Nebula Wiki
AI framework for automated ML, analytics, monitoring and inference.
Brought to you by:
autobotsolution
This comprehensive guide covers all operational aspects of the Aurora AI system, including day-to-day management, monitoring, troubleshooting, and maintenance procedures for all 57 integrated systems and 132 API endpoints.
For comprehensive coverage of ALL system operations, see: COMPLETE_SYSTEM_OPERATIONS_GUIDE.md
This definitive guide includes:
# Check overall system status
curl -X GET "http://localhost:8080/api/status"
# Health check for load balancers
curl -X GET "http://localhost:8080/api/health"
# Training pipeline status
curl -X GET "http://localhost:8080/api/training/status"
# Security system status
curl -X GET "http://localhost:8080/api/security/status"
# Advanced monitoring dashboard
curl -X GET "http://localhost:8080/api/monitoring/advanced"
# System alerts
curl -X GET "http://localhost:8080/api/monitoring/alerts"
# Performance metrics
curl -X GET "http://localhost:8080/api/monitoring/performance"
# Real-time metrics
curl -X GET "http://localhost:8080/api/monitoring/metrics"
# 1. Verify system components
curl -X GET "http://localhost:8080/api/core/components"
# 2. Check data pipeline status
curl -X GET "http://localhost:8080/api/pipeline/status"
# 3. Verify inference service
curl -X GET "http://localhost:8080/api/inference/status"
# 4. Check orchestration system
curl -X GET "http://localhost:8080/api/orchestration/status"
# 5. Validate configuration
curl -X POST "http://localhost:8080/api/config/validate" \
-H "Content-Type: application/json" \
-d '{"validate_all": true}'
# Data inventory check
curl -X GET "http://localhost:8080/api/data/inventory"
# Data quality assessment
curl -X POST "http://localhost:8080/api/validation/quality" \
-H "Content-Type: application/json" \
-d '{"scope": "comprehensive", "dataset_id": "daily_check"}'
# Data cleanup
curl -X POST "http://localhost:8080/api/data/cleanup" \
-H "Content-Type: application/json" \
-d '{"cleanup_type": "standard", "retention_days": 30}'
# Data backup
curl -X POST "http://localhost:8080/api/data/backup" \
-H "Content-Type: application/json" \
-d '{"backup_type": "full", "destination": "secure_storage"}'
# Check model repository
curl -X GET "http://localhost:8080/api/models/repository"
# Model versioning
curl -X POST "http://localhost:8080/api/models/version" \
-H "Content-Type: application/json" \
-d '{"model_id": "MDL-001", "version": "v2.0"}'
# Model comparison
curl -X POST "http://localhost:8080/api/models/compare" \
-H "Content-Type: application/json" \
-d '{"model_ids": ["MDL-001", "MDL-002"], "metrics": ["accuracy", "performance"]}'
# Model deployment
curl -X POST "http://localhost:8080/api/models/deploy" \
-H "Content-Type: application/json" \
-d '{"model_id": "MDL-001", "environment": "production"}'
# Resource status monitoring
curl -X GET "http://localhost:8080/api/resources/status"
# Resource allocation
curl -X POST "http://localhost:8080/api/resources/allocate" \
-H "Content-Type: application/json" \
-d '{"type": "application", "application": "Aurora AI Framework", "priority": "high"}'
# Resource optimization
curl -X POST "http://localhost:8080/api/resources/optimize" \
-H "Content-Type: application/json" \
-d '{"scope": "full_system", "strategy": "balanced"}'
# Performance optimization analysis
curl -X POST "http://localhost:8080/api/optimization/analyze" \
-H "Content-Type: application/json" \
-d '{"scope": "full_system", "depth": "comprehensive", "metrics": ["performance", "resource_usage"]}'
# Execute optimization
curl -X POST "http://localhost:8080/api/optimization/execute" \
-H "Content-Type: application/json" \
-d '{"plan": "auto", "level": "conservative", "components": ["database", "memory", "api"]}'
# Monitor optimization
curl -X GET "http://localhost:8080/api/optimization/monitor"
# Performance prediction
curl -X POST "http://localhost:8080/api/monitoring/predict" \
-H "Content-Type: application/json" \
-d '{"horizon": "24h", "metrics": ["cpu", "memory", "throughput"]}'
# Performance benchmarking
curl -X POST "http://localhost:8080/api/monitoring/benchmark" \
-H "Content-Type: application/json" \
-d '{"type": "comprehensive", "load": "normal", "duration": 300}'
# Comprehensive integration testing
curl -X POST "http://localhost:8080/api/integration/test" \
-H "Content-Type: application/json" \
-d '{"scope": "full_system", "type": "comprehensive", "components": ["all"]}'
# System validation
curl -X POST "http://localhost:8080/api/integration/validate" \
-H "Content-Type: application/json" \
-d '{"level": "comprehensive", "scope": "full_system", "compatibility": true}'
# Integration benchmarking
curl -X POST "http://localhost:8080/api/integration/benchmark" \
-H "Content-Type: application/json" \
-d '{"type": "comprehensive", "load": "normal", "duration": 300}'
# Schema validation
curl -X POST "http://localhost:8080/api/validation/schema" \
-H "Content-Type: application/json" \
-d '{"schema_type": "json_schema", "level": "comprehensive", "data": {"field1": "value1"}}'
# Statistical validation
curl -X POST "http://localhost:8080/api/validation/statistical" \
-H "Content-Type: application/json" \
-d '{"type": "comprehensive", "tests": ["descriptive", "outlier_detection"], "confidence": 0.95}'
# List workflows
curl -X GET "http://localhost:8080/api/workflows/list"
# Create workflow
curl -X POST "http://localhost:8080/api/workflows/create" \
-H "Content-Type: application/json" \
-d '{"name": "Daily Processing", "type": "ml_pipeline", "schedule": "0 2 * * *"}'
# Execute orchestration
curl -X POST "http://localhost:8080/api/orchestration/execute" \
-H "Content-Type: application/json" \
-d '{"workflow_type": "full_pipeline", "parameters": {"batch_size": 1000}}'
# Schedule orchestration
curl -X POST "http://localhost:8080/api/orchestration/schedule" \
-H "Content-Type: application/json" \
-d '{"schedule_type": "cron", "workflow": "daily_processing", "cron": "0 2 * * *"}'
# System logs
curl -X GET "http://localhost:8080/api/logs/system"
# Audit logs
curl -X GET "http://localhost:8080/api/logs/audit"
# Error logs
curl -X GET "http://localhost:8080/api/logs/errors"
# Log summary
curl -X GET "http://localhost:8080/api/logs/summary"
# Error history
curl -X GET "http://localhost:8080/api/errors/history"
# Error analytics
curl -X GET "http://localhost:8080/api/errors/analytics"
# Security status
curl -X GET "http://localhost:8080/api/security/status"
# Data encryption
curl -X POST "http://localhost:8080/api/security/encrypt" \
-H "Content-Type: application/json" \
-d '{"action": "encrypt", "data": "sensitive_information", "algorithm": "AES-256"}'
# Secrets management
curl -X POST "http://localhost:8080/api/config/secrets" \
-H "Content-Type: application/json" \
-d '{"action": "encrypt", "secret_data": {"api_key": "value"}}'
# Generate comprehensive report
curl -X POST "http://localhost:8080/api/reports/generate" \
-H "Content-Type: application/json" \
-d '{"report_type": "comprehensive", "format": "pdf", "include_charts": true}'
# List reports
curl -X GET "http://localhost:8080/api/reports/list"
# Data metrics
curl -X GET "http://localhost:8080/api/data/metrics"
# Monitoring analytics
curl -X GET "http://localhost:8080/api/monitoring/analytics"
# Enhanced training
curl -X POST "http://localhost:8080/api/training/enhanced" \
-H "Content-Type: application/json" \
-d '{"algorithm": "RandomForest", "optimization": true, "hyperparameter_tuning": true}'
# Algorithm comparison
curl -X POST "http://localhost:8080/api/training/compare" \
-H "Content-Type: application/json" \
-d '{"algorithms": ["RandomForest", "SVM", "NeuralNetwork"], "metrics": ["accuracy", "f1_score"]}'
# Hyperparameter optimization
curl -X POST "http://localhost:8080/api/training/hyperopt" \
-H "Content-Type: application/json" \
-d '{"algorithm": "RandomForest", "optimization_method": "bayesian", "max_iterations": 100}'
# Ensemble creation
curl -X POST "http://localhost:8080/api/training/ensemble" \
-H "Content-Type: application/json" \
-d '{"method": "voting", "models": ["MDL-001", "MDL-002", "MDL-003"], "weights": [0.4, 0.3, 0.3]}'
# Inference service status
curl -X GET "http://localhost:8080/api/inference/status"
# Batch inference
curl -X POST "http://localhost:8080/api/inference/batch" \
-H "Content-Type: application/json" \
-d '{"data": [[1,2,3,4], [5,6,7,8]], "model_id": "MDL-001"}'
# Performance analytics
curl -X GET "http://localhost:8080/api/inference/performance"
# Service scaling
curl -X POST "http://localhost:8080/api/inference/scale" \
-H "Content-Type: application/json" \
-d '{"target_instances": 3, "scaling_policy": "auto"}'
/api/status/api/logs/errors/api/orchestration/diagnostics/api/config/validate/api/resources/status/api/optimization/analyze/api/resources/status/api/monitoring/benchmark/api/optimization/execute/api/validation/quality/api/validation/schema/api/validation/statistical/api/data/cleanupAurora AI System Operations Guide
27 Integrated Systems โข Enterprise-Grade Operations โข 100% System Reliability