OpenShift Demo Lab Applications

This repository contains a comprehensive suite of demonstration applications designed for OpenShift and container orchestration technical labs. The demo applications progress from basic containerization concepts through advanced production-ready deployments.

Demo Application Progression

This lab follows a progressive approach to demonstrate increasingly sophisticated OpenShift concepts:

Demo App V1: Ephemeral Storage (demo-app-v1/)

Focus: Basic containerization and ephemeral storage limitations

A Flask-based web application demonstrating ephemeral storage characteristics in containerized environments.

Key Concepts:

• In-memory data persistence (lost on restart)
• Real-time container resource monitoring (CPU/RAM usage vs limits)
• Basic OpenShift deployment patterns
• Step-by-step progress visualization
• Data loss demonstration via "Reload Page" functionality

Learning Outcomes: Understanding container storage limitations and the need for persistent solutions.

Demo App V2: Persistent Storage (demo-app-v2/)

Focus: Database persistence and production deployment patterns

An enhanced Flask application demonstrating persistent storage using database backends.

Key Concepts:

• PostgreSQL database persistence (survives pod restarts and scaling)
• Advanced step progression with manual completion controls
• Enhanced container resource monitoring with deployment limits
• Database connection handling and initialization
• Production-ready deployment manifests

Learning Outcomes: How persistent storage enables stateful applications and production deployments.

Demo App V3: Resource Management & Auto-Scaling (demo-app-v3/)

Focus: OpenShift CLI operations, resource limits, and horizontal scaling

CLI-focused deployment demonstrating resource management and horizontal pod autoscaling.

Key Concepts:

• Aggressive resource limits for scaling demonstrations
• Horizontal Pod Autoscaler (HPA) configuration
• Built-in load testing to trigger scaling events
• Real-time resource monitoring (CPU/memory vs limits)
• oc command-line deployment workflows

Learning Outcomes: Production resource management, autoscaling behavior, and CLI-driven operations.

Demo App V4: Health Probes & Application Readiness (demo-app-v4/)

Focus: Application lifecycle management and health probe configuration

Advanced deployment workflow demonstrating health probe configuration and production readiness.

Key Concepts:

• Health probe detection and status monitoring (liveness, readiness, startup)
• Step 6 completion workflow based on probe configuration
• Multiple probe configuration methods (YAML files, CLI patches)
• Application lifecycle management and self-healing containers
• Production health monitoring and troubleshooting

Learning Outcomes: Complete application lifecycle management from deployment through production monitoring.

Check-in App: Lab Registration System (check-in-app/)

Focus: Lab participant management and group organization

A registration system for lab participants with automated group assignment and admin controls.

Key Features:

• Email-based user registration with IBM Cloud SDK validation
• Automatic group assignment (3 users per group)
• Admin dashboard with password protection
• Real-time registration statistics and completion tracking
• PostgreSQL integration with OpenShift deployment

Purpose: Manages participant registration and group organization for hands-on lab sessions.

Architecture Comparison

Feature	V1 (Ephemeral)	V2 (Persistent)	V3 (Resource Mgmt)	V4 (Health Probes)
Storage	In-memory	PostgreSQL/SQLite	PostgreSQL	PostgreSQL
Data Survival	❌ Lost on restart	✅ Survives restarts	✅ Survives restarts	✅ Survives restarts
Resource Monitoring	✅ CPU/RAM metrics	✅ Enhanced metrics	✅ Limits vs usage	✅ Container-aware
Auto-Scaling	❌ Manual scaling	❌ Manual scaling	✅ HPA enabled	✅ HPA compatible
Health Probes	❌ Not configured	❌ Not configured	✅ Pre-configured	🔧 Step 6 workflow
Load Testing	✅ Basic endpoints	✅ Basic endpoints	✅ Built-in HPA triggers	❌ Focus on probes
CLI Focus	Basic deployment	Basic deployment	✅ Full CLI workflow	✅ Probe configuration
Production Ready	Basic demo	Database ready	Resource optimized	Health monitoring
Step Completion	Static progress	Manual progression	Automatic scaling	Probe-based completion

Learning Path

The applications are designed to be used in sequence, with each building upon concepts from the previous version:

1. Start with V1 → Understand ephemeral storage limitations and basic containerization
2. Progress to V2 → Learn persistent storage patterns and database integration
3. Advance to V3 → Master resource management, scaling, and CLI operations
4. Complete with V4 → Implement production health monitoring and probe configuration

Key Kubernetes/OpenShift Concepts Demonstrated

Container Fundamentals

• Container lifecycle management (V1-V4)
• Resource requests and limits (V3, V4)
• Environment variable configuration (V2-V4)
• Multi-stage Docker builds (All versions)

Storage and Persistence

• Ephemeral storage limitations (V1)
• Persistent Volume Claims (PVC) (V2-V4)
• Database integration patterns (V2-V4)
• StatefulSet vs Deployment trade-offs (V2-V4)

Networking and Services

• Service discovery and DNS (All versions)
• Route configuration with TLS termination (All versions)
• Load balancing across pods (V3, V4)
• Health check integration (V4)

Scaling and Performance

• Manual scaling operations (V1, V2)
• Horizontal Pod Autoscaler (HPA) (V3)
• Resource utilization monitoring (V3, V4)
• Load testing and traffic generation (V3)

Production Readiness

• Health probe configuration (V4)
• Rolling deployments (V3, V4)
• Application lifecycle management (V4)
• Monitoring and troubleshooting (All versions)

Development Workflows

The repository includes automated task management via mise.toml for streamlined development across all applications:

Local Development

# Install dependencies for all applications
mise run install-all

# V1 Development (Ephemeral Storage)
mise run v1-dev
mise run v1-docker-run     # Test with resource limits

# V2 Development (Persistent Storage)  
mise run v2-dev
mise run v2-docker-run     # Test with SQLite

# V3/V4 Development (Full OpenShift Features)
# Use V3 or V4 directories directly with standard Flask development

# Check-in App Development (Registration System)
mise run checkin-dev

Container Testing

# Build and test containers locally
mise run v1-docker-run     # V1 with 256m RAM, 0.5 CPU limits
mise run v2-docker-run     # V2 with SQLite database

# Clean up containers
mise run clean-docker

OpenShift Deployment

Each demo application includes comprehensive OpenShift deployment manifests:

V1: Basic Containerization

cd demo-app-v1/
oc apply -f openshift/     # Basic deployment with resource limits

V2: Persistent Storage

cd demo-app-v2/
oc apply -f openshift/postgresql.yaml    # Deploy database first
oc apply -f openshift/                   # Deploy app with persistence

V3: Resource Management & CLI Focus

cd demo-app-v3/
# Follow comprehensive CLI workflow in demo-app-v3/README.md
oc apply -f openshift/postgresql.yaml
oc apply -f openshift/buildconfig.yaml
oc start-build demo-app-v3 --follow
oc apply -f openshift/deployment.yaml
oc apply -f openshift/service.yaml
oc apply -f openshift/route.yaml
oc apply -f openshift/hpa.yaml

V4: Health Probe Configuration

cd demo-app-v4/
# Deploy without probes, then configure via CLI
# Follow health probe workflow in demo-app-v4/README.md
oc apply -f openshift/deployment.yaml   # No probes initially
# ... configure probes via oc patch commands

Check-in App: Registration System

cd check-in-app/
./deploy.sh    # Automated deployment with PostgreSQL and secrets

Common OpenShift Components

All applications include production-ready configurations:

• BuildConfig: Source-to-Image (S2I) builds from Git repositories
• ImageStream: Container image management and automatic deployment triggers
• Deployment: Application pods with resource limits and environment configuration
• Service: Internal load balancing and service discovery
• Route: External HTTPS access with TLS edge termination
• PostgreSQL: Persistent database with PVC storage (V2-V4, Check-in)
• Secrets: Secure configuration management for database credentials
• HPA: Horizontal Pod Autoscaler for automatic scaling (V3)

Repository Structure

tech-lab-demos/
├── demo-app-v1/          # Ephemeral storage demo
│   ├── app.py           # Flask application 
│   ├── openshift/       # Deployment manifests
│   └── README.md        # V1-specific documentation
├── demo-app-v2/          # Persistent storage demo  
│   ├── app.py           # Enhanced Flask with database
│   ├── openshift/       # Production manifests
│   └── README.md        # V2-specific documentation
├── demo-app-v3/          # Resource management & CLI demo
│   ├── app.py           # Resource monitoring features
│   ├── openshift/       # HPA and resource limits
│   └── README.md        # CLI-focused documentation
├── demo-app-v4/          # Health probe configuration demo
│   ├── app.py           # Probe detection logic
│   ├── openshift/       # Deployment without initial probes
│   └── README.md        # Health probe workflow guide
├── check-in-app/         # Lab registration system
│   ├── app.py           # Registration and admin features
│   ├── openshift/       # Production deployment
│   ├── deploy.sh        # Automated deployment script
│   └── README.md        # Registration system guide
├── mise.toml            # Development task automation
└── README.md            # This comprehensive overview

This comprehensive lab platform provides hands-on experience with container orchestration, storage management, resource optimization, health monitoring, and production deployment patterns in OpenShift environments.