As the “race to embrace” Kubernetes unfolds, major “hyperscalers” such as Microsoft Azure, Google Cloud and Amazon AWS have provided their users’ services to deploy and manage them. They are portals for easier management, pre-built templates, cloud portability, and more agile processes within a cloud structure. Respectively, they are referred to as Azure Kubernetes Services, Google Kubernetes Engine, and Elastic Kubernetes Service. These services provide low-cost playgrounds for developers to generate secure platforms in the cloud and change customer end user experience with fewer overhead costs and without interruption. In some ways, the services mimic the agile and seamless foundation that Kubernetes provides a developer where the customer and end user receive faster, bug-free outputs.
During everyday activities that consumers enjoy including ordering coffee to go, hailing an Uber, using Instacart for grocery shopping or monitoring a delivery; somewhere there are unseen applications running these tasks. With agility and mobile application development “on the fly”, data protection and data management tools enable faster, more trustworthy ways to span updates to the edge without disruption. While there are many use case examples of cloud development, Dell Technologies’ PowerProtect Data Manager provides the momentum to finish the race.
Dell Technologies Data Manager supports all three services mentioned; AKS, GKE and EKS. The infrastructure is made up of Data Manager on-premises or in the public cloud and PowerProtect DD Virtual Edition as storage or their storage disks as target(s). By having DD Virtual Edition as a target it creates an extension of flexibility for the administrators to protect clusters from an on-premises storage disk, hosted on the service instance in the public cloud. In addition to the rich service features that are provided by the end platforms, all the enterprise-features are additionally accessible via Data Manager. These extra features include policy creation, application consistency, cluster restores between clusters, and self-service. With multi-cloud models of development, developers can simply deploy applications in a cloud that provides the best services for the application; AWS RDS (Relational Database Service) and Google ML libraries are such examples. Orchestration comes in through management on-premises and connecting Kubernetes clusters to seamlessly migrate the data between clusters powered by DD Virtual Edition at the cloud target; thereby achieving a true multi-cloud experience wherein YOU the consumer meet SLAs in record setting timeframes!
