CloudBees today launched a software-as-a-service (SaaS) platform for centralizing the management of multiple DevOps environments, including GitHub, GitLab and the open source Jenkins continuous integration/continuous delivery (CI/CD) platforms.
Company CEO Anuj Kapur said CloudBees Unify extends the reach of CloudBees beyond Jenkins and will enable DevOps and platform engineering teams to centrally manage application development environments more easily via a control plane for CI/CD platforms through which DevOps teams can govern and manage multiple platforms.
Fragmented DevOps toolchains are a disservice to organizations because, in addition to slowing down the pace of application development, they also increase total costs, noted Kapur.
Some DevOps teams are trying to address that issue by standardizing on a single platform. However, application developers want to be able to innovate using the tools they prefer. CloudBees Unify provides a way to streamline DevOps workflows and processes while continuing to enable developers to work with any tool they prefer, said Kapur.
CloudBees Unify, in effect, provides an operating layer on top of any existing toolchain, based, for example, on GitHub Actions, he added. That capability makes it possible to both surface analytics in real time, run tests and apply policies that enforce running code scans and implement compliance policies, noted Kapur.
It’s not clear how many organizations are centralizing the management of DevOps workflows, but the rise of artificial intelligence (AI) tools for writing code will soon force the issue, said Kapur. The sheer volume of code moving through DevOps pipelines will soon reach levels that will be impossible to manage without relying on increased automation, he added. As the cost of writing code increasingly approaches zero in the age of AI, many DevOps teams will be simply overwhelmed, he added.
Each organization will need to determine for itself to what degree it may want to centralize the management of DevOps, but it’s not uncommon for enterprise IT organizations to have multiple different platforms performing the same essential functions. Each of those teams adopted DevOps practices at varying times, with each one often making different tooling and platform decisions. However, it soon becomes apparent that acquiring and deploying multiple tools and platforms requires levels of integration that, over time, increase the total cost of application development and deployment.
It’s not clear to what degree AI is being applied to application development, but a recent Futurum Research report found 41% of respondents expect generative AI tools and platforms will be used to generate, review and test code, while 39% plan to make use of AI models based on machine learning algorithms. The one certain thing is that as AI tools are more pervasively adopted across the software development lifecycle, the overall pace of application development is only going to further accelerate.
Regardless of how any DevOps team moves forward, the one thing to remember is that more code doesn’t always directly translate to more applications being deployed without revisiting how pipelines constructed for a different era need to be either replaced or re-engineered.
