Performance testing is crucial for building efficient, reliable, and scalable software applications. However, it comes with its own set of challenges, ranging from test infrastructure issues and high test execution times to inconsistent test environments. These challenges can be categorized into several areas, including unrealistic test scenarios or inadequate test data, high setup time and maintenance overhead, limited scalability of test infrastructure, bottlenecks in load generation, version drift between environments, insufficient collaboration between teams, lack of continuous performance testing in CI/CD pipelines, poor monitoring and logging during tests, time and budget constraints, improper workload modeling, overlooking system and test script errors, neglecting to test under peak load conditions, executing tests in production environments, and selecting inappropriate performance testing tools. To overcome these challenges, teams can adopt solutions such as proper requirement analysis, involving stakeholders, creating realistic test scenarios, using enough test data, leveraging AI-native cloud test orchestration platforms like HyperExecute, optimizing infrastructure setup, running performance tests with multiple regions, promoting collaboration between teams, integrating continuous performance testing into CI/CD pipelines, implementing effective monitoring and logging systems, managing time and budget constraints, improving workload modeling, analyzing system and test script errors, testing under peak load conditions, avoiding production environment execution, and selecting the right tools for performance testing.