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Cloud Migration Part 2: Classify your data
In my first post of this series, “Cloud migration part one: An overview,” I provided a high-level summary of how enterprises should migrate applications to the cloud. In this installment,…
Could Budget Sweeps Fix Your Cybersecurity Problem?
A recent roundtable discussion in Washington, DC with Federal IT and Cyber leaders focused on the business drivers, challenges and evolving strategies around cybersecurity in government. After an opening presentation…
Cloud Migration Part 1: An Overview
Cloud Migration Part One: An Overview Business is all about efficiency and effectiveness. In today’s world, however, those twin goals almost always lead to cloud migration. This anecdotal observation…
A Personal Technology for Good Redux: Call for Code
In 2013 I had the opportunity to manage a $2M demonstration of how cloud computing could be used to support natural disasters. In that NCOIC Geospatial Community Cloud (GCC) demonstration,…
A Path to Hybrid Cloud
Cloud computing is now an operational reality across every industry. Organizations that fail to leverage this economic, operational and technology consumption model are merely consigning themselves to irrelevance. The rapid…
Human-Led Collaboration with Machines
When charged with managing large and complex efforts, an overarching project management task is risk assessment. It involves documenting the current situation, comparing it to the past, and understanding the…
Sensomorphic
240 million results are returned in 1.06 seconds (as of May 28, 2018) when you search for cloud computing in a Google search. With that much information available, and that many…
Artificial Intelligence and the Project Manager
Organizations use teams to create wealth, market share, customer service, competitive advantage, and organizational success. Effective teams accomplish their assigned end goals by engaging in collaboration as a joint learning…
Building A Collaborative Team
Recently, Harvard Business Review cited some insightful research into team behavior at 15 multinational companies. It found that although these teams tended to be large, virtual, diverse, and composed of…
Welcome the New Project Manager!
According to CIO.com, the six traits of highly effective project managers are: Be a strategic business partner who can offer higher-level strategic leadership skills, not just technical management skills, provide…
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)
Cloud Computing
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