clusters

Customers began to approach hosting provider SysEleven about running containers and using container orchestration. To offer their customers the highest quality services for which they are known, they sought an easy to use container orchestra- tion solution. SysEleven chose to partner with Loodse to create MetaKube, a white label of Loodse’s Kubermatic Container Engine, giving their customers Kubernetes clusters in one click. Simon Pearce, MetaKube Team Lead and Systems Architect at SysEleven, explains why they chose Kubermatic to run Kubernetes in their data centers.

Headquartered in Chicago, Bean Suntory owns over 70 premium spirit brands from whiskey and rum, to vodka, cognac, tequila, and gin. Beam Suntory generates $4 billion in annual revenues. But that revenue was in danger. The company’s production software, Wonderware, which controls embedded systems driving almost every critical production process, was underpinned by ageing hardware. If it failed, production would come to a grinding—and expensive—halt.Every hour of downtime results in lost production, which can amount to millions of dollars in losses,” says Sanjay Kirtikar, Director Digital Technologies, Beam Suntory. To ensure Wonderware never failed, Beam Suntory implemented hyperconverged clusters integrated with Nutanix Enterprise Cloud Platform software The results were instant and outstanding. Beam Suntory expects a 25-35% cost benefit from lower support and maintenance efforts, and a 50% reduction in power usage.

Data is a truly inexhaustible resource for an organization. It creates endless possibilities to make data do more. As a technology partner of hundreds of organizations around the world, Infosys helps clients navigate the journey from their current state to the next. Facilitating clients’ transition into data-native enterprises is a crucial part. To understand how companies are using data analytics today and their expectations in a world of endless possibilities with data, we recently commissioned an independent survey of 1,062 senior executives from organizations with annual revenues exceeding US$ 1 billion, in the United States, Europe, Australia, and New Zealand. The respondents were from business and technology roles, who were decision makers, program managers and external consultants; represented 12 industries, grouped into seven industry clusters, such as, consumer goods, retail and logistics, energy and utilities, financial services and insurance, healthcare and life sciences, h

Download the full paper to learn more about how XTREME-Stargate offers a “super head node” for HPC cloud clusters

This start-up guide provides instructions on how to configure the Dell™ PowerEdge™ VRTX chassis with Microsoft® Windows Server® 2012 in a supported failover cluster environment. These instructions cover configuration and installation information for chassis-shared storage and networking, failover clustering, Hyper-V, Cluster Shared Volumes (CSV), and specialized requirements for Windows Server 2012 to function correctly with the VRTX chassis.

A start up guide to Paul Marquardt Building Microsoft Windows Server 2012 Clusters on the Dell PowerEdge VRTX.

This paper presents the results of a three-year total cost of ownership (TCO) study comparing Dell EMC™ VxRail™ appliances and an equivalent do-it-yourself (DIY) solution of standalone server hardware and software from the VMware vSAN ReadyNode™ (hardware compatibility list) configurations. For both options, we modeled total hardware capital expense, total software capital expense and operational expense for small, medium and large clusters over a three-year period.

Identifying the benefits, costs, and risks associated with an Isilon implementation, Forrester interviewed several customers with experience using Isilon. Dell EMC Isilon is a scale-out NAS platform that enables organizations to store, manage, and analyze unstructured data. Isilon clusters are composed of different node types that can scale up to 68 petabytes (PB) in a single cluster while maintaining management simplicity. Isilon clusters can also scale to edge locations and the cloud

This white paper discusses the concept of shared data scale-out clusters, as well as how they deliver continuous availability and why they are important for delivering scalable transaction processing support.

IBM Compose Enterprise delivers a fully managed cloud data platform on the public cloud of your choice - including IBM SoftLayer or Amazon Web Services (AWS) - so you can run MongoDB, Redis, Elasticsearch, PostgreSQL, RethinkDB, RabbitMQ and etcd in dedicated data clusters.

The Cray® CS300-LC™ liquid-cooled cluster supercomputer combines system performance and power savings, allowing users to reduce capital expense and operating costs. The Trend Toward Liquid Cooling Recent IDC surveys of the worldwide high performance computing (HPC) market consistently show that cooling today's larger, denser HPC systems has become a top challenge for datacenter managers. The surveys reveal a notable trend toward liquid cooling systems, and warm water cooling has emerged as an effective alternative to chilled liquid cooling.

As wattages increase in high-density server racks, providing redundant power becomes more challenging and costly. Traditionally, the most practical solution for distributing redundant power in 208V server racks above 5 kW has been to connect dual 3-phase rack PDUs to dual power supplies in each server. Although this approach is reliable, it negates a rewarding system design opportunity for clustered server applications. With their inherent resilience and automated failover, high-availability server clusters will still operate reliably with a single power supply in each server instead of dual power supplies. This streamlined system design promises to reduce both capital expenditures and operating costs, potentially saving thousands of dollars per rack. The problem is that dual rack PDUs can’t distribute redundant power to a single power supply. An alternative approach is to replace the dual PDUs with an automatic transfer switch (ATS) connected to a single PDU, but perfecting an ATS tha

Did you know that majority of the respondents in a recent survey identified digital skillset (57%), senior leadership commitment (50%), and change management (42%) areas as the most important success factors for digital transformation? Infosys commissioned an independent survey of over 1,000 senior management level executives from organizations with annual revenues over US$ 1 billion to understand the impact of digital disruption on their organizations and how they were dealing with it. Three clusters emerged from the survey findings, based on the business objectives behind their digital transformation initiatives- Visionaries, Explorers, and Watchers. The survey provides valuable insights into how organizations can evolve from being watchers and explorers to visionaries. Key findings from the report that you can use to charter your digital future: Visionaries target higher order business objectives, such as new business models and culture, from digital transformation, while explore

Managing the Economics of Your Virtualized Data Center The average datacenter is 50% more costly than Amazon Web Services. As cloud economics threaten the long-term viability of on premise data centers, the survival of IT organizations rests solely in the ability to maximize the operational and financial returns of their existing infrastructure. You will survive, and this brand new whitepaper will help you to follow these 4 best practices: - Maximize the efficiency of your virtual data center. - Optimize workload placement within your clusters. - Reclaim unused server capacity. - And show your boss that this saves money.

Learn why NetApp Open Solution for Hadoop is better than clusters built on commodity storage. This ESG lab report details the reasons why NetApp's use of direct attached storage for Hadoop improves performance, scalability and availability compared to typical internal hard drive Hadoop deployments.

Connections are great. Having a network to connect to is even better. Humans have been connecting, in one form or another, throughout history. Our cities were born from the drive to move closer to each other so that we might connect. And while the need to connect hasn’t changed, the way we do it definitely has. Nowhere is this evolution more apparent than in business. In today’s landscape, business is more virtual, geographically dispersed and mobile than ever, with companies building new data centers and clustering servers in separate locations. The challenge is that companies vary hugely in scale, scope and direction. Many are doing things not even imagined two decades ago, yet all of them rely on the ability to connect, manage and distribute large stores of data. The next wave of innovation relies on the ability to do this dynamically.

A new approach, known as “Big Workflow,” is being created by Adaptive Computing to address the needs of these applications. It is designed to unify public clouds, private clouds, Map Reduce-type clusters, and technical computing clusters. Download now to learn more.

In a multi-database world, startups and enterprises are embracing a wide variety of tools to build sophisticated and scalable applications. IBM Compose Enterprise delivers a fully managed cloud data platform so you can run MongoDB, Redis, Elasticsearch, PostgreSQL, RethinkDB, RabbitMQ and etcd in dedicated data clusters.

For IT departments looking to bring their AIX environments up to the next step in data protection, IBM’s PowerHA (HACMP) connects multiple servers to shared storage via clustering. This offers automatic recovery of applications and system resources if a failure occurs with the primary server.

In this Gigaom Research webinar, the panel will discuss how the multi-cluster approach can be implemented in real systems, and whether and how it can be made to work. The panel will also talk about best practices for implementing the approach in organizations.

IBM Platform HPC Total Cost of Ownership (TCO) tool offers a 3-year total cost of ownership view of your distributed computing environment and savings that you could potentially experience by using IBM Platform HPC in place of competing cluster management software.

View this demo to learn how IBM Platform Computing Cloud Service running on the SoftLayer Cloud helps you: quickly get your applications deployed on ready-to-run clusters in the cloud; manage workloads seamlessly between on-premise and cloud-based resources; get help from the experts with 24x7 Support.

This video explains how IBM Platform Computing is transforming isolated clusters and grids into flexible, dynamic high performance private, hybrid and public clouds.

This industry analyst report describes important considerations when planning a Hadoop implementation. While some companies have the skill and the will to build, operate, and maintain large Hadoop clusters of their own, a growing number are choosing not to make investments in-house and are looking to the cloud. In this report Gigaom Research explores: • How large Hadoop clusters behave differently from the small groups of machines developers typically use to learn • What models are available for running a Hadoop cluster, and which is best for specific situations • What are the costs and benefits of using Hadoop-as-a-Service With Hadoop delivered as a Service from trusted providers such as Altiscale, companies are able to focus less on managing and optimizing Hadoop and more on the business insights Hadoop can deliver.

Want to get even more value from your Hadoop implementation? Hadoop is an open-source software framework for running applications on large clusters of commodity hardware. As a result, it delivers fast processing and the ability to handle virtually limitless concurrent tasks and jobs, making it a remarkably low-cost complement to a traditional enterprise data infrastructure. This white paper presents the SAS portfolio of solutions that enable you to bring the full power of business analytics to Hadoop. These solutions span the entire analytic life cycle – from data management to data exploration, model development and deployment.