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Cisco ACI Fabric Simplifies and Flattens Data Center Network

On July 18th, Cisco IT turned on the first deployment of Application Centric Infrastructure (ACI) fabric at its engineering data center in San Jose. By using ACI fabric to simplify and flatten the data center network, we can reduce network operating costs as much as 55 percent and incident management roughly 20 percent. Take a peek at the ACI fabric inside our engineering data center:  Read More »

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Announcing Cisco Tidal Enterprise Scheduler (TES) 6.2


Introducing New Adapter for Cisco UCS Manager, Lightweight Java Client, Multi-domain AD/LDAP Authentication & Runtime User Support for TES Workgroups   

Managing and automating mission-critical business process is key to the success of your enterprise. By managing the delivery of the right data to the right application at the right time you can ensure that everyone in your organization has the information they need to be successful.

UntitledEnd-to-end Workload Management with Tidal Enterprise Scheduler (TES) 6.2

With the release of TES 6.2, Cisco continues its leadership in workload automation (WLA) and job scheduling. With hundreds of in-production customers, running complex workloads for global trading exchanges, manufactures, health care providers and technology companies, Cisco TES has proven itself in some of the most demanding data centers in the world.

Already known and cited by analysts and customers for its ease-of-use, ease-of-installation, scalability and enterprise-wide visibility, Cisco TES 6.2 ships with major performance enhancements, added user management flexibility and greater infrastructure management reach. Enhancements in this release include:

Adapter for Cisco UCS Manager
The Enterprise Adapter for UCS Manager allows users to schedule UCS Manager component infrastructure jobs through Cisco TES so that users can leverage the scheduler’s capabilities to automate, simplify, and improve job scheduling and workload performance. The UCS Manager Adapter integrates with UCS Manager using the XML API and provides for the automation of UCS Manager activities for blade and rack-mount server management in the form of UCS Manager jobs. This allows you to control and manages server instances as part of an overall infrastructure and data processing workload management solution.

Untitled1Job Definitions for Cisco UCS Manager

Lightweight Java Client
For power users who are managing thousands of workloads and their associated objects in their database, the Java client syncs data directly from the Master, but it is many times faster than the client manager because all data is stored in-memory on the Java VM rather than to an external database. Many interactions through the Java client will see marked increases in performance including smooth scrolling with zero latency and faster search and filtering.

Untitled2Lightweight Java Client for TES 6.2

Flexible Security Feature
For large enterprises that segment globally or for any user who creates domains for their data center, Cisco TES now supports multi-domain coverage from a single client manager allowing greater flexibility and ease of use. And for greater runtime flexibility, Cisco TES allows users to associate runtime users to workgroups to be used while defining the workloads.

Cisco TES and Big Data
TES supports end-to-end workloads that include Big Data business processes. This release strengthens our support for Apache Hadoop, Cloudera as well as MapR. If you are traveling to San Jose for the Hadoop Summit next week stop by our booth (Cisco is a Platinum Sponsor) to see the latest Cisco solution designed specifically for the Hadoop platform. See Scott Ciccone‘s blog post for more details.

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June 3-5, 2014 --San Jose, California

 

Questions? ask-tes@cisco.com

For more on the TES 6.2 release visit http://www.cisco.com/go/workloadautomation

Data Center blogs I follow:
Raghunath Nambiar
Scott Ciccone

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Cisco IT’s Road to Application Centric Infrastructure: Organizational Readiness and the Program Team

Cisco IT is early in the journey to deploying an application centric infrastructure (ACI). This journey requires us to look at the IT organization differently. When we started evaluating what it would take to align applications to the network, we quickly realized that our organizational structure wasn’t favorable to extracting the most value from ACI. We needed an architecture team that represents all seven layers of the OSI stack, and works in sync to create tenets and policies and classify applications that conform with how we ultimately want to build out the fabric. ACI requires a completely different view of the relationship (along with a common syntax and language) between IT infrastructure and applications.

Read More »

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eStore, A Winning Digital Strategy

Earlier this month, we received some great news. Cisco ranked 25th on the InformationWeek Elite top 100 leading-edge IT organizations. Our ranking is a clear result of how we are embracing mobility, analytics, and cloud technologies to cut costs, boost productivity, and essentially, provide the best possible user experience. A prime example of how we are taking great strides in adopting the consumerization of IT is eStore. Read More »

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Cisco @StrataConf : Best Practices for Hadoop In Production-Panel Discussion

Hey data heads! O’Reilly Strata Conference kicks off tomorrow at the Santa Clara Convention Center. If you plan to go you better have tickets because the event is sold out.

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If you are attending the three days of sessions, keynotes, receptions and exhibits, please stop by the MapR booth for some face time with one of our big data partners and plan to attend their sponsored panel discussion which includes Cisco IT and other MapR customers facilitated by Mike Gualtieri from Forrester Research.

Best Practices for Hadoop In Production

“Mike Gualtieri, principal analyst at Forrester Research, Inc., will engage a panel of production Hadoop users – including Cisco IT, The Climate Corporation, The Rubicon Project, and Solutionary – to discuss the challenges and best practices for deploying Hadoop in production. Join us for an engaging conversation on tips and tricks in deploying Hadoop in production. 10:40am, Wednesday February 12 in Ballroom H” See more here.

Representing Cisco IT will be Distinguished Engineer, Piyush Bhargava. Piyush is Chief Architect for Data Architecture & Innovation and is responsible for finding new ways of harnessing value from data and for designing architectures to support data processing, analytics & data science needs.

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If you can’t make it to Strata Conference or are double booked during this time slot you can get the goods on this topic from a number of other sources.

  • First, check out the webinar Cisco and MapR produced with Mike that highlights the Cisco IT case study. Mike outlines the 7 Best Practices for Productionizing Hadoop, MapR follows with their best practices for data tables and Cisco IT covers their big data use case. If you want to skip to the Cisco IT use case, it starts at 34:00.
  • Then, take a look at my blog post on the Cisco IT big data platform success story. Cisco IT has standardized on Cisco UCS servers and fabric interconnects for its big data infrastructure and uses MapR for data tables.

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For operational workloads, Cisco IT has standardized company-wide on Cisco Tidal Enterprise Scheduler with its unique set of adapters that include API integrations to MapR, Hive and Sqoop for big data workload processing.

Cisco Tidal Enterprise Scheduler for Big Data

  • Next, spend some time reading the Unleashing IT Big Data Edition. This special edition of Unleashing IT is all about big data and highlights our joint Cisco/MapR customer Solutionary who incidentally, will join Cisco IT on the Strata Conference panel discussion on Wednesday. This e-zine is packed full of big data thought leadership; best practices for infrastructure and operations; customer success stories and include our partners Intel, MapR and others.
  • Finally, peruse the Cisco big data website for all the latest on our solutions, partners, services and resources to help you make the best informed decision on moving your big data platform from development to production.

Big Data blogs I follow:
Raghunath Nambiar
Scott Ciccone

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