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Performance Testing

Master performance testing methodologies and tools.

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Performance Testing Types

Understand different types of performance testing and their purposes

Content by: Paras Dadhania

Software Testing & QA Specialist

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Performance Testing Categories

•Load Testing: Normal expected load conditions
•Stress Testing: Beyond normal capacity limits
•Volume Testing: Large amounts of data
•Spike Testing: Sudden load increases
•Endurance Testing: Extended period testing
•Scalability Testing: System scaling capabilities

Performance Testing Objectives

Code Example

// Performance Testing Goals
const performanceGoals = {
    "Response Time": {
        "Page Load": "< 3 seconds",
        "API Response": "< 1 second",
        "Database Query": "< 500ms",
        "Search Results": "< 2 seconds"
    },
    "Throughput": {
        "Requests per Second": "1000+ RPS",
        "Concurrent Users": "5000+ users",
        "Data Processing": "10GB/hour",
        "Transaction Rate": "500+ TPS"
    },
    "Resource Utilization": {
        "CPU Usage": "< 80%",
        "Memory Usage": "< 85%",
        "Disk I/O": "< 70%",
        "Network Bandwidth": "< 75%"
    },
    "Availability": {
        "Uptime": "99.9%",
        "Error Rate": "< 0.1%",
        "Recovery Time": "< 5 minutes",
        "Mean Time Between Failures": "> 30 days"
    }
};

// Performance Testing Types
const testingTypes = {
    "Load Testing": {
        "Purpose": "Verify system behavior under normal load",
        "Load Level": "Expected user load",
        "Duration": "30-60 minutes",
        "Focus": "Response time and throughput"
    },
    "Stress Testing": {
        "Purpose": "Find breaking point of the system",
        "Load Level": "Beyond normal capacity",
        "Duration": "15-30 minutes",
        "Focus": "System stability and recovery"
    },
    "Volume Testing": {
        "Purpose": "Test with large amounts of data",
        "Load Level": "Maximum data volume",
        "Duration": "2-4 hours",
        "Focus": "Data handling and storage"
    },
    "Spike Testing": {
        "Purpose": "Test sudden load increases",
        "Load Level": "Sudden spikes in traffic",
        "Duration": "5-10 minutes",
        "Focus": "System resilience"
    }
};

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// Performance Testing Goals
const performanceGoals = {
    "Response Time": {
        "Page Load": "< 3 seconds",
        "API Response": "< 1 second",
        "Database Query": "< 500ms",
        "Search Results": "< 2 seconds"
    },
    "Throughput": {
        "Requests per Second": "1000+ RPS",
        "Concurrent Users": "5000+ users",
        "Data Processing": "10GB/hour",
        "Transaction Rate": "500+ TPS"
    },
    "Resource Utilization": {
        "CPU Usage": "< 80%",
        "Memory Usage": "< 85%",
        "Disk I/O": "< 70%",
        "Network Bandwidth": "< 75%"
    },
    "Availability": {
        "Uptime": "99.9%",
        "Error Rate": "< 0.1%",
        "Recovery Time": "< 5 minutes",
        "Mean Time Between Failures": "> 30 days"
    }
};

// Performance Testing Types
const testingTypes = {
    "Load Testing": {
        "Purpose": "Verify system behavior under normal load",
        "Load Level": "Expected user load",
        "Duration": "30-60 minutes",
        "Focus": "Response time and throughput"
    },
    "Stress Testing": {
        "Purpose": "Find breaking point of the system",
        "Load Level": "Beyond normal capacity",
        "Duration": "15-30 minutes",
        "Focus": "System stability and recovery"
    },
    "Volume Testing": {
        "Purpose": "Test with large amounts of data",
        "Load Level": "Maximum data volume",
        "Duration": "2-4 hours",
        "Focus": "Data handling and storage"
    },
    "Spike Testing": {
        "Purpose": "Test sudden load increases",
        "Load Level": "Sudden spikes in traffic",
        "Duration": "5-10 minutes",
        "Focus": "System resilience"
    }
};

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Load Testing & Stress Testing

Learn load testing and stress testing methodologies and best practices

Content by: Yash Sanghavi

Software Testing & QA Specialist

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Load Testing Process

•Define Performance Requirements
•Create Test Scenarios
•Prepare Test Data
•Configure Test Environment
•Execute Load Tests
•Analyze Results and Report

Load Testing Scenarios

Code Example

// Load Testing Scenarios
const loadTestScenarios = {
    "E-commerce Website": {
        "Scenario 1": {
            "Name": "Product Browsing",
            "Users": 100,
            "Duration": "30 minutes",
            "Actions": [
                "Login to system",
                "Browse products",
                "Add items to cart",
                "View product details",
                "Search products"
            ]
        },
        "Scenario 2": {
            "Name": "Checkout Process",
            "Users": 50,
            "Duration": "20 minutes",
            "Actions": [
                "Login to system",
                "Add items to cart",
                "Proceed to checkout",
                "Enter payment details",
                "Complete purchase"
            ]
        }
    },
    "API Load Testing": {
        "Scenario 1": {
            "Name": "User Authentication",
            "RPS": 500,
            "Duration": "15 minutes",
            "Endpoints": [
                "POST /auth/login",
                "POST /auth/refresh",
                "GET /auth/profile"
            ]
        },
        "Scenario 2": {
            "Name": "Data Retrieval",
            "RPS": 1000,
            "Duration": "30 minutes",
            "Endpoints": [
                "GET /api/users",
                "GET /api/products",
                "GET /api/orders"
            ]
        }
    }
};

// Stress Testing Scenarios
const stressTestScenarios = {
    "Gradual Load Increase": {
        "Phase 1": "100 users for 10 minutes",
        "Phase 2": "200 users for 10 minutes",
        "Phase 3": "400 users for 10 minutes",
        "Phase 4": "800 users for 10 minutes",
        "Phase 5": "1600 users for 10 minutes"
    },
    "Sudden Load Spike": {
        "Normal Load": "100 users for 5 minutes",
        "Spike": "1000 users for 2 minutes",
        "Recovery": "100 users for 5 minutes"
    },
    "Resource Exhaustion": {
        "Memory Test": "Large data processing",
        "CPU Test": "Complex calculations",
        "Disk Test": "Heavy file operations",
        "Network Test": "High bandwidth usage"
    }
};

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// Load Testing Scenarios
const loadTestScenarios = {
    "E-commerce Website": {
        "Scenario 1": {
            "Name": "Product Browsing",
            "Users": 100,
            "Duration": "30 minutes",
            "Actions": [
                "Login to system",
                "Browse products",
                "Add items to cart",
                "View product details",
                "Search products"
            ]
        },
        "Scenario 2": {
            "Name": "Checkout Process",
            "Users": 50,
            "Duration": "20 minutes",
            "Actions": [
                "Login to system",
                "Add items to cart",
                "Proceed to checkout",
                "Enter payment details",
                "Complete purchase"
            ]
        }
    },
    "API Load Testing": {
        "Scenario 1": {
            "Name": "User Authentication",
            "RPS": 500,
            "Duration": "15 minutes",
            "Endpoints": [
                "POST /auth/login",
                "POST /auth/refresh",
                "GET /auth/profile"
            ]
        },
        "Scenario 2": {
            "Name": "Data Retrieval",
            "RPS": 1000,
            "Duration": "30 minutes",
            "Endpoints": [
                "GET /api/users",
                "GET /api/products",
                "GET /api/orders"
            ]
        }
    }
};

// Stress Testing Scenarios
const stressTestScenarios = {
    "Gradual Load Increase": {
        "Phase 1": "100 users for 10 minutes",
        "Phase 2": "200 users for 10 minutes",
        "Phase 3": "400 users for 10 minutes",
        "Phase 4": "800 users for 10 minutes",
        "Phase 5": "1600 users for 10 minutes"
    },
    "Sudden Load Spike": {
        "Normal Load": "100 users for 5 minutes",
        "Spike": "1000 users for 2 minutes",
        "Recovery": "100 users for 5 minutes"
    },
    "Resource Exhaustion": {
        "Memory Test": "Large data processing",
        "CPU Test": "Complex calculations",
        "Disk Test": "Heavy file operations",
        "Network Test": "High bandwidth usage"
    }
};

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JMeter & Performance Tools

Master Apache JMeter and other performance testing tools

Content by: Paras Dadhania

Software Testing & QA Specialist

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JMeter Test Plan Structure

•Test Plan: Root element containing all test elements
•Thread Groups: Simulate users and their actions
•Samplers: Send requests to servers
•Listeners: Collect and display test results
•Timers: Add delays between requests
•Assertions: Validate responses

JMeter Test Configuration

Code Example

// JMeter Test Plan Example
<?xml version="1.0" encoding="UTF-8"?>
<jmeterTestPlan version="1.2">
  <hashTree>
    <TestPlan testname="E-commerce Load Test">
      <elementProp name="TestPlan.arguments" elementType="Arguments">
        <collectionProp name="Arguments.arguments"/>
      </elementProp>
      <stringProp name="TestPlan.user_define_classpath"></stringProp>
      <boolProp name="TestPlan.functional_mode">false</boolProp>
      <boolProp name="TestPlan.serialize_threadgroups">false</boolProp>
    </TestPlan>
    
    <hashTree>
      <ThreadGroup testname="User Load Test">
        <stringProp name="ThreadGroup.num_threads">100</stringProp>
        <stringProp name="ThreadGroup.ramp_time">60</stringProp>
        <stringProp name="ThreadGroup.duration">1800</stringProp>
        <stringProp name="ThreadGroup.delay">0</stringProp>
        <boolProp name="ThreadGroup.scheduler">true</boolProp>
      </ThreadGroup>
      
      <hashTree>
        <HTTPSamplerProxy testname="Login Request">
          <stringProp name="HTTPSampler.domain">api.example.com</stringProp>
          <stringProp name="HTTPSampler.port">443</stringProp>
          <stringProp name="HTTPSampler.protocol">https</stringProp>
          <stringProp name="HTTPSampler.path">/auth/login</stringProp>
          <stringProp name="HTTPSampler.method">POST</stringProp>
          <stringProp name="HTTPSampler.contentEncoding">UTF-8</stringProp>
        </HTTPSamplerProxy>
        
        <hashTree>
          <HeaderManager testname="HTTP Header Manager">
            <collectionProp name="HeaderManager.headers">
              <elementProp name="" elementType="Header">
                <stringProp name="Header.name">Content-Type</stringProp>
                <stringProp name="Header.value">application/json</stringProp>
              </elementProp>
            </collectionProp>
          </HeaderManager>
        </hashTree>
      </hashTree>
    </hashTree>
  </hashTree>
</jmeterTestPlan>

// JMeter Performance Metrics
const jmeterMetrics = {
    "Response Time": {
        "Average": "Time taken for average response",
        "Min": "Fastest response time",
        "Max": "Slowest response time",
        "90th Percentile": "90% of requests faster than this",
        "95th Percentile": "95% of requests faster than this"
    },
    "Throughput": {
        "Requests per Second": "Number of requests per second",
        "Bytes per Second": "Data transfer rate",
        "Transactions per Second": "Business transactions per second"
    },
    "Error Rate": {
        "Error Percentage": "Percentage of failed requests",
        "Error Count": "Total number of errors",
        "Error Types": "Different types of errors"
    }
};

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// JMeter Test Plan Example
<?xml version="1.0" encoding="UTF-8"?>
<jmeterTestPlan version="1.2">
  <hashTree>
    <TestPlan testname="E-commerce Load Test">
      <elementProp name="TestPlan.arguments" elementType="Arguments">
        <collectionProp name="Arguments.arguments"/>
      </elementProp>
      <stringProp name="TestPlan.user_define_classpath"></stringProp>
      <boolProp name="TestPlan.functional_mode">false</boolProp>
      <boolProp name="TestPlan.serialize_threadgroups">false</boolProp>
    </TestPlan>
    
    <hashTree>
      <ThreadGroup testname="User Load Test">
        <stringProp name="ThreadGroup.num_threads">100</stringProp>
        <stringProp name="ThreadGroup.ramp_time">60</stringProp>
        <stringProp name="ThreadGroup.duration">1800</stringProp>
        <stringProp name="ThreadGroup.delay">0</stringProp>
        <boolProp name="ThreadGroup.scheduler">true</boolProp>
      </ThreadGroup>
      
      <hashTree>
        <HTTPSamplerProxy testname="Login Request">
          <stringProp name="HTTPSampler.domain">api.example.com</stringProp>
          <stringProp name="HTTPSampler.port">443</stringProp>
          <stringProp name="HTTPSampler.protocol">https</stringProp>
          <stringProp name="HTTPSampler.path">/auth/login</stringProp>
          <stringProp name="HTTPSampler.method">POST</stringProp>
          <stringProp name="HTTPSampler.contentEncoding">UTF-8</stringProp>
        </HTTPSamplerProxy>
        
        <hashTree>
          <HeaderManager testname="HTTP Header Manager">
            <collectionProp name="HeaderManager.headers">
              <elementProp name="" elementType="Header">
                <stringProp name="Header.name">Content-Type</stringProp>
                <stringProp name="Header.value">application/json</stringProp>
              </elementProp>
            </collectionProp>
          </HeaderManager>
        </hashTree>
      </hashTree>
    </hashTree>
  </hashTree>
</jmeterTestPlan>

// JMeter Performance Metrics
const jmeterMetrics = {
    "Response Time": {
        "Average": "Time taken for average response",
        "Min": "Fastest response time",
        "Max": "Slowest response time",
        "90th Percentile": "90% of requests faster than this",
        "95th Percentile": "95% of requests faster than this"
    },
    "Throughput": {
        "Requests per Second": "Number of requests per second",
        "Bytes per Second": "Data transfer rate",
        "Transactions per Second": "Business transactions per second"
    },
    "Error Rate": {
        "Error Percentage": "Percentage of failed requests",
        "Error Count": "Total number of errors",
        "Error Types": "Different types of errors"
    }
};

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Performance Metrics & Analysis

Learn key performance metrics and how to analyze test results

Content by: Yash Sanghavi

Software Testing & QA Specialist

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Key Performance Metrics

•Response Time: Time taken to process requests
•Throughput: Number of requests processed per unit time
•Concurrent Users: Number of simultaneous users
•Resource Utilization: CPU, Memory, Disk, Network usage
•Error Rate: Percentage of failed requests
•Availability: System uptime percentage

Performance Analysis Dashboard

Code Example

// Performance Metrics Dashboard
const performanceDashboard = {
    "Response Time Analysis": {
        "Average Response Time": "1.2 seconds",
        "95th Percentile": "2.8 seconds",
        "99th Percentile": "5.1 seconds",
        "Max Response Time": "12.3 seconds",
        "Status": "Within SLA (< 3 seconds)"
    },
    "Throughput Analysis": {
        "Requests per Second": "850 RPS",
        "Peak RPS": "1200 RPS",
        "Average RPS": "750 RPS",
        "Target RPS": "1000 RPS",
        "Status": "Below target"
    },
    "Resource Utilization": {
        "CPU Usage": "65% (Target: < 80%)",
        "Memory Usage": "72% (Target: < 85%)",
        "Disk I/O": "45% (Target: < 70%)",
        "Network Usage": "38% (Target: < 75%)",
        "Status": "Within limits"
    },
    "Error Analysis": {
        "Total Errors": "23",
        "Error Rate": "0.8% (Target: < 1%)",
        "4xx Errors": "15 (Client errors)",
        "5xx Errors": "8 (Server errors)",
        "Status": "Acceptable"
    }
};

// Performance Bottleneck Analysis
const bottleneckAnalysis = {
    "Database Bottlenecks": {
        "Slow Queries": "5 queries > 2 seconds",
        "Connection Pool": "85% utilization",
        "Index Issues": "Missing indexes on 3 tables",
        "Recommendations": [
            "Optimize slow queries",
            "Increase connection pool size",
            "Add missing database indexes"
        ]
    },
    "Application Bottlenecks": {
        "Memory Leaks": "2 potential leaks detected",
        "Inefficient Algorithms": "3 functions need optimization",
        "Synchronous Operations": "5 blocking operations found",
        "Recommendations": [
            "Fix memory leaks",
            "Optimize algorithms",
            "Implement async operations"
        ]
    },
    "Infrastructure Bottlenecks": {
        "Server Capacity": "CPU at 85% during peak",
        "Network Bandwidth": "75% utilization",
        "Storage I/O": "Disk queue depth high",
        "Recommendations": [
            "Scale horizontally",
            "Upgrade network capacity",
            "Optimize storage configuration"
        ]
    }
};

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// Performance Metrics Dashboard
const performanceDashboard = {
    "Response Time Analysis": {
        "Average Response Time": "1.2 seconds",
        "95th Percentile": "2.8 seconds",
        "99th Percentile": "5.1 seconds",
        "Max Response Time": "12.3 seconds",
        "Status": "Within SLA (< 3 seconds)"
    },
    "Throughput Analysis": {
        "Requests per Second": "850 RPS",
        "Peak RPS": "1200 RPS",
        "Average RPS": "750 RPS",
        "Target RPS": "1000 RPS",
        "Status": "Below target"
    },
    "Resource Utilization": {
        "CPU Usage": "65% (Target: < 80%)",
        "Memory Usage": "72% (Target: < 85%)",
        "Disk I/O": "45% (Target: < 70%)",
        "Network Usage": "38% (Target: < 75%)",
        "Status": "Within limits"
    },
    "Error Analysis": {
        "Total Errors": "23",
        "Error Rate": "0.8% (Target: < 1%)",
        "4xx Errors": "15 (Client errors)",
        "5xx Errors": "8 (Server errors)",
        "Status": "Acceptable"
    }
};

// Performance Bottleneck Analysis
const bottleneckAnalysis = {
    "Database Bottlenecks": {
        "Slow Queries": "5 queries > 2 seconds",
        "Connection Pool": "85% utilization",
        "Index Issues": "Missing indexes on 3 tables",
        "Recommendations": [
            "Optimize slow queries",
            "Increase connection pool size",
            "Add missing database indexes"
        ]
    },
    "Application Bottlenecks": {
        "Memory Leaks": "2 potential leaks detected",
        "Inefficient Algorithms": "3 functions need optimization",
        "Synchronous Operations": "5 blocking operations found",
        "Recommendations": [
            "Fix memory leaks",
            "Optimize algorithms",
            "Implement async operations"
        ]
    },
    "Infrastructure Bottlenecks": {
        "Server Capacity": "CPU at 85% during peak",
        "Network Bandwidth": "75% utilization",
        "Storage I/O": "Disk queue depth high",
        "Recommendations": [
            "Scale horizontally",
            "Upgrade network capacity",
            "Optimize storage configuration"
        ]
    }
};

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Database Performance Testing

Learn database performance testing techniques and optimization

Content by: Paras Dadhania

Software Testing & QA Specialist

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Database Performance Testing Areas

•Query Performance: Individual query execution time
•Concurrent Connections: Multiple simultaneous connections
•Data Volume: Large dataset performance
•Index Performance: Index usage and effectiveness
•Transaction Performance: ACID compliance under load
•Backup and Recovery: Data integrity and speed

Database Performance Testing Tools

Code Example

// Database Performance Testing Tools
const dbTestingTools = {
    "MySQL": {
        "mysqlslap": "Load testing tool for MySQL",
        "sysbench": "Benchmarking tool",
        "MySQL Workbench": "Performance monitoring",
        "pt-query-digest": "Query analysis tool"
    },
    "PostgreSQL": {
        "pgbench": "Built-in benchmarking tool",
        "pg_stat_statements": "Query statistics",
        "pgAdmin": "Performance monitoring",
        "EXPLAIN ANALYZE": "Query execution analysis"
    },
    "Oracle": {
        "AWR (Automatic Workload Repository)": "Performance reports",
        "ASH (Active Session History)": "Real-time monitoring",
        "SQL Tuning Advisor": "Query optimization",
        "Enterprise Manager": "Performance dashboard"
    },
    "SQL Server": {
        "SQL Server Profiler": "Query tracing",
        "Database Engine Tuning Advisor": "Index recommendations",
        "Activity Monitor": "Real-time monitoring",
        "Query Store": "Query performance tracking"
    }
};

// Database Performance Test Scenarios
const dbTestScenarios = {
    "Query Performance Test": {
        "Scenario": "Execute complex queries under load",
        "Metrics": [
            "Query execution time",
            "CPU usage per query",
            "Memory consumption",
            "I/O operations"
        ],
        "Tools": ["mysqlslap", "pgbench", "AWR"]
    },
    "Concurrent User Test": {
        "Scenario": "Multiple users executing queries simultaneously",
        "Metrics": [
            "Connection pool utilization",
            "Lock contention",
            "Deadlock occurrences",
            "Response time degradation"
        ],
        "Tools": ["sysbench", "pgbench", "LoadRunner"]
    },
    "Data Volume Test": {
        "Scenario": "Performance with large datasets",
        "Metrics": [
            "Query performance with large tables",
            "Index effectiveness",
            "Memory usage patterns",
            "Disk I/O patterns"
        ],
        "Tools": ["Custom scripts", "Database-specific tools"]
    }
};

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// Database Performance Testing Tools
const dbTestingTools = {
    "MySQL": {
        "mysqlslap": "Load testing tool for MySQL",
        "sysbench": "Benchmarking tool",
        "MySQL Workbench": "Performance monitoring",
        "pt-query-digest": "Query analysis tool"
    },
    "PostgreSQL": {
        "pgbench": "Built-in benchmarking tool",
        "pg_stat_statements": "Query statistics",
        "pgAdmin": "Performance monitoring",
        "EXPLAIN ANALYZE": "Query execution analysis"
    },
    "Oracle": {
        "AWR (Automatic Workload Repository)": "Performance reports",
        "ASH (Active Session History)": "Real-time monitoring",
        "SQL Tuning Advisor": "Query optimization",
        "Enterprise Manager": "Performance dashboard"
    },
    "SQL Server": {
        "SQL Server Profiler": "Query tracing",
        "Database Engine Tuning Advisor": "Index recommendations",
        "Activity Monitor": "Real-time monitoring",
        "Query Store": "Query performance tracking"
    }
};

// Database Performance Test Scenarios
const dbTestScenarios = {
    "Query Performance Test": {
        "Scenario": "Execute complex queries under load",
        "Metrics": [
            "Query execution time",
            "CPU usage per query",
            "Memory consumption",
            "I/O operations"
        ],
        "Tools": ["mysqlslap", "pgbench", "AWR"]
    },
    "Concurrent User Test": {
        "Scenario": "Multiple users executing queries simultaneously",
        "Metrics": [
            "Connection pool utilization",
            "Lock contention",
            "Deadlock occurrences",
            "Response time degradation"
        ],
        "Tools": ["sysbench", "pgbench", "LoadRunner"]
    },
    "Data Volume Test": {
        "Scenario": "Performance with large datasets",
        "Metrics": [
            "Query performance with large tables",
            "Index effectiveness",
            "Memory usage patterns",
            "Disk I/O patterns"
        ],
        "Tools": ["Custom scripts", "Database-specific tools"]
    }
};

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Module 6: Performance Testing

Performance Testing

Select Topics Overview

Performance Testing Types

Load Testing & Stress Testing

JMeter & Performance Tools

Performance Metrics & Analysis

Database Performance Testing

Performance Testing Types

Load Testing & Stress Testing

JMeter & Performance Tools

Performance Metrics & Analysis

Database Performance Testing

Performance Testing Types

Performance Testing Categories

Performance Testing Objectives

🎯 Practice Exercise

Load Testing & Stress Testing

Load Testing Process

Load Testing Scenarios

🎯 Practice Exercise

JMeter & Performance Tools

JMeter Test Plan Structure

JMeter Test Configuration

🎯 Practice Exercise

Performance Metrics & Analysis

Key Performance Metrics

Performance Analysis Dashboard

🎯 Practice Exercise

Database Performance Testing

Database Performance Testing Areas

Database Performance Testing Tools

🎯 Practice Exercise

Module 5: API Testing & Web Services

Module 7: Mobile Testing & Cross-Platform

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