When it comes to managing your team’s access and permissions to cloud environments, it’s important to grant the right permissions to your users—no less and no more than they need. Different teams can require different levels of access, for example cloud budget managers and users will require different permissions than the DevOps engineers who are operating and managing the cloud on a daily basis.

With our recent announcement regarding the general availability of Ocean for Azure Kubernetes Service (AKS), I decided to migrate one of our production services. The service was already running on AKS, but will now be managed by Spot’s Ocean for AKS. TL;DR: The results are pretty cool, as I was able to cut 82% out of the existing spending for this AKS cluster. You can see the results in the screen capture below.

Ocean automates cloud infrastructure for containers. It continuously analyzes how your containers are using infrastructure, automatically scaling compute resources to maximize utilization without sacrificing availability. Ocean shuffles workloads and then scales down underutilized nodes to ensure everything runs at the lowest cost.

Since becoming part of NetApp, we have increasingly been asked by customers how Spot’s optimization technology could be extended to their cloud storage resources to help them use storage more efficiently, reducing costs and eliminating waste.

Jupyter Notebook is a web-based interactive computational environment for creating notebook documents. It supports programming languages – such as Python, Scala, R – and is largely used for data engineering, data analysis, machine learning, and further interactive, exploratory computing. Think of notebooks like a developer console or terminal, but with an intuitive UI that allows for efficient iteration, debugging or exploration.

When Apache Spark introduced native support for Kubernetes it was a game changer for big data. Speed, scale and flexibility are now at the fingertips of data teams—-if they can master Kubernetes. It’s an uphill climb for even experienced DevOps teams. At Spot by NetApp, we’ve seen first-hand the challenges that companies are facing as they navigate the complexities of operating large-scale Kubernetes applications.

Running Apache Spark applications on Kubernetes has a lot of benefits, but operating and managing Kubernetes at scale has significant challenges for data teams. With the recent addition of Ocean for Apache Spark to Spot’s suite of Kubernetes solutions, data teams have the power and flexibility of Kubernetes without the complexities. A cloud-native managed service, Ocean Spark automates cloud infrastructure and application management for Spark-on-Kubernetes.

The Azure Marketplace is one of the best ways to add complementary applications and services to your cloud solution, and makes it easy to onboard and adopt new solutions. It can also help centralize your Azure cloud financial commitments in one place with Azure billing.

As a premium autoscaler for containers and Kubernetes applications, Spot Ocean automatically and continuously executes scaling actions based on the requests and specified constraints of pods and specific containers. This container-driver autoscaling approach is core to how Ocean leverages and optimizes the compute infrastructure required to run containers in the cloud.

As a managed data plane service for containerized applications, Spot Ocean provides a severless experience for running containers in the cloud. Ocean integrates with the control plane of your choice, and handles key areas of infrastructure management, from provisioning compute and autoscaling, to pricing optimization and right-sizing. A core component of Ocean’s architecture is the Ocean controller, which is how Ocean and your Kubernetes cluster integrate and interact.