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Quality Scenarios

Overview​

Quality scenarios provide concrete examples of how BookWorm should behave under specific conditions. Each scenario follows the standard format: Source → Stimulus → Environment → Artifact → Response → Response Measure.

Performance Scenarios​

P-1: Peak Shopping Load​

  • Source: 1000 concurrent users browsing the catalog
  • Stimulus: Search and filter requests during peak hours (Black Friday)
  • Environment: Production environment under normal operation
  • Artifact: Catalog service and database
  • Response: System maintains response times under 2 seconds
  • Response Measure: 95th percentile response time < 2000ms, throughput > 500 RPS

P-2: Book Search Performance​

  • Source: User searching for books with complex filters
  • Stimulus: Search query with multiple filters and sorting
  • Environment: Production with full catalog (100k+ books)
  • Artifact: Search service and Elasticsearch index
  • Response: Search results returned quickly with relevance ranking
  • Response Measure: Search response time < 500ms for 99% of queries

P-3: Real-time Chat Performance​

  • Source: 200 concurrent chat sessions
  • Stimulus: Real-time message exchange between users and AI
  • Environment: Production with SignalR hub scaling
  • Artifact: Chat service and WebSocket connections
  • Response: Messages delivered in real-time with AI responses
  • Response Measure: Message delivery latency < 100ms, AI response < 3s

Reliability Scenarios​

R-1: Database Failure Recovery​

  • Source: Primary PostgreSQL database becomes unavailable
  • Stimulus: Database connection failure due to infrastructure issue
  • Environment: Production during business hours
  • Artifact: All services using PostgreSQL
  • Response: System switches to read replicas, writes queued for retry
  • Response Measure: Service restored within 5 minutes, zero data loss

R-2: External Service Degradation​

  • Source: AI service (Ollama) experiencing high latency
  • Stimulus: AI chat requests timing out or responding slowly
  • Environment: Production during chat operations
  • Artifact: Chat service AI integration
  • Response: Circuit breaker activates, fallback responses provided
  • Response Measure: System remains operational, users receive feedback < 5s

R-3: Container Instance Failure​

  • Source: Container instance crashes due to memory leak
  • Stimulus: Application exception causing container termination
  • Environment: Azure Container Apps production environment
  • Artifact: Any microservice instance
  • Response: Health checks detect failure, new instance started automatically
  • Response Measure: Service automatically recovers within 30 seconds

Scalability Scenarios​

S-1: Traffic Surge Handling​

  • Source: 10x normal traffic load during promotional event
  • Stimulus: Sudden increase in concurrent users (viral social media post)
  • Environment: Production during promotional events
  • Artifact: All services and Azure Container Apps infrastructure
  • Response: Auto-scaling triggers, additional instances deployed
  • Response Measure: System handles increased load without degradation < 2 minutes

S-2: Geographic Expansion​

  • Source: New market launch requiring regional deployment
  • Stimulus: Need for reduced latency in new geographic region
  • Environment: Multi-region Azure deployment
  • Artifact: Complete application stack and data replication
  • Response: Services deployed to new region with data synchronization
  • Response Measure: Regional latency < 100ms, data consistency maintained

S-3: Storage Scaling​

  • Source: Catalog grows from 100k to 1M books
  • Stimulus: Large volume of new book data and images
  • Environment: Production with increasing data storage needs
  • Artifact: Database and Azure Storage services
  • Response: Storage automatically scales, indexing performance maintained
  • Response Measure: Search performance remains < 500ms despite 10x data growth

Security Scenarios​

SEC-1: Authentication Attack​

  • Source: Malicious user attempting brute force login
  • Stimulus: Multiple failed authentication attempts from same IP
  • Environment: Production API gateway and Keycloak
  • Artifact: Authentication service and rate limiting
  • Response: Account locked after 5 attempts, IP blocked, security team notified
  • Response Measure: Attack mitigated within 1 minute, zero unauthorized access

SEC-2: Data Breach Attempt​

  • Source: Unauthorized attempt to access customer data
  • Stimulus: SQL injection or API manipulation attempt
  • Environment: Production database and API services
  • Artifact: Data access layer and API endpoints
  • Response: Request blocked by input validation, attempt logged, alerts triggered
  • Response Measure: Zero unauthorized data access, full audit trail maintained

SEC-3: Token Compromise​

  • Source: JWT token potentially compromised
  • Stimulus: Token usage from unusual geographic location
  • Environment: Production API services
  • Artifact: JWT validation and Keycloak token introspection
  • Response: Token revoked, user session terminated, re-authentication required
  • Response Measure: Compromise contained within 2 minutes, user notified

Maintainability Scenarios​

M-1: New Feature Development​

  • Source: Development team adding new AI book recommendation feature
  • Stimulus: Business requirement for personalized book recommendations
  • Environment: Development and staging environments
  • Artifact: Catalog service and new AI recommendation service
  • Response: Feature implemented without affecting existing functionality
  • Response Measure: Development completed in 2 weeks, zero regression tests failed

M-2: Technology Migration​

  • Source: Need to migrate from PostgreSQL to newer version
  • Stimulus: Performance optimization and security updates
  • Environment: Production environment with zero downtime requirement
  • Artifact: Data access layer and migration scripts
  • Response: Migration completed with data consistency maintained
  • Response Measure: Zero downtime, all data migrated successfully, performance improved

M-3: Service Refactoring​

  • Source: Technical debt reduction in ordering service
  • Stimulus: Code complexity metrics exceed threshold
  • Environment: Development with automated testing
  • Artifact: Ordering service business logic and API contracts
  • Response: Service refactored while maintaining API compatibility
  • Response Measure: Code complexity reduced 50%, test coverage maintained > 80%

Usability Scenarios​

U-1: Mobile User Experience​

  • Source: User browsing catalog on mobile device
  • Stimulus: Searching and filtering books on small screen
  • Environment: Mobile browser with varying network conditions
  • Artifact: Web application responsive design
  • Response: Interface adapts to screen size, touch-friendly controls
  • Response Measure: Task completion rate > 90%, user satisfaction score > 4/5

U-2: Accessibility Compliance​

  • Source: Visually impaired user using screen reader
  • Stimulus: Navigating catalog and placing order
  • Environment: Desktop with assistive technology
  • Artifact: Web application accessibility features
  • Response: All functionality accessible via keyboard and screen reader
  • Response Measure: WCAG 2.1 AA compliance verified, zero accessibility barriers

U-3: Error Recovery​

  • Source: User encounters form submission error
  • Stimulus: Network timeout during checkout process
  • Environment: Web browser with intermittent connectivity
  • Artifact: Error handling and user feedback systems
  • Response: Clear error message displayed, user can retry or recover
  • Response Measure: User completes task within 3 attempts, error recovery rate > 95%

Testing Integration​

Scenario-Driven Testing​

Each quality scenario maps to specific testing approaches:

Continuous Validation​

Quality scenarios are continuously validated through:

  • Automated Testing: K6 performance tests, security scans
  • Production Monitoring: Real-time metrics and alerting
  • User Feedback: Analytics and experience surveys
  • Regular Reviews: Quality scenario updates and improvements