![]() ![]() Test automation and continuous integration (CI) Additionally, the performance management teams that rely on APM solutions will also be able to view NeoLoad performance test results in their dashboards, eliminating user access control configuration and training requirements, since every consumer of performance data can do so in their preferred solution. This integration allows testers to correlate test data with real-time performance metrics, providing insights for optimization and ensuring that performance issues are addressed proactively. Integrating NeoLoad with APM tools like Datadog, Dynatrace, or AppDynamics enables continuous monitoring of application performance and helps identify bottlenecks. Performance monitoring and Application Performance Monitoring (APM) integration It can also integrate with container orchestration tools like Kubernetes to monitor the impact of container scaling and deployments on application performance. NeoLoad supports testing in containerized and microservices-based applications by enabling the creation of realistic load tests that focus on individual components and their interactions. Containerization and microservicesĪs applications adopt containerization and microservices architectures, performance testing needs to adapt to these new environments. While NeoLoad itself does not provide IaC capabilities, it can be integrated with IaC tools like Terraform, Ansible, and Puppet, allowing performance testers to execute load tests against different versions of an application in a repeatable and version-controlled manner. ![]() IaC enables automated setup and configuration of testing environments, ensuring consistency and reducing the likelihood of human errors. NeoLoad supports cloud-based load testing by seamlessly integrating with cloud platforms like AWS, Azure, and Google Cloud, allowing testers to create dynamic infrastructure for performance testing to generate load from various geographic locations and simulate large numbers of virtual users without investing in expensive hardware. Cloud-based testingĬloud-based testing enables scalable and cost-effective solutions for performance testing by leveraging cloud resources. This helps make performance testing more efficient and accurate, while eliminating the need to examine results that do not contain substantive performance degradation. ![]() NeoLoad leverages AI-driven algorithms to automatically detect regressions in performance over time, giving insight to performance experts on where they should be applying their time and skills. Artificial intelligence and machine learningĪrtificial intelligence (AI) and machine learning (ML) can enhance performance testing processes by automating test case generation, detecting anomalies, and providing predictive analytics. ![]() For instance, using the NeoLoad Command Line Interface (CLI), developers can create and execute performance tests during the development phase, allowing them to identify bottlenecks and optimize code before it reaches the testing or production stages. Shift-left testing involves integrating performance testing earlier in the software development life cycle (SDLC), enabling teams to identify and address performance issues during the design and development phases.
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