New Software Solution Hewlett Packard Enterprise Delivers Greater Flexibility and Lower Cost for Kubernetes Deployments of Cloud-Native and Non-Cloud-Native Applications on Bare-Metal or Virtualized Infrastructure, in Their Data Centers, on Any Cloud, or at the Network Edge
Hewlett Packard Enterprise announced that the HPE Container Platform, unveiled in November 2019, is now generally available. The Hewlett Packard Enterprise Container Platform is the industry’s first enterprise-grade container platform designed to support both cloud-native and non-cloud-native applications using 100 percent open source Kubernetes – running on bare-metal or virtual machines (VMs), in the data center, on any public cloud, or at the edge. In addition, Hewlett Packard Enterprise is introducing new professional services to ensure faster time-to-value and several new reference configurations for data-intensive application workloads such as AI, machine learning, deep learning (DL), data analytics, edge computing, and Internet of Things (IoT).
Many organizations started their container journey with stateless workloads that are easier to transition to a cloud-native microservices architecture. However, the majority of business applications today are monolithic, stateful, and non-cloud-native workloads that live throughout the enterprise. Organizations seek to modernize and containerize these applications without significant refactoring – while ensuring production-grade security and persistent data storage. While some early on-premises Kubernetes deployments used containers with VMs, this approach is no longer necessary. Running containers on bare-metal provides significant advantages to organizations seeking to modernize and run containers at scale in the enterprise. These include: reducing unnecessary overhead, avoiding lock-in with a proprietary virtualization format, and eliminating “vTax” licensing costs.
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The HPE Container Platform dramatically reduces cost and complexity by running containers on bare-metal, while providing the flexibility to deploy in VMs or cloud instances. This allows businesses to embrace a hybrid cloud or multi-cloud approach to deploying Kubernetes with enterprise-class security, performance, and reliability. Organizations seeking greater cost savings, efficiency, utilization, and application performance can eliminate the need for virtualization and expensive hypervisor licenses, by running containers directly on bare-metal infrastructure.
Additional advantages of the Hewlett Packard Enterprise Container Platform and bare-metal containers include:
- Speed. Deploying and running containerized applications on bare-metal is faster. There’s no need to start up the guest operating system (OS) of the VM, including a full boot process; this speeds development, operations, and time-to-market.
- Reduction in cost and resources. Since each VM has its own guest OS, eliminating it reduces the RAM, storage and CPU resources—and the associated data center costs—required to sustain it.
- Elimination of an orchestration layer. There’s no need to have a management framework for a virtualized environment and a Kubernetes orchestration environment for containers.
- Increased density per hardware platform. Run more containers on a given physical host than VMs, by eliminating multiple copies of guest OSes and their requirements for CPU, memory, and storage.
- Better performance for applications that require direct access to hardware. Analytics and artificial intelligence (AI) workloads with machine learning (ML) algorithms require heavy computation to train the ML models; these applications will deliver faster results and higher throughput on bare-metal.
Built on proven innovations from HPE’s recent acquisitions of BlueData and MapR, the HPE Container Platform is an integrated turnkey solution with BlueData software as the container management control plane and the MapR distributed file system as the unified data fabric for persistent storage.
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“With the HPE Container Platform, GM Financial has deployed containerized applications for machine learning and data analytics running in production in a multi-tenant hybrid cloud architecture, for multiple use cases from credit risk analysis to improving customer experience,” said Lynn Calvo, AVP of Emerging Data Technology at GM Financial.
“The next phase of enterprise container adoption requires breakthrough innovation and a new approach,” said Kumar Sreekanti, senior vice president and chief technology officer of Hybrid IT at HPE. “Our HPE Container Platform software brings agility and speed to accelerate application development with Kubernetes at scale. Customers benefit from greater cost efficiency by running containers on bare-metal, with the flexibility to run on VMs or in a cloud environment.”
“We’re leveraging the innovations of the open source Kubernetes community, together with our own software innovations for multi-tenancy, security, and persistent data storage with containers,” continued Sreekanti. “The new HPE Container Platform is designed to help customers as they expand their containerization deployments, for multiple large-scale Kubernetes clusters with use cases ranging from machine learning to CI / CD pipelines.”
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Commitment to open source
Hewlett Packard Enterprise is actively engaged in the Cloud Native Computing Foundation and Kubernetes community, with open source projects such as KubeDirector. A key component of the HPE Container Platform, KubeDirector provides the ability to run non-cloud-native monolithic applications (i.e., stateful applications with persistent storage) on Kubernetes. HPE’s recent acquisition of Scytale for cloud-native security underscores its commitment to the open source ecosystem, with ongoing contributions to open source projects, including Secure Production Identity Framework for Everyone (SPIFFE) and SPIFFE Runtime Environment (SPIRE).
Use case-specific reference designs
The software uniquely addresses the requirements for enterprise containerization deployments across a wide range of application use cases, including data-intensive application workloads such as AI, machine learning, deep learning (DL), data analytics, edge computing, and Internet of Things (IoT). HPE is aligning its hybrid IT portfolio of products and services to support these use cases and enhance the capabilities of the HPE Container Platform. The new reference designs provide best-practice blueprints for workload-optimized configurations on HPE infrastructure.1 These include AI, ML, DL, and data analytics workloads running on HPE Apollo; edge analytics and IoT workloads on HPE Edgeline; and DevOps workloads and CI / CD pipelines on HPE Synergy. The HPE Container Platform also works with storage solutions such as HPE Cloud Volumes and the HPE Container Storage Interface (CSI) Driver for hybrid cloud deployments with Kubernetes.
New professional services
HPE Pointnext Services provides expert advisory, deployment, training, and support services for containerization. New design, implementation, and operational services for the HPE Container Platform will help customers to accelerate their containerization strategy, de-risk enterprise adoption of containerization, and assure faster time-to-production.
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