The DevOps approach to software production aims to produce better software at a faster pace by utilizing short, narrowly focused release cycles and by fostering close collaboration between developers and operations staff. DevOps metrics provide a measure how effective DevOps teams and processes are. These metrics can be tied to the quality of software in development as revealed by testing. Other DevOps metrics can be linked to frequency of releases, the frequency and severity of problems in live applications, and mean time to repair (MTTR) for production issues.
Digital transformation solutions such as those offered by Dynatrace seek to extend and improve DevOps metrics specifically with an eye toward helping DevOps teams produce high-performing applications. For example, Dynatrace application dependency mapping tools automatically discover and map the entire topologies of your applications in development and test environments, with automatic detection of changes from build to build. These automated application mapping tools provide valuable insight into application performance hotspots and potential bottlenecks, early in the application lifecycle—when the fixes may be faster and easier than they would be later in production.
Improve DevOps metrics using Dynatrace artificial intelligence
Dynatrace is the leader in digital performance management for DevOps and continuous delivery. Its application performance management technology incorporates artificial intelligence algorithms that help to automate the monitoring of application performance and analysis of performance issues resulting in improved DevOps efficiency and DevOps metrics.
Dynatrace's application performance monitoring solutions integrate with IDEs, build servers, and test automation suites to analyze the performance impact of each check-in and each build, providing a rich source of performance-oriented DevOps metrics. Through the Dynatrace dashboard, performance infographics based on these DevOps metrics are available for developers, testers, and architects, with support for drilling down into any tier and any point in a call stack.
Once applications are live, Ops teams can use Dynatrace to proactively detect any performance problems. Dynatrace leverages its native artificial intelligence capabilities to automatically determine the baseline behavior of your application—taking into account variables such as time of day or day of the week. Dynatrace alerts Ops teams to performance anomalies or regressions and automatically conducts root cause analysis. Results of the automated root cause analysis can be packaged and shared with developers and testers to speed problem resolution and minimize any impact on end users.
Integrate Dynatrace with DevOps tools to improve DevOps metrics
A major goal of DevOps is to increase deployment frequency with low failure rates. This is especially useful for cloud deployments where continuous deployment is a necessity. To aid in increasing deployment frequency and to improve DevOps metrics, Dynatrace cloud performance management tools can be integrated with continuous integration and continuous delivery tools as well as with IDEs. Dynatrace can be used with JUnit, NUnit, Selenium, JMeter, SoapUI, Gatling, MSTest, Jenkins, Bamboo, Team Foundation Server, Team City, Eclipse, Visual Studio, and many others.
Integrating Dynatrace with these tools yields many benefits. For example, integrating with an IDE can stop bad code commits, and offer one-click instrumentation and performance metrics generation from your IDE. Combined with other Dynatrace tools like Azure monitoring tools for cloud application monitoring, you can greatly improve the qualify of your code and introduce efficiencies into your DevOps pipeline.
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