Komodor Extends Kubernetes Management Reach to IDPs
Komodor this week revealed it has integrated its platform for managing Kubernetes clusters with internal developer portals (IDPs), starting with the open source Backstage and the proprietary Port platform.
Company CTO Itiel Shwartz said that integration will extend the reach of the Klaudia artificial intelligence (AI) agents that Komodor has embedded in its platform to address issues that application developers experience when building and deploying cloud-native applications.
Most of those issues are relatively routine and can now be addressed directly from within the same IDP that a DevOps or platform engineering team has set up to enable application developers to self-service their own requirements within the context of a set of guardrails and best practices they have defined and implemented.
The overall goal is to provide developers with detailed instructions for resolving issues without requiring them to have deep Kubernetes expertise, said Shwartz. It also provides insights into service health status, configuration drift, costs, service dependencies and other issues that might be adversely affecting applications.
In the absence of being able to access these AI agents, application developers wind up escalating trivial issues to IT operations teams that should be more focused on resolving more complex issues or deploying new applications, said Shwartz.
IDPs are at the core of an effort to embrace platform engineering, a methodology for centralizing the management of DevOps workflows in a way that promises to increase developer productivity while also reducing costs. A survey of 326 software engineering leaders conducted by Futurum Research finds that adoption of platform engineering is gaining significant traction.
More than a quarter of respondents (26%) have mastered platform engineering, compared to 41% who are still working toward applying platform engineering across multiple projects. Another 24% are still working toward operationalizing a set of best practices for platform engineering, while 7% are just getting started. Metrics being used to track whether platform engineering teams are successful include developer productivity (64%), fewer security incidents or failures (62%), software release frequency (59%), developer satisfaction (58%), reduction of costs (50%) and reduced complexity (29%).
Because Kubernetes defines a standard set of application programming interfaces (APIs), there is a high amount of correlation between adoption of platform engineering and Kubernetes, noted Shwartz. Many organizations in the wake of recent change to VMware licensing terms made by Broadcom are also investigating the degree to which Kubernetes provides a viable alternative for running legacy applications, he added.
It’s not clear to what degree IT teams are adopting platforms infused with AI tools to manage Kubernetes clusters. Arguably, adoption of Kubernetes is being held back by the level of expertise required to successfully manage these platforms. Kubernetes is simultaneously one of the most powerful and one of the most complex platforms to find mainstream adoption in the enterprise. IT organizations appreciate the ability to dynamically scale resources up and down, but many IT professionals are also intimidated by the number of settings that need to be correctly configured. Adding to that complexity are add-ons such as IDPs that in many cases are just as or more complex to manage than Kubernetes itself.
Hopefully, as management platforms such as Komodor provide a layer of abstraction that makes Kubernetes environments more accessible to both IT administrators and DevOps engineers, it’s only a matter of time before there is more Kubernetes adoption than ever.
