Module observability 

Observability Service Implementation

This module provides a comprehensive observability service for the adaptive pipeline system. It combines metrics collection, performance tracking, alerting, and health monitoring to provide complete system visibility.

Overview

The observability service implementation provides:

• Real-Time Monitoring: Live performance tracking and system health monitoring
• Alerting: Threshold-based alerting with configurable conditions
• Performance Analysis: Detailed performance analysis and trend tracking
• Health Scoring: System health scoring based on multiple indicators
• Integration: Seamless integration with metrics and configuration services

Architecture

The observability service follows these design principles:

• Comprehensive Coverage: Monitors all aspects of system operation
• Real-Time Processing: Provides real-time insights and alerts
• Configurable Thresholds: Flexible alerting with configurable thresholds
• Performance Optimized: Low overhead monitoring with minimal impact

Key Components

Performance Tracker

Tracks real-time performance metrics:

• Active Operations: Number of currently running operations
• Total Operations: Cumulative count of all operations
• Throughput Metrics: Average and peak throughput measurements
• Error Rates: Error rate percentage and trend analysis
• Health Scoring: Overall system health score calculation

Alert System

Configurable alerting based on thresholds:

• Performance Alerts: Throughput and latency threshold alerts
• Error Rate Alerts: Error rate threshold monitoring
• Resource Alerts: Memory and CPU utilization alerts
• Health Alerts: System health degradation alerts

Health Monitoring

Comprehensive system health assessment:

• Component Health: Individual component health status
• Dependency Health: External dependency health monitoring
• Resource Health: System resource availability and utilization
• Overall Health: Aggregated system health score

Usage Examples

Basic Observability Service

Performance Tracking

Health Monitoring

Performance Tracking

Real-Time Metrics

The performance tracker maintains real-time metrics:

• Throughput Tracking: Continuous throughput measurement and averaging
• Operation Counting: Active and total operation counters
• Error Rate Calculation: Rolling error rate calculation
• Health Score Computation: Multi-factor health score calculation

Trend Analysis

• Moving Averages: Smoothed metrics using moving averages
• Peak Detection: Detection and tracking of performance peaks
• Anomaly Detection: Statistical anomaly detection in metrics
• Trend Prediction: Short-term trend prediction and forecasting

Alerting System

Alert Types

• Critical: System-threatening conditions requiring immediate attention
• Warning: Degraded performance or approaching thresholds
• Info: Informational alerts for significant events
• Debug: Detailed debugging information for troubleshooting

Alert Conditions

• Threshold-Based: Simple threshold crossing alerts
• Rate-Based: Rate of change alerts (e.g., rapidly increasing errors)
• Composite: Multi-condition alerts combining multiple metrics
• Time-Based: Time-window based alerts with hysteresis

Alert Management

• Deduplication: Prevents duplicate alerts for the same condition
• Escalation: Automatic escalation for unacknowledged alerts
• Suppression: Temporary alert suppression during maintenance
• Routing: Intelligent alert routing based on severity and type

Health Monitoring

Health Indicators

The system tracks multiple health indicators:

• Performance Health: Based on throughput and latency metrics
• Error Health: Based on error rates and failure patterns
• Resource Health: Based on CPU, memory, and I/O utilization
• Dependency Health: Based on external service availability

Health Scoring

Health scores are calculated using weighted factors:

• Performance Weight: 30% - System performance metrics
• Reliability Weight: 25% - Error rates and stability
• Resource Weight: 25% - Resource utilization and availability
• Dependency Weight: 20% - External dependency health

Integration

The observability service integrates with:

• Metrics Service: Collects and analyzes metrics data
• Configuration Service: Dynamic configuration of thresholds and settings
• Logging System: Correlates observability data with application logs
• External Monitoring: Integrates with external monitoring systems

Performance Considerations

Low Overhead Design

• Efficient Data Structures: Optimized data structures for metric storage
• Sampling: Configurable sampling rates for high-frequency metrics
• Batch Processing: Batch processing of metrics to reduce overhead
• Lazy Evaluation: Expensive calculations performed only when needed

Scalability

• Concurrent Processing: Thread-safe concurrent metric processing
• Memory Management: Bounded memory usage with automatic cleanup
• Resource Pooling: Efficient resource pooling and reuse
• Load Balancing: Distributed processing for high-load scenarios

Security and Privacy

Data Protection

• No Sensitive Data: Observability data contains no sensitive information
• Aggregated Metrics: Only aggregated statistics are stored and exposed
• Access Control: Observability endpoints can be secured
• Audit Logging: Access to observability data can be audited

Future Enhancements

Planned enhancements include:

• Machine Learning: AI-powered anomaly detection and prediction
• Advanced Analytics: Statistical analysis and correlation detection
• Custom Dashboards: User-configurable monitoring dashboards
• Integration APIs: APIs for integration with external tools

Structs

Alert

AlertThresholds

Alert thresholds for monitoring

ObservabilityService

Enhanced observability service for comprehensive monitoring

OperationTracker

Individual operation tracker

PerformanceTracker

Real-time performance tracking

SystemHealth

System health status

Enums

AlertSeverity

HealthStatus