New @georgeacrump Blog: Designing Shared Storage for Hadoop, Elastic, Kafka, TensorFlow

As analytics environments like Hadoop, Elastic, Kafka and TensorFlow continue to scale, organizations need to find a way to create a shared infrastructure that can deliver the bandwidth, flexibility, and efficiency that these environments need. In a recent Storage Intensity podcast, Tom Lyon, founder and chief scientist of DriveScaleand George Crump, Lead Analyst of Storage Switzerland, sat down…

New @georgeacrump Blog: Silos of Clusters - Is this the End Result of Data Center Modernization?

Applications like Elastic, Hadoop, Kafka and TensorFlow typically operate on scale-out architectures built from dozens, if not hundreds of servers, which act as nodes in the application’s cluster. Many organizations now use a mix of these applications to derive the outcomes they need to be productive. Data centers today increasingly consist of a growing number of these clusters but with limited…

Get The Latest @georgeacrump eBook: Hyperscale Performance, Is NVMe Enough?

Hyperscale architectures that support Elastic, Hadoop, and Kafka, often vary wildly between organizations and even within each organization. Each workload often needs its own cluster and IT teams are constantly trying new technology within those clusters, trying to improve performance. The combination of workload specific clusters and an endless pursuit of high-performance often creates very…

Latest @georgeacrump eBook: What is a Cloud-Like Storage Experience for On-Premises Applications?

The public cloud is often described as “just a business model” that provides organizations with the ability to pay for storage and compute resources as they need them. If that were true then the public cloud providers could be easily replaced by a leasing package. The reality is there is more to the success of the public cloud than just how it is paid for. In the cloud, IT is able to “create”…

Latest @klmacomber Blog: DriveScale Composable Infrastructure: Elastic and Efficient Resources for Modern Workloads

Modern workloads such as Hadoop, Kafka and machine learning are demanding in terms of the volume of data that must be processed, the speed at which that data much be processed, and the fact that their capacity and performance requirements are both variable and unpredictable. They require a blend of performance, adaptable capacity, flexibility in configuration and cost-efficiency obtained through…

Latest @klmacomber Blog: Kaminario Drives Composable Storage 2.0

Accelerated performance and usage-based storage for business critical applications

A new generation of composable infrastructurethat is truly software-only is required to deliver the levels of multi-cloud data mobility, automation, efficiency and flexibility, which are required by modern workloads. These solutions enable the independent transfer of software licenses across underlying hardware,…

New Post has been published on http://www.thessdreview.com/daily-news/latest-buzz/toshiba-announces-xg6-p-nvme-ssd-industrys-most-advanced-flash-node-and-up-to-2tb-of-capacity-computex-2019-update/

Toshiba Announces XG6-P NVMe SSD – Industry's Most Advanced Flash Node and up to 2TB of Capacity-- Computex 2019 Update

Latest @georgeacrump Blog: Is NVMe Enough for Efficient Hyperscale Data Centers?

Hyperscale architectures typically sacrifice resource efficiency for performance by using direct attached storage instead of a shared storage solution. That lost efficiency though, means the organization is spending money on excess compute, graphics processing units (GPUs) and storage capacity that it doesn’t need. Some organizations are looking to Non-volatile Memory Express over Fabric…