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From PC Break/Fix to CloudMASTER®
https://www.linkedin.com/in/stevendonovan It was late 2011 and Steven Donovan was comfortable working at SHI International Corporation, a growing information technology firm, as a personal computer break/fix technician. His company had been…
Is Data Classification a Bridge Too Far?
Today data has replaced money as the global currency for trade. “McKinsey estimates that about 75 percent of the value added by data flows on the Internet accrues to “traditional”…
Vendor Neutral Training: Proven Protection Against Cloud Horror Stories
Cloud computing is now entering adolescence. With all the early adopters now swimming in the cloud pool with that “I told you so” smug, fast followers are just barely beating…
Cognitive Business: When Cloud and Cognitive Computing Merge
Cloud computing has taken over the business world! With almost maniacal focus, single proprietors and Board Directors of the world’s largest conglomerates see this new model as a “must do”.…
Government Cloud Achilles Heel: The Network
Cloud computing is rewriting the books on information technology (IT) but inter-cloud networking remains a key operational issue. Layering inherently global cloud services on top of a globally fractured networking…
System Integration Morphs To Cloud Service Integration
Cloud Service Brokerage is changing from an industry footnote toward becoming a major system integration play. This role has now become a crucial component of a cloud computing transition because…
Networking the Cloud for IoT – Pt 3 Cloud Network Systems Engineering
Dwight Bues & Kevin Jackson (This is Part 3 of a three part series that addresses the need for a systems engineering approach to IoT and cloud network design. Networking the Cloud for IoT –…
Networking the Cloud for IoT – Pt. 2 Stressing the Cloud
Dwight Bues & Kevin Jackson This is Part 2 of a three part series that addresses the need for a systems engineering approach to IoT and cloud network design. Part…
Networking the Cloud for IoT – Pt. 1: IoT and the Government
Dwight Bues & Kevin Jackson This is Part 1 of a three part series that addresses the need for a systems engineering approach to IoT and cloud network design:…
Parallel Processing and Unstructured Data Transforms Storage
(This post originally appeared on Direct2Dell, The Official Dell Corporate Blog) Enterprise storage is trending away from traditional, enterprise managed network-attached storage (NAS) and storage area networks (SAN) towards a…
As cloud computing becomes the information technology mainstream, data center technology is accelerating at a breakneck speed. Concepts like software define infrastructure, data center analytics and Nonvolatile Memory Express (NVMe) over Fabrics are changing the very nature of data center management. According to industry research firm IDC, organizations will spend an additional $142.8 billion oninfrastructure for both public and private cloud environments in the next three years (2016-2018) to boost efficiency and business agility.
- Investing in the ecosystem to accelerate enterprise-ready, easy-to-deploy software defined infrastructure (SDI) solutions;
- Optimizing SDI solutions to deliver highly efficient clouds across a range of workloads by taking full advantage of Intel platform capabilities; and
- Aligning the industry and engaging the community through open industry standards, solutions and routes to market to accelerate cloud deployment.
As cloud infrastructure management is moving towards these new management paradigms, those at the leading edge are exploring how to make data center’s think for themselves. Industry leaders like Dr. Brian Womack, Director of Distributed Analytics Solutions in Intel’s Data Center Solutions Group, and Das Kamhout, Senior Principal Engineer at Intel are learning how to use data, artificial intelligence frameworks and machine learning to create data centers that think for themselves. Two key components of their vision are SNAP and TAP.
- Empowering systems to expose a consistent set of telemetry data;
- Simplifying telemetry ingestion across ubiquitous storage system;
- Improving the deployment model, packaging and flexibility for collecting telemetry;
- Allowing flexible processing of telemetry data on agent (e.g. machine learning); and
- Providing powerful clustered control of telemetry workflows across small or large clusters.
Visit Chip Chat to hear more more about creating a data center that thinks for itself! |
This content is being syndicated through multiple channels. The opinions expressed are solely those of the author and do not represent the views of GovCloud Network, GovCloud Network Partners or any other corporation or organization.
( Thank you. If you enjoyed this article, get free updates by email or RSS – © Copyright Kevin L. Jackson 2016)
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