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Mesosphere Kubernetes Engine Brings Breakthrough Automation & Efficiency for Data-Driven Apps on Multi-Cloud & Edge

Mesosphere, the multi-cloud automation platform company, announced the general availability of Mesosphere Kubernetes Engine (MKE), Mesosphere DC/OS 1.12 and the public beta of Mesosphere Jupyter Service (MJS). Mesosphere Kubernetes Engine is the only software platform that delivers pure Kubernetes-as-a-Service on multi-cloud and edge with high-density resource pooling, yet without the need for virtualization. DC/OS 1.12 adds improvements to secure multi-cloud operations, performance at scale and real-time operational visibility. MJS simplifies delivery of Jupyter Notebooks, popular with data scientists, to streamline how they build and deliver AI-enabled services.

Driven by demand from enterprise customers, like GE Transportation and Two Sigma, Mesosphere 1.12 was developed to help businesses adopt enterprise standards across any infrastructure, while empowering developers and data scientists. 

Companies need to move fast to stay relevant in today’s competitive landscape. To do this, IT teams are leveraging leading tools such as Kubernetes, Jupyter Notebooks, advanced security and software registries to drive software innovation,” said Florian Leibert, Mesosphere CEO. “By natively integrating Kubernetes and Jupyter into DC/OS, we’re able to deliver fast deployment and centralized management for businesses to readily adopt the latest enterprise technologies across any infrastructure, while still enabling experimentation and providing developer choice.”

Secure and Consistent Operations for Kubernetes and Data Across Multi-Cloud, Datacenter and Edge

Mesosphere DC/OS 1.12 gives IT organizations the security and control to operate edge and multi-cloud infrastructures from a single control plane. With MKE, enterprise IT can centralize scattered Kubernetes clusters on multiple cloud providers managed from a single platform. With MJS, organizations can accelerate data science initiatives with on-demand data science notebooks securely hosted from general-purpose infrastructure. Enterprises can easily scale Jupyter deployments as their data science teams grow.

With DC/OS 1.12, Mesosphere continues to advance its modern hybrid cloud enterprise IT platform,” said Rhett Dillingham, vice president & senior analyst with Moor Insights & Strategy. “Kubernetes and Jupyter Notebooks are two of the most important emerging technologies, and their tight integration within DC/OS substantially helps data engineers with implementation and deployment.”

With MKE, MJS and DC/OS 1.12, enterprise customers receive the following benefits:

  • Pure Kubernetes-as-a-Service on any Infrastructure: A central control plane for complete lifecycle automation of multiple Kubernetes clusters, including different versions, stretched across clouds or datacenters. Up to 50% infrastructure cost savings from reducing cluster sprawl with high-density multi-Kubernetes pooling, no virtualization required.
  • On-Demand Data Science Environment: Data scientists get instant access to the Jupyter Notebooks interactive computing environment, preconfigured with all the tools they need to be productive. MJS also eliminates the need for dedicated gateway infrastructures for analytics and model training by using shared general-purpose infrastructure without resource contention.
  • Complete Edge and Multi-Cloud Management: Operators and developers get a consistent, secure and scalable experience on any infrastructure. Private Package Registry enables IT to empower DevOps and Data Science teams, while maintaining IT control of available services on cloud or completely disconnected datacenters.

Data science and machine learning are the future of enterprise innovation, but many data sets are too large to fit on laptops or individual work stations. This forces data scientists and engineers working with Jupyter Notebooks to repeatedly work with smaller data sets, constraining progress and increasing the risk of data leaks.

While many enterprise IT innovation budgets are focused on enabling data science and machine learning, the ecosystem of open source tools that support these platforms is fragile and extremely difficult to configure for the enterprise,” said David Palaitis, engineering manager, Two Sigma. “We partnered with Mesosphere to build a custom solution for deploying and managing Jupyter notebooks for our modelers and are pleased to see it’s now available to any customer through MJS.”

 

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