Modern-day engineering teams rely on continuous integration and continuous delivery (CI/CD) providers, such as GitHub Actions, GitLab, and Jenkins to build automated pipelines and testing tools that enable them to commit and deploy application code faster and more frequently.
Zendesk provides support teams with an integrated solution for processing all types of customer inquiries and feedback. But as organizations scale, support tickets multiply, making it increasingly difficult to parse all of your customers’ feedback and time-consuming to investigate issues. Customers often report issues without providing the detailed context needed for troubleshooting, creating unclear and indirect paths to remediation.
In Java applications, concurrency issues can be difficult to reproduce and debug. Because work is scheduled nondeterministically across threads, the conditions that have led to an error in one execution of the program may not trigger the same issue the next time around. Exceptions that are silently handled—also known as swallowed exceptions—can also be challenging to debug because they typically do not leave any trace in the logs.
Datadog Workflow Automation speeds up incident response and remediation for DevOps, SRE, and security teams by enabling them to automatically run predefined task sequences whenever specific alerts or security signals are triggered. After the feature’s initial release in 2023, Datadog is now excited to announce a significant expansion of its Workflow Automation capabilities with Azure actions, allowing engineers to create automated workflows for their Azure resources for the first time.
Your applications are only as powerful as they are iterable. To keep up with their rapidly changing production environments, your teams need reliable CI/CD systems that implement best practices—including build and test automation, flaky test management, and deployment management. By optimizing their CI/CD pipelines, your teams can build their apps more efficiently, deploy them more safely, and catch bugs and security vulnerabilities before they make it to production.
