Nutanix has added several features to its Cloud Platform focused on accelerating Kubernetes adoption. These include broad support for leading Kubernetes container platforms, and various infrastructure capabilities, such as enhanced code and data services for applications. With these features, DevOps teams can streamline application delivery, while customers can control their IT costs.
The platform, with the embedded AHV hypervisor, is now compatible with most Kubernetes container platforms, such as Amazon EKS-A. This is based on an ecosystem that includes Red Hat OpenShift, SUSE Rancher, Google Anthos, and Microsoft Azure Arc for edge deployments. All of this is coupled with Nutanix’s native Kubernetes, Nutanix Kubernetes Engine (NKE).
The company also has updated a family of APIs, and its SDKs, in Java, JS, Go and Python. Yes, this novelty is still in development. This will allow for large-scale automation and consistent operations regardless of location: data center, public cloud, or edge.
The Nutanix Cloud Platform’s architecture at scale allows you to start small and scale later, based on business needs, to multi-PB sized deployments. This platform is the only one that unifies the delivery of integrated data services with file and object services, and now also with database services for Kubernetes-based applications.
In this sense Nutanix has launched Database Service Operator for Kubernetes, a service that allows developers to quickly provision and attach databases to their applications, directly from development environments. The open source operator can be downloaded from artifacthub.io and GitHub.
Additionally, Nutanix Objects now supports a reference implementation of the Container Object Storage Interface (COSI). This way you can streamline self-service orchestration and provisioning. It has also added observability support, for which it uses Prometheus, and Objects is validated with analytics applications like Presto, Dremio, and Vertica. These, along with Confluent Kafka, enable efficient large-scale data pipelines, often used in streaming applications.
According to Thomas Cornely, Vice President of Product Management at Nutanix«Kubernetes deployments are inherently dynamic and difficult to manage at scale. Running Kubernetes container platforms cost-effectively at scale requires a developer-ready infrastructure that seamlessly adapts to changing requirements.”
