D2iQ Delivers on Generative AI Promise to Simplify Kubernetes

D2iQ this week made available a tool that leverages generative artificial intelligence (AI) to make managing Kubernetes clusters more accessible to a wider range of IT professionals with varying skill levels.

Available with version 2.6 of the D2iQ Kubernetes Platform (DKP), the DKP AI Navigator has been trained using documentation created by D2iQ. The tool enables IT professionals to use a natural language interface to launch queries that surface, for example, recommendations for how best to configure a Kubernetes cluster.

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In addition, version 2.6 provides an update to the technology preview of DKP Insight, a service through which DKP provides access to a tool for tracking the status of Kubernetes clusters, including any vulnerabilities that cybercriminals might exploit. Any D2iQ customer can now use DKP Insight to create a quarterly report that describes the status of their Kubernetes clusters and outlines suggested remediations for any issue discovered.

D2iQ also provides support for Podman containers from Red Hat to enable rootless provisioning of Kubernetes clusters, support for the Amazon Web Services (AWS) Elastic Container Registry (ECR), enhanced monitoring of Kubernetes clusters deployed at the network edge and the ability to ensure D2iQ’s control plane is always highly available.

Finally, D2iQ has added support for customizable banners that can be used to add information such as system classification and company brand and logos.

Dan Ciruli, vice president of product for D2iQ, said one of the issues limiting widespread adoption of Kubernetes is the level of expertise required to manage it. Tools such as DKP AI Navigator and DKP Insight lower the skill requirement for successfully managing fleets of Kubernetes clusters, he added.

When it comes to furthering adoption, the issue most complex platforms encounter is that available documentation is overly complex, noted Ciruli. Generative AI tools make it simpler for IT professionals of varying skill levels to manage platforms such as Kubernetes clusters without having to wade through arcane documentation, he said.

As more Kubernetes clusters are deployed in production environments, the skills gap that currently exists is becoming a more acute issue. IT organizations need to be able to rely on IT administrators to manage Kubernetes clusters simply because there is not enough available DevOps expertise to programmatically manage this platform using YAML files.

More challenging still, most clusters are running different versions of Kubernetes that are often based on different distributions provided by various IT vendors. Kubernetes updates are released three times a year, but IT teams are reluctant to upgrade because a deprecated application programming interface (API) that is no longer available might prevent an application that depends on that API from continuing to run, noted Ciruli.

It’s not clear if there might ever be a long-term release (LTR) of Kubernetes that would help minimize that disruption. In the meantime, however, the need to streamline the management of Kubernetes clusters in production environments is definitely becoming a more pressing concern.