Electric Cloud, the leader in Adaptive Release Orchestration and Continuous Delivery, announced a new predictive analytics solution, ElectricFlow DevOps Foresight. DevOps Foresight applies machine learning algorithms to the massive amounts of data generated by tool chains to develop a risk score metric that predicts the outcomes of releases before they head into production. Taking predictive analytics even further, it will also illustrate where to improve pipelines based on developer influence, code complexity influence, etc.

ElectricFlow DevOps Foresight provides DevOps teams with the necessary steps to eliminate further sources of “release anxiety” by having clearer insight into existing development practices and release patterns. Now, bottlenecks and inefficiencies throughout the software delivery process are easier to find and correct. The ability to understand resource allocation for new and complex application and environment requirements also helps ensure the best path toward successful software releases.

To arrange a demo of ElectricFlow DevOps Foresight, visit http://electric-cloud.com/solutions/devops-foresight/

Based on deep insights into past patterns of success and failures, DevOps Foresight predicts the likelihood of a release’s success. Much like a credit score, the creation of a release’s risk score numerical value is based on developer, code and environment profiles and gives stakeholders an easy, visual way to interpret the likelihood of success for a particular build or pipeline. If the score is high, DevOps teams can look at those profiles to determine what, specifically within those profiles, is driving up the risk.

In order to illustrate areas for improving the pipeline, DevOps Foresight looks at contributing factors and what has helped to improve them in the past, and will suggest appropriate changes in teams, code or environments. Managers will be able to proactively answer questions like:

  • Are we going to finish our release on time?
  • Can we move faster or can we do more?
  • Will this release cause more or less quality issues?
  • What’s the likelihood of a production deployment failure?

“Electric Cloud long established great ways for its customers to gain insights into releases that are moving through the pipeline, but it’s been a challenge for organizations to understand the risks of releases before they’re finalized or even started,” said Carmine Napolitano, CEO of Electric Cloud. “Improving the pipeline is often based on trial and error or best guesses. What we aim to do with ElectricFlow DevOps Foresight is provide data-driven insights much earlier in the process by looking at past successes, build complexity, author profiles and more, and then show where the pipeline can be improved based on facts. I’m proud to say the team at Electric Cloud has built a tool that can save our customers hundreds of hours of work and relieve unnecessary release anxiety for each and every product they deliver.”


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