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Keeping the Peace in the Modern Data Center

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Following the evolution curve of infrastructure performance management, whereby most legacy data centers sprung up with multiple vendors and disparate and dispersed assets, the challenge to gaining a ‘single source of truth’ for performance management analytics have only become harder, especially as service assurance models demand end-to-end visibility to end-user quality of experience.

How, then, is a virtualization systems administrator expected to “keep the peace,” if you will, across multiple layers of data centers, networking, storage, compute, application and cloud infrastructures?

Here are the eight-great questions to ask as you evaluate whether virtualization management tools provide true cross-silo visibility and service assurance analytics to avoid the IT blame game and eliminate finger pointing altogether:

1. How much do outages and latency really cost you in time?
2. What are the operating costs for remote site tech support?
3. What are the intangible costs from customer dissatisfaction?
4. Do you really have the most scalable infrastructure tools?
5. How do you prove where and when the problems actually occur?
6. How can you consolidate multiple silo-based tools?
7. What will allow you to successfully provision VDI services?
8. Wouldn’t it be great to troubleshoot problems before my users do!

Read our blog for more information:

http://blog.xangati.com/news/keeping-the-peace-in-the-modern-data-center/

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Keeping the Peace in the Modern Data Center

  1. 1. Keeping the Peace in the Data Center August 19, 2015 Atchison Frazer VP-Marketing
  2. 2. SaaS apps driving requirements for cross-silo data intelligence for hybrid-cloud environments NOW: Hybrid-Cloud Infrastructure Workload flexibility and server cost reduction expectations measured by productivity gains Virtualization Always on high availability infrastructure and connectivity measured by continuous uptime Internet Powerful microcomputers measured by capital equipment and power/management cost reductions Client-Server Demand for Big Data and storage-intensive apps, e.g., Internet video, measured by uptime and low latency Converged Hot swap systems and thin- client virtualization functionality measured by expandable capacity Mainframe 2010’s: Converged 2000’s: Virtualization 1990’s: Internet 1980’s: Client-Server 1970’s: Mainframe Evolution of the Data Center & Performance Metrics
  3. 3. Xangati Virtual Infrastructure Performance Topology Download a free trial: http://xangati.com/downloads/

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