Performance Engineering and Optimization

2.

Fundamental Concepts and Metrics

2.1.

Core Performance Metrics

2.1.1.

Latency and Response Time

2.1.1.1.

Average Latency

2.1.1.2.

2.1.1.3.

End-to-End Latency

2.1.1.4.

Network Latency

2.1.2.

2.1.2.1.

Transactions Per Second

2.1.2.2.

Requests Per Second

2.1.2.3.

Peak Throughput

2.1.2.4.

Sustained Throughput

2.1.3.

2.1.3.1.

Concurrent Users

2.1.3.2.

Concurrent Requests

2.1.3.3.

Maximum Supported Concurrency

2.1.3.4.

Session Management

2.1.4.

Resource Utilization

2.1.4.1.

2.1.4.1.1.

2.1.4.1.2.

2.1.4.1.3.

Context Switching

2.1.4.2.

2.1.4.2.1.

2.1.4.2.2.

Memory Fragmentation

2.1.4.2.3.

Garbage Collection Impact

2.1.4.3.

2.1.4.3.1.

2.1.4.3.2.

2.1.4.3.3.

2.1.4.3.4.

2.1.4.4.

2.1.4.4.1.

Bandwidth Utilization

2.1.4.4.2.

2.1.4.4.3.

Retransmissions

2.1.4.4.4.

Connection Pooling Efficiency

2.1.5.

2.1.5.1.

Application Errors

2.1.5.2.

2.1.5.3.

2.1.5.4.

HTTP Status Code Distribution

2.1.6.

Availability Metrics

2.1.6.1.

Uptime Percentage

2.1.6.2.

Mean Time Between Failures

2.1.6.3.

Mean Time to Recovery

2.2.

Key Performance Indicators

2.2.1.

2.2.2.

Aligning KPIs with Business Goals

2.2.3.

Technical vs Business KPIs

2.2.4.

KPI Measurement and Tracking

2.3.

Service Level Objectives and Agreements

2.3.1.

SLO Definition and Measurement

2.3.2.

SLA Enforcement and Penalties

2.3.3.

2.3.4.

SLI Selection and Implementation

2.4.

Statistical Concepts in Performance

2.4.1.

Understanding Percentiles

2.4.1.1.

2.4.1.2.

2.4.1.3.

2.4.1.4.

2.4.1.5.

2.4.2.

Calculating and Interpreting Percentiles

2.4.3.

Distribution Analysis

2.4.4.

Outlier Detection

2.5.

Performance Laws and Principles

2.5.1.

2.5.1.1.

Formula and Application

2.5.1.2.

Limitations and Assumptions

2.5.2.

2.5.2.1.

Formula and Application

2.5.2.2.

Implications for Parallelization

2.5.3.

Universal Scalability Law

2.5.3.1.

Formula and Parameters

2.5.3.2.

Practical Use Cases

2.5.4.

Gustafson's Law

2.5.5.

Queueing Theory Fundamentals

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1. Introduction to Performance Engineering

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3. Performance Engineering in the Software Development Lifecycle