NetApp data mechanics buy latest move to optimize hybrid cloud

NetApp on Tuesday extended its cloud capabilities with the acquisition of cloud analytics and technology developer Big Data Data Mechanics to better leverage the growing use of Apache Spark analytics in conjunction with NetApp’s Ocean Kubernetes DevOps technology and its Spot technology to optimize cloud computing.

NetApp has also extended its Ocean technology with new continuous delivery as a way to automate the application delivery process from development to production.

With Data Mechanic, NetApp continues to expand beyond its roots as a storage vendor to embrace new technologies to improve cloud workload optimization, said Amiram Shachar, vice president and Managing Director of Spot by NetApp.

[Related: NetApp Leans Hard Into Hybrid Cloud With New Ontap, FlexPod as a Service]

12 months ago, NetApp acquired Spot, a developer of technology to manage and optimize compute in public clouds, to target cloud-native businesses beyond storage, Shachar said.

“We are now focusing on continuous optimization in the cloud,” Shachar told CRN. “We are now operating in several areas with Spot. There is a lot of interest in containers and Kubernetes to modernize applications and launch new services.

Two and a half years ago, NetApp also released Ocean, an automation and optimization technology that allows customers to run containers without having to manage their infrastructure, Shachar said.

“Ocean is a DevOps suite for Kubernetes in the cloud that starts with automation to help customers run containers without virtual machines,” he said. “Everything that is needed for infrastructure as a service, Ocean provides. It’s completely serverless.

On top of that, Ocean adds optimization for storage and compute resources, with algorithms to place workloads into the right infrastructure in an optimized way, Shachar said.

“This ensures that Kubernetes is running in the most efficient location,” he said. “For example, think of two apps that talk to each other a lot. Ocean sees this and moves the applications so that they are close to each other to reduce communication costs. “

Data Mechanics adds to this to ensure that Ocean and Spot optimize big data and data analytics for Apache Spark workloads, Shachar said.

“Ocean takes care of the infrastructure, while Data Mechanics takes care of the application,” he said. “It looks at every running task in a Spark cluster, collects information as it runs, and then automates those resources for the next run. So a task that can take four hours can normally run in less than 40 minutes the next time, or a 60-minute task can run in 10 minutes. Data Mechanics really understands what jobs need in terms of compute and storage and makes those resources available.

Data Mechanics is tailor-made for Apache Spark, which has become the second most common workload in Kubernetes, Shachar said. The most common workload is web services from various vendors. “But Spark is the biggest platform running on Kubernetes,” he said.

Future versions could be rolled out to other big data platforms, including Kafka and Elasticsearch, but it’s still early days to say for sure, Shachar said.

Data Mechanics is the perfect acquisition for NetApp to increase the reach of some of its other technologies, including Spot, said John Woodall, vice president of western engineering at General Datatech, a Dallas-based solutions provider and partner of long-term distribution of NetApp.

NetApp recently introduced Spot Wave, which focuses on automating the compute layer for cloud applications, Woodall told CRN. Wave is compatible with Apache Spark to automatically scale resources and deploy the app, he said.

“Data mechanics logically sits above Spot to do Spark automation and dynamic resource allocation,” he said. “It optimizes the provisioning of resource usage and costs over time for applications running on Spark. “

NetApp has a clear focus on hybrid clouds and on optimizing data services and cloud resources for Kubernetes, Woodall said.

“But NetApp is still doing cloud storage,” he said. “So on the compute and application side, everything can now be stored on NetApp storage on the top three hyperscalers. Big data workloads require value for money to facilitate their provisioning. And that seems to be the point.

With NetApp, customers get Spot Wave for infrastructure optimization, including compute resources and optimization, and Data Mechanics is adding automated operations for applications, especially Spark, said Woodall.

“So now a workload – Spark – can be optimized across multiple dimensions,” he said.

Data mechanics is something NetApp can use immediately to add value to customer engagements, Shachar said.

“We already have customers on board Ocean and Data Mechanics,” he said.

As for NetApp Ocean, NetApp on Tuesday introduced Ocean CD, or Continuous Delivery.

Ocean was originally developed to provide continuous operations, but is now in the process of transitioning to continuous delivery, Shachar said.

“Customers now write code, review it and send it to continuous integration for testing, then send it to servers,” he said. “It’s all ‘automated’, but it’s still a manual process. The customer deploys the application, then examines metrics and logs and checks with users, then deploys other versions.

Ocean CD changes that, Shachar said.

“Ocean CD has automated these manual interventions,” he said. “It’s very Kubernetes focused. Ocean CD automatically detects when a new application is deployed to Kubernetes and monitors all events. Customers start with a pre-deployed strategy. For example, apps can be deployed one after the other at two-minute intervals, or deploy half now and half later. That’s a big, big part of modernizing applications.

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