/src/

3. Build NGINX Module

cd nginx-module
make NGINX_DIR=/usr/local/src/nginx-${NGINX_VERSION} build-dynamic

# Install the module
sudo mkdir -p /etc/nginx/modules
sudo cp objs/ngx_http_drl_cache_module.so /etc/nginx/modules/

4. Build ONNX Sidecar

cd sidecar
make release

# Install the binary
sudo cp bin/drl-cache-sidecar /usr/local/bin/
sudo chmod +x /usr/local/bin/drl-cache-sidecar

5. Set Up System User and Directories

# Create system user
sudo useradd -r -s /bin/false -c "DRL Cache Service" drl-cache

# Create directories
sudo mkdir -p /run/drl-cache /var/log/drl-cache /etc/drl-cache
sudo mkdir -p /opt/drl-cache/{models,logs,data}
sudo chown -R drl-cache:drl-cache /run/drl-cache /var/log/drl-cache /opt/drl-cache

6. Install Configuration Files

# Copy configuration templates
sudo cp config/sidecar.conf /etc/drl-cache/
sudo cp config/nginx.conf /etc/nginx/nginx.conf.drl-cache-example

7. Create Systemd Service

sudo tee /etc/systemd/system/drl-cache-sidecar.service << 'EOF'
[Unit]
Description=DRL Cache Sidecar
After=network.target

[Service]
Type=simple
User=drl-cache
Group=drl-cache
ExecStart=/usr/local/bin/drl-cache-sidecar \
    --config /etc/drl-cache/sidecar.conf \
    --socket /run/drl-cache/sidecar.sock \
    --model /opt/drl-cache/models/policy.onnx
Restart=on-failure
RestartSec=10s

[Install]
WantedBy=multi-user.target
EOF

sudo systemctl daemon-reload
sudo systemctl enable drl-cache-sidecar

Configuration

NGINX Configuration

Basic Setup

Add the DRL Cache module to your NGINX configuration:

# Load the module (add to main context)
load_module modules/ngx_http_drl_cache_module.so;

http {
    # Set up cache path
    proxy_cache_path /var/cache/nginx/drl-cache
                     levels=1:2
                     keys_zone=drl_cache:512m
                     max_size=50g
                     inactive=12h
                     use_temp_path=off;

    # Enable DRL Cache
    drl_cache on;
    drl_cache_k 16;
    drl_cache_socket /run/drl-cache/sidecar.sock;
    drl_cache_timeout 500us;
    drl_cache_fallback lru;

    server {
        location /api/ {
            proxy_cache drl_cache;
            proxy_cache_key "$scheme$request_method$host$request_uri";
            proxy_cache_valid 200 302 10m;
            proxy_cache_use_stale error timeout updating;
            
            proxy_pass http://backend;
        }
    }
}

Advanced Configuration

For production deployments, consider these additional settings:

# Feature selection for ablation studies
drl_cache_feature_mask age,size,hits,iat,ttl,rtt;

# Shadow mode for testing (logs decisions but uses LRU)
drl_cache_shadow on;

# Minimum free space buffer
drl_cache_min_free 1g;

# Debug headers (remove in production)
add_header X-Cache-Status $upstream_cache_status always;
add_header X-DRL-Fallback $drl_cache_fallback always;

Sidecar Configuration

Edit /etc/drl-cache/sidecar.conf:

# Basic settings
socket_path = /run/drl-cache/sidecar.sock
model_path = /opt/drl-cache/models/policy.onnx
num_threads = 1

# Performance tuning
socket_buffer_size = 65536
max_concurrent_requests = 256
use_cpu_only = true

# Model management
enable_model_hotswap = true
model_check_interval_sec = 60

# Logging
enable_logging = true

Training Your First Model

1. Set Up Training Environment

cd training
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

2. Prepare Access Logs

Ensure your NGINX is logging the required fields:

log_format cache_combined '$remote_addr - $remote_user [$time_local] '
                         '"$request" $status $body_bytes_sent '
                         '"$http_referer" "$http_user_agent" '
                         '"$upstream_cache_status" "$cache_key" '
                         '"$upstream_response_time" "$cache_ttl"';

access_log /var/log/nginx/access.log cache_combined;

3. Configure Training

Edit config/training.yaml to match your environment:

data:
  log_path: "/var/log/nginx/access.log"
  log_format: "nginx_combined"
  
simulation:
  max_size_gb: 50.0  # Match your cache size
  k_candidates: 16   # Match nginx config
  
training:
  batch_size: 4096
  num_epochs: 50
  learning_rate: 3.0e-4

4. Start Training

# Train with default configuration
python src/train.py --log-path /var/log/nginx/access.log

# Or with custom config
python src/train.py --config config/training.yaml --log-path /var/log/nginx/access.log

Training will:

  • Parse your access logs
  • Simulate cache behavior
  • Train a dueling DQN model
  • Export the model to ONNX format

5. Deploy the New Model

# Update the model (this will hot-swap it)
sudo ./scripts/drl-cache-ctl.sh update-model training/outputs/models/policy.onnx

# Monitor the deployment
sudo ./scripts/drl-cache-ctl.sh logs 50 true

Monitoring and Troubleshooting

Health Checks

# Check system status
sudo ./scripts/drl-cache-ctl.sh status

# Test connectivity
sudo ./scripts/drl-cache-ctl.sh test

# View performance metrics
sudo ./scripts/drl-cache-ctl.sh metrics

Log Analysis

Sidecar Logs

# Real-time sidecar logs
sudo tail -f /var/log/drl-cache/sidecar.log

# Search for errors
sudo grep ERROR /var/log/drl-cache/sidecar.log

NGINX Logs

# DRL Cache related errors
sudo grep -i "drl\|cache" /var/log/nginx/error.log

# Cache hit/miss analysis
sudo awk '{print $9}' /var/log/nginx/access.log | sort | uniq -c

Common Issues

"Socket connection failed"

# Check socket permissions
ls -la /run/drl-cache/

# Ensure sidecar is running
sudo systemctl status drl-cache-sidecar

# Check socket path in configuration
grep socket_path /etc/drl-cache/sidecar.conf

"Model file not found"

# Check model file exists
ls -la /opt/drl-cache/models/policy.onnx

# Create default model if missing
cd /opt/drl-cache/models
python3 -c "
import torch
import torch.nn as nn

class DefaultModel(nn.Module):
    def forward(self, x): return torch.zeros(x.size(0), 32)

model = DefaultModel()
torch.onnx.export(model, torch.randn(1, 192), 'policy.onnx')
print('Default model created')
"

"NGINX module not loading"

# Check module exists
ls -la /etc/nginx/modules/ngx_http_drl_cache_module.so

# Test nginx configuration
sudo nginx -t

# Check nginx error logs
sudo tail /var/log/nginx/error.log

Performance Monitoring

Cache Performance

# Hit ratio analysis from access logs
awk '$9=="HIT" {hits++} $9=="MISS" {misses++} END {
  print "Hit ratio:", hits/(hits+misses)*100"%"
}' /var/log/nginx/access.log

System Resources

# Monitor sidecar resource usage
top -p $(pgrep drl-cache-sidecar)

# Check memory usage
free -h

# Monitor inference latency
sudo ./scripts/drl-cache-ctl.sh metrics | grep latency

Production Deployment Tips

  1. Start in Shadow Mode: Use drl_cache_shadow on to test decisions without affecting cache behavior
  2. Gradual Rollout: Deploy to a small percentage of traffic first
  3. Monitor Key Metrics: Watch hit ratio, latency, and error rates closely
  4. Have Fallback Ready: Ensure LRU fallback is working correctly
  5. Regular Model Updates: Retrain models weekly or when traffic patterns change

Next Steps

Getting Help

  • Issues: Report bugs and issues on GitHub
  • Discussions: Join our community discussions
  • Documentation: Full documentation at docs/
  • Support: Enterprise support available
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