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240305 ||| eng |
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|a TK7895.M4
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|a Gupta, Paresh
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|a Detecting, troubleshooting, and preventing congestion in storage networks
|c Paresh Gupta, Edward Mazurek
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| 260 |
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|a San Jose, CA
|b Cisco Press
|c 2024
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| 300 |
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|a 736 pages
|b illustrations
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| 505 |
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|a Includes bibliographical references and index
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| 653 |
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|a Computer storage devices / http://id.loc.gov/authorities/subjects/sh85029541
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| 653 |
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|a Computer storage devices / fast
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| 653 |
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|a Réseaux d'ordinateurs
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| 653 |
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|a Ordinateurs / Mémoires
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| 653 |
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|a Computer networks / fast
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| 653 |
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|a Computer networks / http://id.loc.gov/authorities/subjects/sh85029513
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|a Mazurek, Edward
|e author
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| 041 |
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|a eng
|2 ISO 639-2
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| 989 |
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|b OREILLY
|a O'Reilly
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|z 9780137887231
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|z 013788723X
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| 856 |
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|u https://learning.oreilly.com/library/view/~/9780137887279/?ar
|x Verlag
|3 Volltext
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|a 331
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|a 004.5
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|a The complete practical guide to architect storage networks for maximum efficiency, and to quickly troubleshoot congestion issues. Data is the most important entity in a data center. In addition to being stored securely for the long term, data must be accessible to applications with low latency so that high performance can be maintained 24/7. To meet this performance goal of applications, the storage infrastructure services must be designed accordingly. In Detecting, Troubleshooting, and Preventing Congestion in Storage Networks, leading Cisco experts take a practical approach to explaining the congestion handling mechanisms of the transport technologies like FC, FCoE, RoCE, and TCP. The authors share proven troubleshooting methodology developed through years of firsthand experience as well as analytical techniques for monitoring the st rage fabrics and gaining predictive insights. Through real-world experiences and case study examples, youll learn what questions to ask, how to start planning, what exists today, what components still must evolve, and how to drive value in building custom applications in detecting congestion in large-scale storage networks. Optimize user experience with faster resolution of congestion in storage networks in production data centers Master congestion handling mechanisms in technologies like FC, FCoE, RoCE, and TCP Applicable to networks connected to all storage array types and vendors including Dell, HPE, IBM, NetApp, Hitachi Real-world case studies and troubleshooting methodology ensuring storage SLAs are consistently met Increase uptime with custom analytical tools for predicting and resolving congestion Boost storage infrastructure efficiency in a hybrid cloud model Save on employee training and reduce support ticket hassles with vendors
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