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Cisco’s Data Center and Cloud Management Software at Cisco Live San Francisco #CLUS

May 18, 2014 at 4:00 pm PST

We’re excited to showcase new innovations in our data center infrastructure automation and cloud management software at Cisco Live San Francisco this week!

CL14-CoSp-Exhib-250x250-GGB

This past Friday, Cisco announced the new Cisco UCS Director version 5.0 – including Application Centric Infrastructure (ACI) support and integration with the Cisco Application Policy Infrastructure Controller (APIC). Cisco customers, prospective customers, and partners in the data center market won’t want to miss these two Cisco Live breakout sessions that will showcase this major new release on Thursday:

Cisco UCS Director 5.0
PSODCT-1004
Thursday, May 22
8:30 to 9:30am

Management and Automation of Application Centric Infrastructure (ACI) with Cisco UCS Director
BRKACI-2410
Thursday, May 22
12:30 to 2:00pm

In addition, we’ll be featuring live demos of UCS Director 5.0 all week in the Cisco Live World of Solutions expo. Here are some of the Cisco UCS Director + ACI demos you don’t want to miss:

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How Data Virtualization Helps Data Scientists

By now it is clear that big data analytics opens the door to unprecedented analytic opportunities for business innovation, customer retention and profit growth. However, a shortage of data scientists is creating a bottleneck as organizations move from early big data experiments into larger scale adoption. This constraint limits big data analytics and the positive business outcomes that could be achieved.

Jason Hull

Click on the photo to hear from Comcast’s Jason Hull, Data Integration Specialist about how his team uses data virtualization to get what they need done, faster

It’s All About the Data

As every data scientist will tell you, the key to analytics is data. The more data the better, including big data as well as the myriad other data sources both in the enterprise and across the cloud. But accessing and massaging this data, in advance of data modeling and statistical analysis, typically consumes 50% or more of any new analytic development effort.

• What would happen if we could simplify the data aspect of the work?
• Would that free up data scientists to spend more time on analysis?
• Would it open the door for non-data scientists to contribute to analytic projects?

SQL is the key. Because of its ease and power, it has been the predominant method for accessing and massaging data for the past 30 years. Nearly all non-data scientists in IT can use SQL to access and massage data, but very few know MapReduce, the traditional language used to access data from Hadoop sources.

How Data Virtualization Helps

“We have a multitude of users…from BI to operational reporting, they are constantly coming to us requesting access to one server or another…we now have that one central place to say ‘you already have access to it’ and they immediately have access rather than having to grant access outside of the tool” -Jason Hull, Comcast

Data virtualization offerings, like Cisco’s, can help organizations bridge this gap and accelerate their big data analytics efforts. Cisco was the first data virtualization vendor to support Hadoop integration with its June 2011 release. This standardized SQL approach augments specialized MapReduce coding of Hadoop queries. By simplifying access to Hadoop data, organizations could for the first time use SQL to include big data sources, as well as enterprise, cloud and other data sources, in their analytics.

In February 2012, Cisco became the first data virtualization vendor to enable MapReduce programs to easily query virtualized data sources, on-demand with high performance. This allowed enterprises to extend MapReduce analyses beyond Hadoop stores to include diverse enterprise data previously integrated by the Cisco Information Server.

In 2013, Cisco maintained its big data integration leadership with updates of its support for Hive access to the leading Hadoop distributions including Apache Hadoop, Cloudera Distribution (CDH) and Hortonworks (HDP). In addition, Cisco now also supports access to Hadoop through HiveServer2 and Cloudera CDH through Impala.

Others, beyond Cisco, recognize this beneficial trend. In fact, Rick van der Lans, noted Data Virtualization expert and author, recently blogged on future developments in this area in Convergence of Data Virtualization and SQL-on-Hadoop Engines.

So if your organization’s big data efforts are slowed by a shortage of data scientists, consider data virtualization as a way to break the bottleneck.

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New UCS Servers deliver innovative scaling options and record-breaking power

February 18, 2014 at 10:31 am PST

This week we’re announcing new systems at the upper end of the UCS server product line: some heavy-duty iron for heavy-duty times.   These are important new tools for our UCS customers:  the digital age is accelerating, IT needs more horsepower to keep up, and there is a lot at stake.

Cisco UCS Servers with Intel® Xeon® Processor E7 V2 Deliver Unmatched Customer Benefits from Cisco Data Center

Consider this: less than 10 years ago, some of the largest mainframes scaled up to half a terabyte (TB) of main memory.  What if I were to tell you that these latest generation UCS blade servers will scale to 3TB?   Sound like a lot?  It is.  And that’s just the two-processor version.   Connect two UCS B260 M4 blades with an expansion connector and they become a UCS B460 M4, a four socket server that will scale to 6TB.  Putting that into perspective: a spiffy new laptop might ship today with 8GB of memory.   Multiply that by 750 and you have 6TB.

Not too long ago, all the content Wikipedia would fit in this type of footprint (in 2010 it was just under 6TB with media.)   Here is a fun illustration of what this scale of data would look like on paper (just the ~10GB of text, not the images.)  Now remember, we’re not talking about fitting all that data on the local disks of the server – we’re talking about fitting it in main memory.   This is becoming crucially important in the field of data analytics, where “in-memory” is the key to speed and competitiveness.  Applications like SAP HANA are at the forefront of this trend. Today, at Intel’s launch event in San Francisco, Dan Morales (Vice President of Enabling Functions at eBay) joined us to talk about how they’re betting on this type of analytic technology to help them make the eBay Marketplace work better for buyers and sellers (and eBay shareholders.)   I’ll post a video clip of that soon; his description of the challenges and opportunities, at eBay scale, is worth a watch.

We’ve talked about memory scaling, and Bruno Messina has a nice post that talks more about the scalability on these systems and UCS at large.   But dominating performance is the name of the game: behemoth processing performance is what we look for at this end of the server spectrum and Intel has not disappointed on this round of new technology.   The next generation of the Intel Xeon E7 family packs up to 15 cores per processor and delivers an average 2x performance increase compared to previous generation products.   Performance will be even higher on specific workloads, for example up to 3X on database and even higher for virtualization.   Cisco’s implementation of this technology has once again set the standard for system performance.   In today’s launch, Intel cited Cisco with 6 industry-leading results on key workloads.  As of this posting, the closest to come to that achievement that was Dell with 4.  HP ProLiant posted 1.  So hats off, once again, to the engineering team in Cisco’s Computing Systems Product Group.  Girish Kulkarni has a great summary of the performance news here.

 

New UCS Mission Critical Servers from Cisco Data Center

 

Our collaboration with Intel is one of the best technology combinations in the industry today.  Consider what we both bring to the party.  Intel: innovation in processor technology that drives Moore’s Law.  Cisco: innovation in connecting things across the data center and around the world.  UCS is an outcome of two blue-chip tech powerhouses investing in real innovation and the results have changed the industry.

In 1991, Stewart Alsop famously wrote:  “I predict that the last mainframe will be unplugged on 15 March 1996.”  He just as famously had to eat his words.  He munched on those twelve years ago, and while mainframes and RISC-based systems remain, there is an inexorable trend as the heaviest analytic workloads continue to shift to the type of scale-up x86-based systems we’re talking about today.   It only makes sense.  So while this will garner me plenty of comments from the architectural purists out there, I say “go ahead and plug a mainframe back in.”  It will fit right in your UCS B-Series blade chassis…

 

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Get Inspired by Cisco Live Europe 2014

Cisco Live Europe 2014 (Milan) just ended and I think I will need a few days to reorganize my ideas. It was my first opportunity to attend #CLEUR, and moreover I did it as a CCIE.

CLEUR is not just a Cisco event (or should I say THE Cisco event) but also a unique opportunity to experience technology, expertise, vision, and inspiration.  And of course meet friends. Read More »

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SDN Reflections on the London Gartner Data Center Conference – Part 1

December 6, 2013 at 4:58 am PST

Last week I was in London for the Gartner Data Center Conference.  As always there was a wide range of interesting topics being discussed, all very useful.  Working in Cisco Data Center Services, I am interested in many data center topics, however this year I was interested to hear perspectives on SDN, how the market is evolving, and how the attendees -- including many senior IT practitioners -- are considering SDN adoption.

London's Big Ben at Night

London’s Big Ben at Night

From a Cisco perspective, we were showcasing the recently launched Application Centric Infrastructure (ACI), which generated a lot of interest.  There is growing awareness among our customers that ACI could do for networks and applications what the Cisco UCS has done for the server market (with UCS server profiles in the latter proving a good analogy to help customers understand the potential of ACI).

So what were some of my key takeaways from the SDN discussion I heard here?  And what were the questions that in my view are still not being discussed sufficiently across the industry?

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