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Purpose-Built Solutions Make a Big Difference In Extracting Data Insights: HP ProLiant SL4500
This is a duplicate of the blog I’ve authored on the HP blog site at http://h30507.www3.hp.com/t5/Hyperscale-Computing-Blog/Purpose-Built-Solutions-Make-a-Big-Difference-In-Extracting-Data/ba-p/173222#.VEUdYrEo70c
Indulge me as I flash back to the summer of 2012 at the Aquatics Center in London, England – it’s the Summer Olympics, where some of the world’s top swimmers, representing a host of nations, are about to kick off the Men’s 100m Freestyle swimming competition. The starter gun fires, and the athletes give it their all in a heated head to head match for the gold.
And the results of the race are astounding: USA’s Nathan Adrian took the gold medal with a time of 47.52 seconds, with Australia’s James Magnussen finishing a mere 0.01 seconds later to claim the silver medal! It was an incredible display of competition, and a real testament to power of the human spirit.
For an event demanding such precise timing, we can only assume that very sensitive and highly calibrated measuring devices were used to capture accurate results. And it’s a good thing they did – fractions of a second separated first and second place.
Now, you and I have both measured time before – we’ve checked our watches to see how long it has been since the workday started, we’ve used our cell phones to see how long we’ve been on the phone, and so on. It got the job done. Surely the Olympic judges at the 2012 Men’s 100m Freestyle had some of these less precise options available – why didn’t they just simply huddle around one of their wrist watches to determine the winner of the gold, silver and bronze?
OK, I am clearly taking this analogy to a silly extent to make a point.
When you get serious about something, you have to step up your game and secure the tools you need to ensure the job gets done properly.
There is a real science behind using purpose-built tools to solve complex challenges, and the same is true with IT challenges, such as those addressed with big data / scale out storage. There are a variety of infrastructure options to deal with the staggering amounts of data, but there are very few purpose built server solutions like HP’s ProLiant SL4500 product – a server solution built SPECIFCIALLY for big data and scale out storage.
The HP ProLiant SL4500 was built to handle your data. Period.
- It provides an unprecedented drive capacity with over THREE PB in a single rack
- It delivers scalable performance across multiple drive technologies like SSD, SAS or SATA
- It provides significant energy savings with shared cooling and power and reduced complexity with fewer cables
- It offers flexible configurations •A 1-node, 60 large form factor drive configuration, perfect for large scale object storage with software vendors like Cleversafe and Scality, or with open source projects like OpenStack Swift and Ceph
- A 2-node, 25 drive per node configuration, ideal for running Microsoft Exchange
- A 3-node, 15 drive per node configuration, optimal for running Hadoop and analytics applications
If you’re serious about big data and scale out storage, it’s time to considering stepping up your game with the SL4500. Purpose-built makes a difference, and the SL4500 was purpose-built to help you make sense of your data.
You can learn more about the SL4500 by talking to your HP rep or by visiting us online at HP ProLiant SL4500 Scalable Systems or at Object Storage Software for ProLiant.
And if you’re here at Hadoop World this week, come on by the HP booth – we’d love to chat about how we can help solve your data challenges with SL4500 based solutions.
Until next time,
Joseph George
NOW AVAILABLE: The Dell Red Hat Cloud Solution, powered by RHEL OpenStack Platform!
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This is a duplicate of a blog I posted on del.ly/60119gex.
This week, those of us on the OpenStack and Red Hat OpenStack teams are partying like its 1999! (For those of you who don’t get that reference, read this first.)
Let me provide some context…
In 1999, when Linux was still in the early days of being adopted broadly by the enterprise (similar to an open source cloud project we all know), Dell and Red Hat joined forces to bring the power of Linux to the mainstream enterprise space.
Fast forward to today, and we see some interesting facts:
- Red Hat has become the world’s first billion dollar open source company
- 1 out of every 5 servers sold annually runs Linux
- Enterprise’s view of open source is far more receptive than in the past
So today – Dell and Red Hat are doing it again: this time with OpenStack.
Today, we announce the availability of the Dell Red Hat Cloud Solution, Powered by Red Hat Enterprise Linux OpenStack Platform – a hardware + software + services solution focused on enabling the broader mainstream market with the ability to run and operate OpenStack backed by Dell and Red Hat. This is a hardened architecture, a validated distribution of OpenStack, additional software, and services / support to get you going and keep you going, and lets you:
- Accelerate your time to value with jointly engineered open, flexible components and purpose engineered configurations to maximize choice and eliminate lock-in
- Expand on your own terms with open, modular architectures and stable OpenStack technologies that can scale out to meet your evolving IT and business needs
- Embrace agility with open compute, storage, and networking technologies to transform your application development, delivery, and management
- Provide leadership to your organization with new agile, open IT services capable of massive scalability to meet dynamic business demands
Here is one more data point to consider – Dell’s IT organization is using the RHEL OpenStack Platform as a foundational element for incubating new technologies with a self-service cloud infrastructure. Now, that is pretty strong statement about how an OpenStack cloud can help IT drive innovation in a global scale organization.
At the end of the day, both Dell and Red Hat are committed to getting OpenStack to the enterprise with the right level of certification, validation, training, and support.
We’ve done it before with RHEL, and we’re going to do it again with OpenStack.
Until next time,
JOSEPH
@jbgeorge
Day 2: Big Data Innovation Summit 2014 #DataWest14
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Hello again big data fans – from where I’ve learned the San Francisco 49’ers will be playing their 2014 NFL season at Levi’s Stadium… Santa Clara!
(BTW, the stadium – from what I could see – is beautiful! I’m a big NFL fan, and there’s now another reason to come to the San Jose area, other than all the cloud / big data conferences.)
Got a lot of great feedback on yesterday’s “Day 1” post of the summit, so here are some observations from the final day of the conference.
- Yahoo’s Duru Ahanotu spoke through driving efficiency in how data teams are organized, going through the permutations of generalists vs specialists and centralized vs de-centralized, and how to best address teams in each model.
. - PayPal’s Moises Nascimento (who is a very captivating speaker) drove the point home, that though we are now adopting many of the new data technologies like Hadoop and NoSQL, most of our existing data sources and toolsets still provide value – so there is value in leveraging ALL data sources.
. - Moises also made a point of highlighting that data manipulation is best handled at the SYSTEM level, while data analysis is better managed at the ENTERPRISE level
. - In HP’s discussion, they introduced the concept of the GEOBYTE – 10^30 bytes, a size of data that the human race is expected to hit in the next few years.
To provide context on the magnitude of a GEOBYTE (10^30 bytes), there is estimated to only be 10^19 GRAINS OF SAND ON THE EARTH. Think about that for a second.
- The team also highlighted their view on “Big BI” vs “Big Data”
- Big BI – same types of analysis but on more data; more batch processing; results that were not easily actionable
- Big Data – joining datasets that have not been previously joined, near real time analysis, action oriented results
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- I thought Ancestry.com had one of the best sessions of the event, as they went deep into the GERMLINE algorithm that was the foundation of their business technology, and how they had to create jermline (now with a “j”) based on Hadoop / HDFS to create a SCALABLE matching engine. As we all know, SCALE matters. The performance and speed benchmarks between the “G” project and the “j” project were mindblowing.
. - Finally, sat in on the Netflix session – in addition to being a big fan of Netflix, as both a consumer and a tech observer, I’ve always been impressed with the way Netflix has evolved their business, and continues to do so. In this session, they went into great detail on their use of the Amazon cloud services, and their open source projects as a layer above to enhance functionality and deploy features. Topics touched on included red / black deployment to allow ease of features into production, and the importance of graceful degradation, so that a failure can be less of a catastrophic event for the end user.
.- One very telling statement is really a commentary on the value of use and participation in the open source process – Netflix was clear that they see value in being an open source contributor / leader is that it preserves the future of their systems – rather than sitting back and letting the industry decide their direction with tools and tech, Netflix uses open source to help drive and lead the industry to where they see value.
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- One very telling statement is really a commentary on the value of use and participation in the open source process – Netflix was clear that they see value in being an open source contributor / leader is that it preserves the future of their systems – rather than sitting back and letting the industry decide their direction with tools and tech, Netflix uses open source to help drive and lead the industry to where they see value.
- (I did resist the urge to ask the Netflix presenter when the next season of “House of Cards” would come out. 🙂 )
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One of the frequent questions that came up at the Dell booth was “what is Dell doing in big data?”
The answer? Actually… quite a bit, and for quite a while.
Between the Dell Apache Hadoop HW+SW+Services Solution, the Toad BI suite, the Kitenga analytics toolsets, and our growing HPC business, Dell has been a part of this movement since its early days. I’d recommend you drop us a line at Hadoop@Dell.com or visit us at http://www.Dell.com/Hadoop to learn more.
If you were out at the show this week, be sure to leave a comment on your thoughts as well.
Hope everyone has safe trips home, and we’ll see you at the next big data get-together!
Until next time,
JBG
@jbgeorge
Day 1: Big Data Innovation Summit 2014
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Hello from sunny, Santa Clara!
My team and I are here at the BIG DATA INNOVATION SUMMIT representing Dell (the company I work for), and it’s been a great day one.
I just wanted to take a few minutes to jot down some interesting ideas I heard today:
- In Daniel Austin’s keynote, he addressed that the “Internet of things” should really be the “individual network of things” – highlighting that the number of devices, their connectivity, their availability, and their partitioning is what will be key in the future.
. - One data point that also came out of Daniel’s talk – every person is predicted to generate 20 PETABYTES of data over the course of a lifetime!
. - Juan Lavista of Bing hit on a number of key myths around big data:
- the most important part of big data is its size
- to do big data, all you need is Hadoop
- with big data, theory is no longer needed
- data scientists are always right 🙂
QUOTE OF THE DAY: “Correlation does not yield causation.” – Juan Lavista (Bing)
- Anthony Scriffignano was quick to admonish the audience that “it’s not just about data, it’s not just about the math… [data] relationships matter.”
. - The state of Utah state government is taking a very progressive view to areas that analytics can help drive efficiency in at that level – census data use, welfare system fraud, etc. And it appears Utah is taking a leadership position in doing so.
I also had the privilege of moderating a panel on the topic of the convergence between HPC and the big data spaces, with representatives on the panel from Dell (Armando Acosta), Intel (Brent Gorda), and the Texas Advanced Computing Center (Niall Gaffney). Some great discussion about the connections between the two, plus tech talk on the Lustre plug-in and the SLURM resource management project.
Additionally, Dell product strategists Sanjeet Singh and Joey Jablonski presented on a number of real user implementations of big data and analytics technologies – from university student retention projects to building a true centralized, enterprise data hub. Extremely informative.
All in all, a great day one!
If you’re out here, stop by and visit us at the Dell booth. We’ll be showcasing our hadoop and big data solutions, as well as some of the analytics capabilities we offer.
(We’ll also be giving away a Dell tablet on Thursday at 1:30, so be sure to get entered into the drawing early.)
Stay tuned, and I’ll drop another update tomorrow.
Until next time,
JOSEPH
@jbgeorge
Michael Dell Comments on the “Data Economy”
This is a repost of my blog at http://dell.to/1euUcqk.
In this short interview with Inc., Michael Dell provides an overview of the company’s transformation into a leading player in the “data economy.”
As Michael notes, with the costs of collecting data decreasing, more companies in a growing number of industries are making better use of existing data sources, and gathering data from new sources.
And that’s where Dell has been enabling customers for years with solutions built with technologies like Hadoop and NoSql. Helping companies and organizations make better use of this data, and assisting them in using it to solve their challenges, are just a few of the ways Dell has changed the Big Data conversation, and built an entirely new enterprise business along the way.
As a member of the Technology CEO Council, Michael also recently joined other tech CEOs to discuss the data economy with policy makers. As an example of the potential of the data economy, he explained how Dell’s growing health information technology practice includes 7 billion medical images. These images are in an aggregated data set allowing researchers to mine them for patterns and predictive analytics.
“There’s lots that can be done with this data that was very, very siloed in the past,” Michael toldComputerworld, “We’re really just kind of scratching the surface.”
It’s certainly an exciting time to be at Dell – and the data revolution continues!
It’s OpenStack Foundation Election Time!
What is your relationship to OpenStack, and why is its success important to you? What would you say is your biggest contribution to OpenStack’s success to date?
I believe OpenStack represents a trend that service providers and enterprise IT are making to deeper community collaboration on new technologies and practices, and I will continue to drive the initiative to make my customers and the community successful in a very real-world meaningful way.
Describe your experience with other non profits or serving as a board member. How does your experience prepare you for the role of a board member?
What do you see as the Board’s role in OpenStack’s success?
What do you think the top priority of the Board should be in 2014?
1. Clarify the definition of OpenStack – what is core, what is compliant, and what is not.
2. Understand where the strategic opportunities lie for OpenStack as a technology, and clear the path to ensure OpenStack gets there.
3. Fully enable any and every new entrant to OpenStack in a real way – developers, implementers, and users – with the right level of documentation, tools, community support, and vendor support.
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Thanks, and appreciate your nomination to represent the OpenStack Foundation in 2014!
Until next time,
JOSEPH
@jbgeorge