Dummy Data for Kubernetes Analysis Tools
This directory contains comprehensive sample Kubernetes YAML files designed for testing and demonstrating the capabilities of k8s-analyzer and k8s-reporter tools. The data represents realistic enterprise-grade applications with proper labeling, security configurations, and compliance requirements.
Directory Structure
dummy-data/
├── cluster-exports/ # Complete cluster exports
├── manifests/ # Individual resource manifests
├── multi-cluster/ # Multi-cluster deployment examples
└── README.md # This file
Applications Overview
The dummy data includes 5 different enterprise applications across 10 namespaces:
- Healthcare Management System - Patient records, appointments, HIPAA compliance
- E-commerce Platform - Online shopping, catalog, orders, payments
- Retail Point-of-Sale - In-store transactions, inventory, PCI DSS compliance
- Financial Services - Payment processing, billing, reporting
- Logistics Management - Inventory tracking, delivery management
Kubernetes Resources by Kind
Namespaces (10 total)
- healthcare-frontend - Frontend services for healthcare platform
- healthcare-backend - Backend APIs and services for healthcare
- healthcare-data - Database and data services for healthcare
- healthcare-analytics - Analytics and reporting for healthcare
- healthcare-integration - Integration services (HL7, FHIR)
- retail-sales - Point-of-sale and sales management
- retail-inventory - Inventory management and tracking
- ecommerce-frontend - E-commerce web interfaces
- ecommerce-backend - E-commerce backend services
- finance - Financial processing and billing
Labels Used:
- application
: Groups resources by business domain
- tier
: Technical layer (frontend, backend, database, analytics)
- environment
: Deployment environment (production, staging, development)
- team
: Owning team for operational responsibility
- compliance
: Regulatory requirements (hipaa, pcidss, sox)
- data-classification
: Data sensitivity level
Deployments (15+ instances)
Comprehensive application deployments with: - Resource specifications - CPU, memory, storage limits and requests - Health probes - Liveness, readiness, and startup probes - Security contexts - Non-root users, capability drops, read-only filesystems - Environment variables - Configuration and secrets integration - Volume mounts - Config files, SSL certificates, persistent storage - Affinity rules - Pod anti-affinity for high availability - Tolerations - Node selection and scheduling preferences
Key Applications:
- patient-portal
- Healthcare patient interface (25 replicas)
- patient-service
- Patient management API (20 replicas)
- appointment-service
- Appointment scheduling (15 replicas)
- product-catalog-api
- E-commerce catalog service (15 replicas)
- order-management-api
- Order processing (12 replicas)
- pos-system
- Retail point-of-sale (10 replicas)
- inventory-service
- Inventory management (12 replicas)
StatefulSets (4 instances)
Database and stateful services: - healthcare-postgresql - Primary healthcare database (PostgreSQL 14.9) - retail-postgresql - Retail application database (PostgreSQL 13.3) - elasticsearch-cluster - E-commerce search engine (6 replicas) - redis-cluster - Caching and session storage
Features: - Volume claim templates for persistent storage - Service discovery through headless services - Database initialization scripts - Monitoring exporters (Prometheus metrics) - Replication and backup configurations
Services (12+ instances)
Load balancing and service discovery: - LoadBalancer services - External access with AWS NLB annotations - ClusterIP services - Internal service communication - NodePort services - Development and testing access - Headless services - StatefulSet service discovery
Service Types by Application: - Healthcare: Patient portal, API services, database connections - E-commerce: Web storefront, catalog API, search services - Retail: POS terminals, inventory APIs - Multi-port configurations for HTTP/HTTPS, metrics, management
ConfigMaps (8+ instances)
Application and infrastructure configuration:
Application Configurations
- patient-portal-config - Healthcare portal settings, security, features
- patient-service-config - Spring Boot configuration, database pools, Kafka
- pos-system-config - Retail POS features, security, compliance
- inventory-service-config - Inventory management, caching, notifications
Infrastructure Configurations
- nginx.conf - Reverse proxy, SSL termination, rate limiting, security headers
- postgresql.conf - Database tuning, connection pools, performance settings
- prometheus.yml - Monitoring configuration, scrape targets, alerting
- elasticsearch.yml - Search cluster configuration, security, performance
Configuration Categories: - Security settings (timeouts, authentication, encryption) - Feature flags (toggles for functionality) - Performance tuning (connection pools, caching, timeouts) - Compliance controls (audit logging, data retention) - Integration endpoints (APIs, databases, message queues)
Secrets (10+ instances)
Secure credential and certificate management:
Database Credentials
- healthcare-database-credentials - PostgreSQL connection strings, usernames, passwords
- retail-database-credentials - Retail database access credentials
- elasticsearch-credentials - Search cluster authentication
Application Secrets
- healthcare-app-secrets - JWT tokens, encryption keys, session secrets
- retail-app-secrets - POS system encryption, payment processing keys
- aws-credentials - Cloud storage and services access
SSL/TLS Certificates
- healthcare-ssl-certificates - HTTPS certificates for healthcare services
- retail-ssl-certificates - PCI DSS compliant certificates for retail
Security Features: - Base64 encoded values with comments showing plaintext - Separate secrets per namespace for isolation - Multi-purpose secrets (database + application + certificates) - Compliance-specific secrets (HIPAA, PCI DSS requirements)
ServiceAccounts (8 instances)
RBAC and service authentication:
- healthcare-frontend-sa - Frontend service permissions
- healthcare-backend-sa - Backend API permissions
- healthcare-data-sa - Database access permissions
- retail-sales-sa - Sales system permissions
- retail-inventory-sa - Inventory management permissions
- retail-data-sa - Retail database permissions
Features: - Namespace isolation for security - Application-specific permissions - Compliance labeling for audit trails
PersistentVolumeClaims (6+ instances)
Storage requirements for different use cases:
Healthcare Storage
- healthcare-audit-logs-pvc - HIPAA audit trail storage (500Gi, ReadWriteMany)
- patient-documents-pvc - Medical records and documents (2000Gi, ReadWriteMany)
E-commerce Storage
- static-assets-pvc - Web assets and media files
- order-files-pvc - Order processing documents
- image-cache-pvc - Product image caching
Storage Classes:
- encrypted-high-performance-ssd
- High IOPS for databases
- encrypted-standard-ssd
- General purpose encrypted storage
- standard
- Basic persistent storage
- fast-ssd
- Performance-optimized storage
Jobs and CronJobs (3 instances)
Batch processing and scheduled tasks: - daily-report-generator - Financial reporting (daily at 1 AM) - inventory-sync - Inventory synchronization job - data-migration - Database migration tasks
Features: - Cron schedule expressions - Resource limits for batch operations - Persistent volume integration for output - Retry and failure policies
Compliance and Security Features
HIPAA Compliance (Healthcare)
- Audit logging enabled for all PHI access
- Data encryption at rest and in transit
- Access controls and authentication
- Data retention policies (7 years)
- Patient data isolation and security
PCI DSS Compliance (Retail/Finance)
- Payment card data protection
- Secure payment processing
- Network segmentation
- Regular security monitoring
- Encrypted communication channels
Security Best Practices
- Non-root container execution
- Read-only root filesystems
- Capability dropping (ALL capabilities removed)
- Security contexts and seccomp profiles
- Network policies and service mesh integration
- Regular credential rotation
Label Strategy
Organizational Labels
application
: Business application groupingteam
: Owning team for operationscost-center
: Financial tracking and chargeback
Technical Labels
tier
: Architecture layer classificationcomponent
: Specific functional componentversion
: Application version tracking
Operational Labels
environment
: Deployment stagecompliance
: Regulatory requirementsdata-classification
: Data sensitivity level
Example Label Usage
labels:
application: healthcare
tier: backend
component: patient-management
team: backend-team
environment: production
compliance: hipaa
data-classification: sensitive
version: v2.8.4
cost-center: "2002"
File Sizes and Resource Counts
Large Files (40KB+)
healthcare-platform.yaml
- 42KB, 30+ resourcesecommerce-platform.yaml
- 34KB, 25+ resources
Medium Files (10-20KB)
retail-platform.yaml
- 18KB, 15+ resourcesfinance-logistics-combined.yaml
- 12KB, 20+ resources
Resource Distribution
- Total Resources: 100+ Kubernetes resources
- Total Size: 150KB+ of YAML configuration
- Namespaces: 10 across 5 applications
- Deployments: 15+ with comprehensive configurations
- StatefulSets: 4 database and storage systems
- ConfigMaps: 8+ with detailed application settings
- Secrets: 10+ covering all credential types
Usage Examples
Analyze Healthcare Resources
Generate Retail Compliance Report
k8s-reporter generate --input dummy-data/cluster-exports/retail-platform.yaml --output retail-report.html --filter="compliance=pcidss"
Multi-Application Analysis
k8s-analyzer batch --directory dummy-data/cluster-exports/ --export-format sqlite --output analysis.db
Resource Relationship Analysis
k8s-analyzer relationships --input dummy-data/cluster-exports/ecommerce-platform.yaml --visualize --output ecommerce-graph.png
Testing Scenarios
The dummy data supports various testing scenarios:
- Single Application Analysis - Healthcare, e-commerce, retail platforms
- Multi-Namespace Operations - Cross-namespace resource relationships
- Compliance Reporting - HIPAA, PCI DSS, SOX compliance checks
- Resource Optimization - CPU, memory, storage analysis
- Security Assessment - Security context, RBAC, network policy analysis
- Label-Based Filtering - Team, application, compliance-based queries
- Performance Analysis - Resource utilization and scaling patterns
- Cost Analysis - Resource allocation and cost center reporting
This comprehensive dataset provides realistic enterprise scenarios for thorough testing of Kubernetes analysis and reporting tools.