Performance Optimization Guide

This guide provides comprehensive strategies for optimizing Plugged.in performance, scalability, and resource utilization across different deployment scenarios.

System Requirements

Minimum Requirements

Component	Minimum	Recommended	Enterprise
CPU	2 cores	4 cores	8+ cores
RAM	4 GB	8 GB	16+ GB
Storage	20 GB SSD	50 GB SSD	100+ GB SSD
Network	100 Mbps	1 Gbps	10+ Gbps

Database Requirements

# PostgreSQL Configuration
shared_buffers = 256MB          # 25% of RAM
effective_cache_size = 1GB      # 50% of RAM
work_mem = 4MB                  # Per operation
maintenance_work_mem = 64MB     # For maintenance
wal_buffers = 16MB              # WAL buffer
checkpoint_segments = 32        # Checkpoint frequency

Application Optimization

Memory Management

Node.js Optimization

# Memory Settings
NODE_OPTIONS="--max-old-space-size=4096 --optimize-for-size --enable-gc-interval=30000"

# Garbage Collection
GC_INTERVAL=30000
GC_THRESHOLD=0.8
MEMORY_MAX_BUFFER=1GB
MEMORY_MAX_RSS=1.5GB

Application-Level Caching

# Caching Strategy
CACHE_TYPE=redis
CACHE_TTL=3600
CACHE_MAX_SIZE=100MB
CACHE_REDIS_URL=redis://localhost:6379

# Memory Cache (Fallback)
MEMORY_CACHE_ENABLED=true
MEMORY_CACHE_TTL=300
MEMORY_CACHE_MAX_SIZE=50MB

Database Optimization

Query Optimization

# Query Performance
DB_QUERY_TIMEOUT=30000
DB_CONNECTION_TIMEOUT=5000
DB_STATEMENT_TIMEOUT=60000
DB_SLOW_QUERY_LOG=true
DB_SLOW_QUERY_THRESHOLD=1000

# Connection Pooling
DB_POOL_MIN=2
DB_POOL_MAX=20
DB_POOL_IDLE_TIMEOUT=30000
DB_POOL_ACQUIRE_TIMEOUT=60000

Index Optimization

-- Essential Indexes for Performance
CREATE INDEX CONCURRENTLY idx_servers_profile_uuid ON servers(profile_uuid);
CREATE INDEX CONCURRENTLY idx_documents_profile_uuid ON documents(profile_uuid);
CREATE INDEX CONCURRENTLY idx_documents_created_at ON documents(created_at DESC);
CREATE INDEX CONCURRENTLY idx_collections_profile_uuid ON collections(profile_uuid);
CREATE INDEX CONCURRENTLY idx_notifications_user_id ON notifications(user_id);
CREATE INDEX CONCURRENTLY idx_notifications_unread ON notifications(unread) WHERE unread = true;

-- Composite Indexes for Common Queries
CREATE INDEX CONCURRENTLY idx_servers_profile_transport ON servers(profile_uuid, transport);
CREATE INDEX CONCURRENTLY idx_documents_profile_source ON documents(profile_uuid, source, created_at DESC);

Frontend Optimization

Bundle Optimization

# Build Optimization
BUNDLE_ANALYZER=true
SOURCEMAP=false
MINIFY=true
COMPRESS=true

# Code Splitting
LAZY_LOAD_ROUTES=true
TREE_SHAKING=true
DEAD_CODE_ELIMINATION=true

Runtime Performance

// React Optimization
const MemoizedComponent = React.memo(MyComponent);
const CallbackRef = useCallback(() => {}, []);
const MemoValue = useMemo(() => computeExpensiveValue(a, b), [a, b]);

// Virtual Scrolling for Large Lists
import { FixedSizeList as List } from 'react-window';

Infrastructure Optimization

Docker Optimization

Multi-Stage Builds

# Dockerfile optimization
FROM node:18-alpine AS base
FROM base AS deps
RUN apk add --no-cache libc6-compat
WORKDIR /app
COPY package.json yarn.lock* package-lock.json* pnpm-lock.yaml* ./
RUN npm ci --only=production

FROM base AS builder
WORKDIR /app
COPY --from=deps /app/node_modules ./node_modules
COPY . .
RUN npm run build

FROM base AS runner
WORKDIR /app
RUN addgroup --system --gid 1001 nodejs
RUN adduser --system --uid 1001 nextjs
COPY --from=builder /app/public ./public
COPY --from=builder --chown=nextjs:nodejs /app/.next/standalone ./
COPY --from=builder --chown=nextjs:nodejs /app/.next/static ./.next/static
USER nextjs
EXPOSE 12005
CMD ["node", "server.js"]

Docker Compose Optimization

version: '3.8'
services:
  pluggedin-app:
    image: pluggedin/app:latest
    deploy:
      resources:
        limits:
          cpus: '1.0'
          memory: 2G
        reservations:
          cpus: '0.5'
          memory: 1G
    environment:
      - NODE_OPTIONS=--max-old-space-size=1536
    volumes:
      - ./uploads:/app/uploads:ro
    restart: unless-stopped

  pluggedin-mcp:
    image: pluggedin/mcp:latest
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 1G
    environment:
      - MCP_SERVER_MEMORY=512M
    restart: unless-stopped

Kubernetes Optimization

Resource Management

apiVersion: apps/v1
kind: Deployment
metadata:
  name: pluggedin-app
spec:
  replicas: 3
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 0
  template:
    spec:
      containers:
      - name: pluggedin-app
        resources:
          requests:
            memory: "512Mi"
            cpu: "250m"
          limits:
            memory: "2Gi"
            cpu: "1000m"
        livenessProbe:
          httpGet:
            path: /health
            port: 12005
          initialDelaySeconds: 30
          periodSeconds: 10
          timeoutSeconds: 5
          failureThreshold: 3
        readinessProbe:
          httpGet:
            path: /api/health
            port: 12005
          initialDelaySeconds: 5
          periodSeconds: 5
          timeoutSeconds: 3
          failureThreshold: 3

Horizontal Pod Autoscaling

apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: pluggedin-app-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: pluggedin-app
  minReplicas: 3
  maxReplicas: 20
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70
  - type: Resource
    resource:
      name: memory
      target:
        type: Utilization
        averageUtilization: 80
  behavior:
    scaleDown:
      stabilizationWindowSeconds: 300
      policies:
      - type: Percent
        value: 10
        periodSeconds: 60
    scaleUp:
      stabilizationWindowSeconds: 120
      policies:
      - type: Percent
        value: 50
        periodSeconds: 60

Database Performance

PostgreSQL Tuning

Configuration Optimization

# Memory Settings
shared_buffers = 1GB                    # 25% of system RAM
effective_cache_size = 3GB              # 75% of system RAM
work_mem = 16MB                         # Per operation memory
maintenance_work_mem = 256MB            # For maintenance operations
wal_buffers = 64MB                      # WAL writing buffer

# Checkpoint Settings
checkpoint_segments = 128               # Increase for high write loads
checkpoint_timeout = 15min              # Checkpoint frequency
checkpoint_completion_target = 0.9     # Spread checkpoint I/O

# Query Planning
default_statistics_target = 1000        # More detailed statistics
random_page_cost = 1.5                  # SSD optimization
effective_io_concurrency = 200          # SSD concurrent requests

# Logging
log_min_duration_statement = 1000ms     # Slow query logging
log_checkpoints = on                    # Checkpoint logging
log_connections = on                    # Connection logging
log_disconnections = on                 # Disconnection logging

Regular Maintenance

# Daily Maintenance
vacuum (analyze, verbose) pluggedin_db;

# Weekly Maintenance
reindex concurrently (verbose) pluggedin_db;

# Monthly Maintenance
vacuum full analyze verbose pluggedin_db;

# Monitor long-running queries
SELECT pid, now() - pg_stat_activity.query_start AS duration, query
FROM pg_stat_activity
WHERE (now() - pg_stat_activity.query_start) > interval '5 minutes';

Connection Pooling

PgBouncer Configuration

# /etc/pgbouncer/pgbouncer.ini
[databases]
pluggedin_db = host=localhost port=5432 dbname=pluggedin_db

[pgbouncer]
pool_mode = transaction
listen_port = 6432
listen_addr = *
auth_type = md5
auth_file = /etc/pgbouncer/userlist.txt

# Pool Settings
max_client_conn = 1000
default_pool_size = 25
min_pool_size = 5
reserve_pool_size = 5
reserve_pool_timeout = 5

# Timeouts
server_reset_query = DISCARD ALL
server_check_delay = 30
server_check_query = select 1
server_lifetime = 3600
server_idle_timeout = 600

# Performance
pkt_buf = 4096
max_packet_size = 2147483647

Caching Strategies

Redis Configuration

Performance Tuning

# /etc/redis/redis.conf
# Memory Management
maxmemory 2GB
maxmemory-policy allkeys-lru
maxmemory-samples 5

# Performance
tcp-keepalive 300
timeout 300
tcp-keepalive 60

# Persistence (if needed)
save 900 1
save 300 10
save 60 10000

# Advanced
appendonly yes
appendfsync everysec
no-appendfsync-on-rewrite no
auto-aof-rewrite-percentage 100
auto-aof-rewrite-min-size 64mb

Cache Warming

# Warm up frequently accessed data
redis-cli MGET user:profile:1 user:profile:2 user:profile:3

# Preload popular MCP servers
redis-cli SMEMBERS trending:servers

# Warm up document search index
redis-cli KEYS "doc:search:*" | head -100 | xargs redis-cli MGET

Application-Level Caching

Implementation Strategies

// Cache Manager Implementation
class CacheManager {
  private cache = new Map();
  private maxSize = 1000;
  private ttl = 3600000; // 1 hour

  set(key: string, value: any, ttl?: number) {
    if (this.cache.size >= this.maxSize) {
      this.evictLRU();
    }
    this.cache.set(key, {
      value,
      expiry: Date.now() + (ttl || this.ttl)
    });
  }

  get(key: string) {
    const item = this.cache.get(key);
    if (!item) return null;
    if (Date.now() > item.expiry) {
      this.cache.delete(key);
      return null;
    }
    return item.value;
  }

  private evictLRU() {
    // Remove oldest entry
    const firstKey = this.cache.keys().next().value;
    this.cache.delete(firstKey);
  }
}

Monitoring & Alerting

Key Metrics to Monitor

Application Metrics

# Response Times
curl -w "@curl-format.txt" -o /dev/null -s "https://plugged.in/api/health"

# Concurrent Connections
ss -tuln | grep :12005 | wc -l

# Memory Usage
ps aux | grep pluggedin | grep -v grep | awk '{sum+=$6} END {print sum/1024 "MB"}'

Database Metrics

-- Connection Count
SELECT count(*) FROM pg_stat_activity WHERE datname = 'pluggedin_db';

-- Table Sizes
SELECT schemaname, tablename,
       pg_size_pretty(pg_total_relation_size(schemaname||'.'||tablename)) as size
FROM pg_tables
WHERE schemaname = 'public'
ORDER BY pg_total_relation_size(schemaname||'.'||tablename) DESC;

-- Index Usage
SELECT schemaname, tablename, indexname, idx_scan, idx_tup_read, idx_tup_fetch
FROM pg_stat_user_indexes
ORDER BY idx_scan DESC;

Performance Benchmarks

Load Testing

# Using Apache Bench
ab -n 1000 -c 10 https://plugged.in/api/health

# Using Artillery
artillery quick --count 100 -n 20 https://plugged.in/api/search

# Using k6
k6 run --vus 10 --duration 30s load-test.js

Benchmark Scripts

// load-test.js for k6
import http from 'k6/http';
import { check, sleep } from 'k6';

export let options = {
  stages: [
    { duration: '2m', target: 100 },
    { duration: '5m', target: 100 },
    { duration: '2m', target: 200 },
    { duration: '5m', target: 200 },
    { duration: '2m', target: 0 },
  ],
};

export default function () {
  let response = http.get('https://plugged.in/api/search?q=test');
  check(response, {
    'status is 200': (r) => r.status === 200,
    'response time < 500ms': (r) => r.timings.duration < 500,
  });
  sleep(1);
}

Scalability Strategies

Horizontal Scaling

Load Balancer Configuration

# nginx.conf
upstream pluggedin_app {
    least_conn;
    server app1:12005 max_fails=3 fail_timeout=30s;
    server app2:12005 max_fails=3 fail_timeout=30s;
    server app3:12005 max_fails=3 fail_timeout=30s;
}

server {
    listen 80;
    server_name plugged.in;

    location / {
        proxy_pass http://pluggedin_app;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header X-Forwarded-Proto $scheme;

        # Timeouts
        proxy_connect_timeout 30s;
        proxy_send_timeout 30s;
        proxy_read_timeout 30s;

        # Buffering
        proxy_buffering on;
        proxy_buffer_size 128k;
        proxy_buffers 4 256k;
        proxy_busy_buffers_size 256k;
    }
}

Database Scaling

Read Replica Setup

# docker-compose with read replicas
services:
  db-primary:
    image: postgres:15
    environment:
      - POSTGRES_DB=pluggedin_db
      - POSTGRES_USER=pluggedin
      - POSTGRES_PASSWORD=password
    volumes:
      - postgres_primary:/var/lib/postgresql/data
    command: postgres -c wal_level=replica

  db-replica:
    image: postgres:15
    environment:
      - POSTGRES_DB=pluggedin_db
      - POSTGRES_USER=pluggedin_ro
      - POSTGRES_PASSWORD=password
    volumes:
      - postgres_replica:/var/lib/postgresql/data
    command: postgres -c hot_standby=on
    depends_on:
      - db-primary

Troubleshooting Performance Issues

Common Performance Problems

High Memory Usage

Diagnosis:

# Check process memory
pm2 monit

# Check system memory
free -h

# Check for memory leaks
node -e "setInterval(() => { console.log(process.memoryUsage()) }, 1000)"

Solutions:

# Restart services
pm2 restart all

# Clear caches
redis-cli FLUSHALL

# Check for memory leaks in logs
journalctl -u pluggedin-app -f | grep -i memory

Slow Database Queries

Diagnosis:

-- Find slow queries
SELECT query, calls, total_time, mean_time
FROM pg_stat_statements
ORDER BY mean_time DESC
LIMIT 10;

-- Check table statistics
SELECT schemaname, tablename, n_tup_ins, n_tup_upd, n_tup_del, n_live_tup
FROM pg_stat_user_tables
ORDER BY n_live_tup DESC;

Solutions:

# Update statistics
ANALYZE VERBOSE pluggedin_db;

# Rebuild indexes
REINDEX INDEX CONCURRENTLY idx_servers_profile_uuid;

# Check for missing indexes
pg_stat_user_indexes

High CPU Usage

Diagnosis:

# Check CPU usage
top -p $(pgrep -f pluggedin)

# Check CPU per process
ps aux | grep pluggedin | grep -v grep

# Check system load
uptime

Solutions:

# Enable slow query logging
echo "log_min_duration_statement = 1000" >> postgresql.conf

# Check for expensive operations
EXPLAIN ANALYZE SELECT * FROM documents WHERE profile_uuid = 'uuid' ORDER BY created_at DESC;

Performance Best Practices

Development Phase

Code Optimization

# Use performance monitoring
npm install --save-dev @next/bundle-analyzer

# Enable source maps for debugging
SOURCEMAP=true npm run build

# Use tree shaking
npm run build -- --analyze

Database Design

-- Use appropriate data types
ALTER TABLE users ALTER COLUMN created_at TYPE TIMESTAMP;

-- Add constraints for performance
ALTER TABLE documents ADD CONSTRAINT check_source CHECK (source IN ('upload', 'ai_generated', 'api'));

-- Use partitioning for large tables
CREATE TABLE documents_y2024 PARTITION OF documents FOR VALUES FROM ('2024-01-01') TO ('2025-01-01');

Production Optimization

Resource Allocation

# Set appropriate limits
ulimit -n 65536
ulimit -u 4096

# Monitor resource usage
iotop -p $(pgrep -f pluggedin)

Regular Maintenance

# Daily cleanup
find /app/uploads -type f -mtime +30 -delete

# Weekly optimization
pnpm db:optimize

# Monthly analysis
pnpm performance:analyze

This performance optimization guide provides comprehensive strategies for achieving optimal performance with Plugged.in. For specific performance issues, consult the troubleshooting guide or contact support.

Getting Started

Platform Features

Tutorials

Security

Deployment

Testing

Migration Guides

Troubleshooting

Advanced Configuration

Integration Guides

Performance

​Performance Optimization Guide

​System Requirements

​Minimum Requirements

​Database Requirements

​Application Optimization

​Memory Management

​Node.js Optimization

​Application-Level Caching

​Database Optimization

​Query Optimization

​Index Optimization

​Frontend Optimization

​Bundle Optimization

​Runtime Performance

​Infrastructure Optimization

​Docker Optimization

​Multi-Stage Builds

​Docker Compose Optimization

​Kubernetes Optimization

​Resource Management

​Horizontal Pod Autoscaling

​Database Performance

​PostgreSQL Tuning

​Configuration Optimization

​Regular Maintenance

​Connection Pooling

​PgBouncer Configuration

​Caching Strategies

​Redis Configuration

​Performance Tuning

​Cache Warming

​Application-Level Caching

​Implementation Strategies

​Monitoring & Alerting

​Key Metrics to Monitor

​Application Metrics

​Database Metrics

​Performance Benchmarks

​Load Testing

​Benchmark Scripts

​Scalability Strategies

​Horizontal Scaling

​Load Balancer Configuration

​Database Scaling

​Read Replica Setup

​Troubleshooting Performance Issues

​Common Performance Problems

​High Memory Usage

​Slow Database Queries

​High CPU Usage

​Performance Best Practices

​Development Phase

​Production Optimization

Performance Optimization Guide

System Requirements

Minimum Requirements

Database Requirements

Application Optimization

Memory Management

Node.js Optimization

Application-Level Caching

Database Optimization

Query Optimization

Index Optimization

Frontend Optimization

Bundle Optimization

Runtime Performance

Infrastructure Optimization

Docker Optimization

Multi-Stage Builds

Docker Compose Optimization

Kubernetes Optimization

Resource Management

Horizontal Pod Autoscaling

Database Performance

PostgreSQL Tuning

Configuration Optimization

Regular Maintenance

Connection Pooling

PgBouncer Configuration

Caching Strategies

Redis Configuration

Performance Tuning

Cache Warming

Application-Level Caching

Implementation Strategies

Monitoring & Alerting

Key Metrics to Monitor

Application Metrics

Database Metrics

Performance Benchmarks

Load Testing

Benchmark Scripts

Scalability Strategies

Horizontal Scaling

Load Balancer Configuration

Database Scaling

Read Replica Setup

Troubleshooting Performance Issues

Common Performance Problems

High Memory Usage

Slow Database Queries

High CPU Usage

Performance Best Practices

Development Phase

Production Optimization