Dimensional Data

NetApp this week extended its alliance with Microsoft to now include its CloudOps portfolio of tools for optimizing cloud computing environments. Previously, the alliance between the two companies focused on data management but is now expanding to include tools to deploy workloads, improve performance and reduce costs using machine learning algorithms across both instances of virtual machines and the Azure Kubernetes Service (AKS). Kevin McGrath, vice president of Spot by NetApp, said in more challenging economic times, there’s a lot more focus on programmatically reining cloud costs using FinOps best practices within the context of a DevOps workflow. Organizations are also starting to create platform engineering teams to more efficiently manage DevOps workflows at scale across hybrid cloud computing environments, he added. For years, developers have been provisioning cloud infrastructure resources with little to no oversight. Unfortunately, developers are also prone to over-provision infrastructure resources to ensure maximum application availability. Many of those infrastructure resources never wind up being consumed by the application, so the cost of cloud computing winds up becoming inflated. IT leaders are also being increasingly required to make sure cloud costs are more predictable. Sudden spikes in consumption resulting in higher monthly bills are an unwelcome surprise to finance teams that are now required to manage costs more closely. Ongoing advances in artificial intelligence (AI) should make it easier to predict costs across highly dynamic cloud computing environments. Navigating all the pricing options that cloud service providers make available is challenging. IT teams need to clearly understand the attributes of each workload to ensure optimal usage of cloud infrastructure resources. Less clear is the degree to which IT teams are pitting cloud service providers against one another. Pricing across the cloud services that most organizations use today is fairly consistent. Most organizations that deploy workloads in the cloud tend to run the bulk of them on the same service because they lack the internal expertise needed to manage multiple clouds equally well. There may be some workloads running on additional clouds, but enterprise licensing agreements reward customers for running more workloads on a cloud. The only way to really optimize cloud spending is to shift workloads to less expensive tiers of service that might only be available for a relatively limited amount of time. One way or another, the management of cloud computing is finally starting to mature. As the percentage of workloads that organizations have running in the cloud steadily increases, IT teams are becoming more adept at both maximizing application performance and the associated return on investment (ROI). Each IT organization will need to decide for itself how best to manage cloud computing environments as it continues to build and deploy cloud-native applications alongside legacy monolithic applications running on virtual machines, but NetApp is betting the need for tools such as CloudOps will increase as cloud computing environment become more complex. The challenge, as always, is finding and retaining the talent needed to manage cloud computing environments when every other organization is looking for that same expertise.