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Computer Science
DevOps and SRE
Performance Engineering and Optimization
1. Introduction to Performance Engineering
2. Fundamental Concepts and Metrics
3. Performance Engineering in the Software Development Lifecycle
4. Performance Modeling and Forecasting
5. Performance Testing Methodologies
6. System Monitoring and Observability
7. Performance Analysis and Tuning
8. Performance in Modern Architectures
9. Advanced Performance Topics
10. Tools and Technologies
11. Performance Engineering Best Practices
6.
System Monitoring and Observability
6.1.
The Three Pillars of Observability
6.1.1.
Metrics
6.1.1.1.
System Metrics
6.1.1.2.
Application Metrics
6.1.1.3.
Business Metrics
6.1.1.4.
Custom Metrics
6.1.2.
Logs
6.1.2.1.
Log Aggregation
6.1.2.2.
Log Analysis
6.1.2.3.
Structured Logging
6.1.2.4.
Log Correlation
6.1.3.
Traces
6.1.3.1.
Distributed Tracing
6.1.3.2.
Trace Collection
6.1.3.3.
Trace Visualization
6.1.3.4.
Trace Sampling
6.2.
Monitoring Strategies
6.2.1.
Black-Box Monitoring
6.2.1.1.
Synthetic Transactions
6.2.1.2.
External Probes
6.2.1.3.
User Journey Monitoring
6.2.2.
White-Box Monitoring
6.2.2.1.
Internal Instrumentation
6.2.2.2.
Application Health Checks
6.2.2.3.
Code-level Metrics
6.2.3.
Hybrid Monitoring Approaches
6.3.
Application Performance Monitoring
6.3.1.
Code-level Visibility
6.3.1.1.
Function Tracing
6.3.1.2.
Exception Tracking
6.3.1.3.
Performance Profiling
6.3.2.
Transaction Tracing
6.3.2.1.
End-to-End Request Tracking
6.3.2.2.
Latency Breakdown
6.3.2.3.
Transaction Flow Analysis
6.3.3.
Dependency Mapping
6.3.3.1.
Service Dependency Graphs
6.3.3.2.
Upstream and Downstream Analysis
6.3.3.3.
Critical Path Identification
6.3.4.
Error Tracking and Analysis
6.4.
Infrastructure Monitoring
6.4.1.
Server Metrics
6.4.1.1.
CPU Utilization
6.4.1.2.
Memory Usage
6.4.1.3.
Disk I/O
6.4.1.4.
Network I/O
6.4.1.5.
Hardware Health
6.4.2.
Network Metrics
6.4.2.1.
Latency
6.4.2.2.
Jitter
6.4.2.3.
Packet Loss
6.4.2.4.
Network Topology
6.4.3.
Container and Orchestration Metrics
6.4.3.1.
Container Resource Usage
6.4.3.2.
Orchestrator Events
6.4.3.3.
Pod Performance
6.4.4.
Cloud Infrastructure Metrics
6.5.
Real User Monitoring
6.5.1.
Client-side Performance Metrics
6.5.2.
User Experience Analysis
6.5.3.
Core Web Vitals
6.5.4.
Mobile Performance Monitoring
6.6.
Alerting and Anomaly Detection
6.6.1.
Threshold-based Alerts
6.6.2.
Statistical Anomaly Detection
6.6.3.
Machine Learning-based Detection
6.6.4.
Incident Response Workflows
6.6.5.
Alert Fatigue Management
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5. Performance Testing Methodologies
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7. Performance Analysis and Tuning