Microsoft’s Azure Kubernetes Service (AKS) officially has a new “Automatic” option designed to ease the configuration, optimization, and usability of the hyperscaler’s Kubernetes-based AKS platform.

Brendan Burns, corporate VP for Azure Compute at Microsoft and co-founder of the Kubernetes open source project while at Google, explained in a blog post that the newly automated AKS removes the “Kubernetes tax.” This is viewed as the overhead required to deploy and manage Kubernetes as a container management platform.

Burns noted that AKS Automatic eliminates this overhead with an “easy mode” for clusters that includes best-practice defaults and guardrails to simplify configurations and operations; offloading day-two operations of maintaining the control plane, tuning node pools, patching systems, handling upgrades, and scaling; and embedding a hardened security default configuration with automated patching and monitoring.

This easy mode is enabled by pre-selected features, including Azure Container Networking Interface (CNI); Azure Linux nodes; the Kubernetes-based event-driven autoscaling (KEDA) platform; automated node provisioning from the open-source Karpenter project; Microsoft’s Entra ID integration for authentication, role-based access control (RBAC), and network policies; and Azure Monitor for logs and metrics.

This acts as an “opinionated experience that abstracts away from infrastructure complexity, while keeping the full power of Kubernetes at your fingertips.”

The platform basically looks to tackle growing cloud-native and containerization within organizations that is driving increased complexity, a notion that is accelerating with AI-leaning applications. The Futurum Group earlier this year released results from an enterprise survey that found 63% of respondents had deployed AI, machine learning (ML), or generative AI workloads on Kubernetes.

That surge feeds into the Kubernetes tax.

“If Kubernetes has an Achilles’ Heel to continue large-scale adoption, complexity wins the day,” the Futurum Group’s Mitch Ashley wrote. “Kubernetes has succeeded to this point despite the criticism about its learning curve and complexity, particularly for very large multicluster, multicloud installations.”

Vendors have targeted this Kubernetes complexity challenge with various higher-level platform-as-a-service (PaaS) offerings that may use Kubernetes as a foundation but attempt to extract configuration challenges.

Purnima Padmanabhan, VP and GM of Broadcom’s Tanzu Division, recently told SDxCentral that Tanzu’s focus is not on a Kubernetes underlay, but is “all about making it easier for customers to run their applications regardless of infrastructure.”

Padmanabhan likened Tanzu to Google’s Cloud Run as opposed to broader Kubernetes-based platforms like Google’s Kubernetes Engine (GKE), Red Hat, or VMware’s own Kubernetes Service (VKS).

“Tanzu just provides you the app and data platform,” Padmanabhan said. “If you want PaaS or you want code-to-production, you go with the Tanzu platform.”

Feeds into Microsoft’s Kubernetes base

Despite the simplicity push, AKS Automatic does still allow for modifications. This includes access to the Kubernetes API, the kubectl command-line interface (CLI), and integration with existing continuous integration, continuous deployment (CI/CD) pipelines.

Burns noted that the new offering is built on upstream open-source Kubernetes and remains conformant with Cloud Native Computing Foundation (CNCF) standards. AKS Automatic also integrates with Microsoft’s other cloud-native tools like Azure Arc, and comes on the heels of Microsoft updating its Azure Container Storage platform.

Microsoft has been lauded for its cloud-native platform support.

Gartner recently labeled the hyperscaler as one of the “leaders” in container management and cloud-native application platforms, though the research firm did note Microsoft’s breadth of offerings can cause confusion.

“For example, deciding between Container Apps and Azure Kubernetes Service (AKS), or running containers on Azure Functions can be confusing, as each service is designed for different use cases and operational models,” Gartner noted in the cloud-native application platform ranking. “But these distinctions are not readily apparent.”