PipeGen

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Examples ​

Explore real-world use cases and see PipeGen in action across different industries and scenarios.

Quick Examples ​

Basic Pipeline ​

bash
# Create and run a basic analytics pipeline
pipegen init basic-analytics
cd basic-analytics
pipegen deploy
pipegen run --dashboard

Load Testing ​

bash
# Simulate Black Friday traffic
pipegen run --message-rate 100 --duration 10m \
  --traffic-pattern "2m-3m:500%,5m-7m:400%,8m-9m:600%" \
  --dashboard --generate-report

Smart Consumer Examples ​

bash
# Auto-calculate expected messages (recommended)
pipegen run --duration 30s
# Producer sends 2,847 messages → Consumer expects 2,847 messages

# Precise control for testing
pipegen run --expected-messages 1000 --message-rate 200
# Consumer stops immediately after consuming exactly 1,000 messages

# Development with fast cycles
pipegen run --duration 10s --pipeline-timeout 2m
# Producer runs 10s, pipeline has 2m total to complete

# Production simulation with realistic timing
pipegen run --duration 5m --pipeline-timeout 30m --expected-messages 50000
# Long producer run with ample processing time

AI-Generated Pipeline ​

bash
# Let AI create a fraud detection system
pipegen init fraud-system --describe \
  "Monitor credit card transactions, detect suspicious patterns using statistical analysis, and alert on potential fraud within 30 seconds" \
  --domain "fintech"

Industry Use Cases ​

🛍️ E-commerce & Retail ​

Real-Time Product Recommendations

bash
pipegen init product-recommendations --describe \
  "Track user interactions with products, calculate item similarity scores, maintain user preference profiles, and generate personalized recommendations in real-time" \
  --domain "ecommerce"

Inventory Management

bash
pipegen init inventory-alerts --describe \
  "Monitor product inventory levels across warehouses, track sales velocity, predict stockouts, and trigger reorder alerts when inventory falls below safety thresholds" \
  --domain "ecommerce"

Customer Journey Analytics

bash
pipegen init customer-journey --describe \
  "Analyze customer touchpoints across web and mobile, track conversion funnels from awareness to purchase, identify drop-off points, and calculate attribution models" \
  --domain "ecommerce"

💰 Financial Services ​

Fraud Detection System

bash
pipegen init fraud-detection --describe \
  "Analyze payment transactions in real-time, compare against customer spending patterns, detect anomalies using machine learning models, and flag suspicious transactions scoring above 0.85 confidence" \
  --domain "fintech"

High-Frequency Trading

bash
pipegen init hft-signals --describe \
  "Process market data feeds from multiple exchanges, calculate technical indicators like MACD and RSI, identify arbitrage opportunities, and generate trading signals with microsecond latency" \
  --domain "fintech"

Risk Management

bash
pipegen init risk-monitoring --describe \
  "Monitor trading positions in real-time, calculate VaR and portfolio exposure, track market volatility indicators, and trigger risk alerts when limits are exceeded" \
  --domain "fintech"

🏭 Manufacturing & IoT ​

Predictive Maintenance

bash
pipegen init predictive-maintenance --describe \
  "Monitor industrial equipment sensors for temperature, vibration, and pressure, detect anomaly patterns, predict equipment failures using historical data, and schedule maintenance before breakdowns occur" \
  --domain "manufacturing"

Quality Control

bash
pipegen init quality-monitoring --describe \
  "Process real-time production line data, monitor product quality metrics, detect defects using statistical process control, and trigger quality alerts when tolerances are exceeded" \
  --domain "manufacturing"

Supply Chain Optimization

bash
pipegen init supply-chain --describe \
  "Track shipments across global supply chain, monitor delivery performance, predict delays based on weather and traffic data, and optimize routing for cost and time efficiency" \
  --domain "logistics"

🎮 Gaming & Entertainment ​

Player Behavior Analytics

bash
pipegen init player-analytics --describe \
  "Track player actions and progression in real-time, identify engagement patterns, predict player churn, and generate personalized offers to improve retention" \
  --domain "gaming"

Dynamic Game Balancing

bash
pipegen init game-balance --describe \
  "Monitor gameplay metrics like win rates and match duration, analyze player skill distribution, detect balance issues, and recommend game parameter adjustments" \
  --domain "gaming"

Live Tournament Analytics

bash
pipegen init tournament-stats --describe \
  "Process live tournament data including player performance, match statistics, audience engagement, and generate real-time leaderboards and analytics dashboards" \
  --domain "gaming"

🏥 Healthcare & Life Sciences ​

Patient Monitoring

bash
pipegen init patient-monitoring --describe \
  "Process vital signs from patient monitors including heart rate, blood pressure, and oxygen levels, detect critical value changes, and trigger immediate alerts for medical staff" \
  --domain "healthcare"

Drug Discovery Analytics

bash
pipegen init drug-discovery --describe \
  "Analyze molecular compound data from research experiments, identify promising candidates based on efficacy and safety profiles, and track clinical trial progress" \
  --domain "healthcare"

📱 Social Media & Content ​

Content Moderation

bash
pipegen init content-moderation --describe \
  "Analyze user-generated content in real-time, detect harmful or inappropriate material using NLP models, calculate toxicity scores, and flag content for human review" \
  --domain "social"

Trend Detection

bash
pipegen init trend-detection --describe \
  "Monitor social media posts and engagement metrics, identify viral content and emerging trends, track hashtag popularity, and generate real-time trend reports" \
  --domain "social"

Traffic Pattern Examples ​

Black Friday Simulation ​

bash
# E-commerce traffic during major sales event
pipegen run --message-rate 200 --duration 30m \
  --traffic-pattern "5m-10m:400%,15m-20m:600%,25m-28m:500%" \
  --dashboard

Breaking News Event ​

bash
# News website traffic spike
pipegen run --message-rate 100 --duration 15m \
  --traffic-pattern "2m-8m:800%,10m-12m:300%" \
  --dashboard --generate-report

Business Hours Pattern ​

bash
# Gradual increase during business hours
pipegen run --message-rate 50 --duration 20m \
  --traffic-pattern "2m-4m:150%,6m-8m:200%,10m-12m:300%,14m-16m:250%,18m-20m:150%" \
  --dashboard

Gaming Event Launch ​

bash
# Massive spike when new game features launch
pipegen run --message-rate 75 --duration 12m \
  --traffic-pattern "3m-8m:700%,10m-12m:400%" \
  --dashboard

Testing Scenarios ​

Performance Benchmarking ​

bash
# Establish baseline performance
pipegen run --message-rate 100 --duration 10m --generate-report

# Test with 2x load
pipegen run --message-rate 200 --duration 10m --generate-report

# Test with extreme spikes
pipegen run --message-rate 100 --duration 10m \
  --traffic-pattern "2m-4m:1000%" --dashboard

Failure Testing ​

bash
# Test recovery from high load
pipegen run --message-rate 50 --duration 8m \
  --traffic-pattern "2m-3m:2000%,5m-6m:1500%" \
  --dashboard

# Sustained high load
pipegen run --message-rate 100 --duration 10m \
  --traffic-pattern "2m-8m:500%" \
  --dashboard --generate-report

Capacity Planning ​

bash
# Model expected growth over time
pipegen run --message-rate 100 --duration 20m \
  --traffic-pattern "5m-15m:200%" \
  --dashboard --generate-report

# Test autoscaling response
pipegen run --message-rate 50 --duration 15m \
  --traffic-pattern "3m-5m:400%,8m-10m:600%,12m-14m:300%" \
  --dashboard

Integration Examples ​

CI/CD Pipeline Testing ​

bash
#!/bin/bash
# ci-test.sh - Automated pipeline testing

set -e

echo "🚀 Starting pipeline validation..."

# Create test pipeline
pipegen init ci-test-$(date +%s) --describe "Simple analytics for CI testing"

cd ci-test-*

# Validate project
pipegen validate

# Deploy local stack
pipegen deploy --startup-timeout 2m

# Run with traffic patterns and generate report
pipegen run --message-rate 100 --duration 3m \
  --traffic-pattern "30s-90s:300%" \
  --generate-report --reports-dir ./ci-reports

# Check for errors in report
if grep -q "ERROR" ci-reports/*.html; then
  echo "❌ Pipeline test failed - errors detected"
  exit 1
fi

echo "✅ Pipeline test passed"

Monitoring Integration ​

bash
# Export metrics to external monitoring
pipegen run --dashboard --message-rate 100 --duration 10m &
PIPELINE_PID=$!

# Collect metrics every 30 seconds
while kill -0 $PIPELINE_PID 2>/dev/null; do
  curl -s http://localhost:3000/api/metrics | \
    jq '.producer.rate' | \
    curl -X POST https://monitoring.company.com/metrics \
    -H "Content-Type: application/json" -d @-
  sleep 30
done

Multi-Environment Testing ​

bash
# Test across different configurations
environments=("local" "staging" "production")

for env in "${environments[@]}"; do
  echo "🌍 Testing in $env environment"
  
  pipegen run --config ".pipegen-$env.yaml" \
    --message-rate 100 --duration 5m \
    --traffic-pattern "1m-2m:200%,3m-4m:300%" \
    --generate-report --reports-dir "./reports-$env"
done

Advanced Use Cases ​

Multi-Pipeline Orchestration ​

bash
# Run multiple pipelines simultaneously
pipegen run --dashboard-port 3001 --project-dir ./pipeline-1 &
pipegen run --dashboard-port 3002 --project-dir ./pipeline-2 &
pipegen run --dashboard-port 3003 --project-dir ./pipeline-3 &

# Aggregate monitoring
pipegen dashboard --port 3000 --aggregate-ports 3001,3002,3003

Custom Schema Testing ​

bash
# Test with real production schemas
pipegen init schema-validation \
  --input-schema ./production-events.avsc \
  --describe "Validate production event processing"

pipegen run --message-rate 1000 --duration 10m \
  --dashboard --generate-report

Performance Profiling ​

bash
# Profile different message rates
rates=(50 100 200 500 1000)

for rate in "${rates[@]}"; do
  echo "📊 Testing at $rate msg/sec"
  
  pipegen run --message-rate $rate --duration 2m \
    --generate-report --reports-dir "./profile-reports" \
    --traffic-pattern "30s-90s:200%"
done

Sample Outputs ​

Dashboard Metrics ​

When running with --dashboard, you'll see real-time metrics like:

  • Producer Rate: 847 msg/sec (↑ in traffic spike)
  • Consumer Rate: 845 msg/sec (lag: 2 messages)
  • End-to-End Latency: P95 = 12ms, P99 = 28ms
  • Error Rate: 0.02% (2 errors in last minute)
  • System Health: ✅ All components healthy

Report Generation ​

Generated HTML reports include:

  • Executive Summary: Pipeline completed successfully, processed 50,000 messages
  • Performance Charts: Throughput trends, latency percentiles, error rates
  • Traffic Analysis: Pattern compliance, peak performance metrics
  • Resource Utilization: CPU, memory, network usage during execution
  • Recommendations: Optimal configurations, scaling suggestions

Common Patterns ​

Development Workflow ​

bash
# 1. Create and validate
pipegen init my-pipeline --describe "..."
pipegen validate --check-connectivity

# 2. Quick test
pipegen run --message-rate 10 --duration 1m

# 3. Load test
pipegen run --message-rate 100 --duration 5m \
  --traffic-pattern "1m-2m:300%" --dashboard

# 4. Generate documentation
pipegen run --generate-report --duration 10m

Production Validation ​

bash
# 1. Baseline test
pipegen run --message-rate 100 --duration 10m --generate-report

# 2. Stress test with spikes  
pipegen run --message-rate 100 --duration 15m \
  --traffic-pattern "3m-5m:500%,8m-10m:700%,12m-14m:400%" \
  --dashboard --generate-report

# 3. Sustained load test
pipegen run --message-rate 200 --duration 30m --generate-report

Next Steps ​

Released under the MIT License.

Copyright © 2025 PipeGen Team