Abstract: According to examples, an apparatus may include a processor that may generate automated and dynamic fail-fast testing pipelines that are efficiently executed to quickly identify tests for which changes to components such as an application will likely fail. The processor may train a classifier to predict whether changes to the application will fail a test procedure and use the classifier to generate machine-learned predictions of test outcomes to generate failure probabilities. The testing pipeline may be dynamically re-ordered based on the failure probabilities. The processor may also group the test procedures into lifecycle stages. Historical performance data may be used to identify time-limits by which to complete the test procedures of each lifecycle stage. Thus, the generated dynamic testing pipelines may be generated based on the likelihood of failures and test procedure duration.

Abstract: According to examples, an apparatus may include a processor that may generate automated and dynamic fail-fast testing pipelines that are efficiently executed to quickly identify tests for which changes to components such as an application will likely fail. The processor may train a classifier to predict whether changes to the application will fail a test procedure and use the classifier to generate machine-learned predictions of test outcomes to generate failure probabilities. The testing pipeline may be dynamically re-ordered based on the failure probabilities. The processor may also group the test procedures into lifecycle stages. Historical performance data may be used to identify time-limits by which to complete the test procedures of each lifecycle stage. Thus, the generated dynamic testing pipelines may be generated based on the likelihood of failures and test procedure duration.

Abstract: Examples disclosed herein relate to automated development operations (DevOps) application deployment. Some examples disclosed herein may include generating a DevOps application deployment packages for DevOps applications based on DevOps application models for deploying the DevOps applications. Application deployment tools for deploying the DevOps applications may be determined based on the DevOps application deployment packages. The DevOps application deployment packages may be provided deployment tool plugins associated with the determined application deployment tools and the deployment tool plugins may execute deployment operations based on deployment properties included in the DevOps application deployment packages to deploy DevOps applications using the determined application deployment tools.