Load testing is a crucial component of software performance testing that evaluates how applications behave under expected user loads. By simulating traffic with virtual users, it assesses system performance during normal and peak conditions to minimize the risk of failures during releases, updates, and daily operations.
Key types of load testing include:
• Scalability Testing: Determines the application’s ability to handle increased load, ensuring it can scale efficiently to meet growing demand.
• Stress Testing: Examines system robustness by pushing it beyond normal load limits to identify breaking points and how it recovers from failures.
• Endurance Testing: Tests system performance over an extended period under a significant load to uncover issues like memory leaks and performance degradation.
• Capacity Testing: Identifies the maximum load an application can handle without compromising performance, helping to establish resource requirements and system limits.
Prominent load testing tools are:
• JMeter: An open-source tool recognized for its flexibility in performance testing.
• LoadRunner: An enterprise-level solution offering multiprotocol support for comprehensive load testing needs.
• PFLB: An AI-powered SaaS platform providing advanced load testing capabilities to meet complex performance requirements to ensure stability and responsiveness during high traffic.
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User Statistics
User statistics refer to data related to user behavior, interactions, or demographics within a particular system. This data is typically stored in various analytics platforms, logs, and databases (DBMS). It is highly valuable for creating accurate load profiles for systems that are already in operation, helping to inform performance testing and optimization efforts.
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