Category: Test case documentation – QA

Challenges in Cloud-Native Testing Complexity: The distributed nature of cloud-native applications can make testing more complex, requiring specialized knowledge and tools. Environment Parity: Ensuring test environments accurately mirror production can be challenging due to the dynamic nature of cloud resources. Tool Integration: Integrating various testing tools and frameworks into CI/CD pipelines can require significant effort… Continue reading Challenges in Cloud-Native Testing

Neural network testing involves evaluating a neural network model to ensure it performs correctly and meets its intended goals. This process includes several key aspects: Validation and Testing Datasets: Neural networks are typically trained on one dataset and tested on separate validation and testing datasets. This helps ensure that the model generalizes well to new,… Continue reading Neural Network Testing

Benefits of Cloud-Native Testing Efficiency and Speed: Testing is integrated into the development process, enabling faster identification and resolution of issues. Scalability: Cloud-native testing can scale to match the size and complexity of the application, leveraging cloud resources. Cost-Effectiveness: Dynamic environments and on-demand resources help optimize costs by only using what’s needed. Realistic Testing Conditions:… Continue reading Benefits of Cloud-Native Testing

Cloud-Native Testing refers to the practice of testing applications that are designed, built, and deployed using cloud-native principles. Cloud-native applications are typically built with a focus on scalability, flexibility, and resilience, leveraging cloud platforms, microservices architecture, containers, and continuous integration/continuous deployment (CI/CD) pipelines. Key Characteristics of Cloud-Native Testing Testing in a Cloud Environment: Cloud-native testing… Continue reading Cloud-Native Testing