This blog is for the open exchange of ideas relating to IBM Systems, storage and storage networking hardware, software and services.
(Short URL for this blog: ibm.co/Pearson )
Tony Pearson is a Master Inventor, Senior IT Architect and Event Content Manager for [IBM Systems for IBM Systems Technical University] events. With over 30 years with IBM Systems, Tony is frequent traveler, speaking to clients at events throughout the world.
Lloyd Dean is an IBM Senior Certified Executive IT Architect in Infrastructure Architecture. Lloyd has held numerous senior technical roles at IBM during his 19 plus years at IBM. Lloyd most recently has been leading efforts across the Communication/CSI Market as a senior Storage Solution Architect/CTS covering the Kansas City territory. In prior years Lloyd supported the industry accounts as a Storage Solution architect and prior to that as a Storage Software Solutions specialist during his time in the ATS organization.
Lloyd currently supports North America storage sales teams in his Storage Software Solution Architecture SME role in the Washington Systems Center team. His current focus is with IBM Cloud Private and he will be delivering and supporting sessions at Think2019, and Storage Technical University on the Value of IBM storage in this high value IBM solution a part of the IBM Cloud strategy. Lloyd maintains a Subject Matter Expert status across the IBM Spectrum Storage Software solutions. You can follow Lloyd on Twitter @ldean0558 and LinkedIn Lloyd Dean.
Tony Pearson's books are available on Lulu.com! Order your copies today!
Safe Harbor Statement: The information on IBM products is intended to outline IBM's general product direction and it should not be relied on in making a purchasing decision. The information on the new products is for informational purposes only and may not be incorporated into any contract. The information on IBM products is not a commitment, promise, or legal obligation to deliver any material, code, or functionality. The development, release, and timing of any features or functionality described for IBM products remains at IBM's sole discretion.
Tony Pearson is a an active participant in local, regional, and industry-specific interests, and does not receive any special payments to mention them on this blog.
Tony Pearson receives part of the revenue proceeds from sales of books he has authored listed in the side panel.
Tony Pearson is not a medical doctor, and this blog does not reference any IBM product or service that is intended for use in the diagnosis, treatment, cure, prevention or monitoring of a disease or medical condition, unless otherwise specified on individual posts.
The developerWorks Connections platform will be sunset on December 31, 2019. On January 1, 2020, this community and its apps will no longer be available. More details available on our FAQ.
Wrapping up my week's coverage of the IBM Pulse 2011 conference, I have had several people ask me to explain IBM's latest initiative, Smarter Computing, which IBM launched this week at this conference. Having led the IT industry through the Centralized Computing era and the Distributed Computing era, IBM is now well-positioned to help companies, governments and non-profit organizations to enter the new Smarter Computing era, focused on insight and discovery.
Thousands of IT professionals
Effiicent, but only the largest companies and governments had them
Millions of office workers
Personal computers (PC)
Innovative, extending the reach to small and medium-sized businesses, but resulted in server sprawl and increased TCO
Billions of people
Smart phones and other handheld devices
Efficient and Innovative, combining the best of centralized and distributed computing
1952 to 1980
1981 to 2010
2011 and beyond
To help clients with this transition, IBM's Smarter Computing initiative has three main components. This is a corporate-wide strategy, with systems, software and services all working together to realize results.
The first component is Big Data. This combines three different sources of data:
Traditional structured data in OLTP databases and OLAP data warehouses, using data management solutions like DB2 and IBM Netezza.
Unstructured data, including text documents, images, audio, and video, processed with massive parallelism using IBM BigInsights and Apache Hadoop.
Real-Time Analytics Processing (RTAP) of incoming data, including video surveillance, social media, RFID chips, smart meters, and traffic control systems, processed with IBM InfoSphere Streams
Of course, Big Data will bring new opportunities on the storage front, which I will save for a future post!
Rather than general purpose IT equipment, we have now the scale and scope to specialize with systems optimized for particular workloads, the second component of the Smarter Computing initiative. Of course, IBM has been delivering integrated stacks of systems, software and services for decades now, but it is important to remind people of this, as IBM now has a spate of competitors all trying to follow IBM's lead in this arena.
As with Big Data, the focus on Optimized Systems has impacted IBM's strategy on storage as well. I'll save that discussion for a future post as well!
I am glad that nearly all of the storage vendors have standardized to a common definition for Cloud, the third component of Smarter Computing, which shows that this concept has matured:
Cloud computing is a pay-per-use model for enabling network access to a pool of computing resources that can be provisioned and released rapidly with minimal management effort or service provider interaction. -- U.S. National Institute of Standards and Technology [nist.gov]
Of course, Cloud is just an evolution of IBM's Service Bureau business of the 1960s and 1970s, renting out time-sharing on mainframe systems, Grid Computing of the 1980s, and Application Service Providers that popped up in the 1990s. While the [butchers, bakers and candlestick makers] that IBM competes against might focus their efforts on just private cloud or just public cloud, IBM recognizes the reality is that different clients will need different solutions. Rather than rip-and-replace, IBM will help clients transition to cloud via inclusive solutions that adopt a hybrid approach:
Traditional enterprise with private cloud deployments, using solutions like IBM CloudBurst, SONAS and Information Archive
Traditional enterprise with public cloud services to handle seasonable peaks, providing offsite resiliency, and solutions for a mobile workforce
Hybrid clouds that blend private and public cloud services, to handle seasonal peak workloads, remote and branch offices
IBM's emphasis on IT Infrastructure Library (ITIL), Tivoli and Maximo products will play well in this space to provide integrated service management across traditional and cloud deployments. This is why IBM decided to launch Smarter Computing initiative at Pulse 2011 conference, the industry's premiere conference on intergrated service management.
The IBM Watson that competed on Jeopardy! is an excellent example of all three components of Smarter Computing at work.
IBM Watson was able to respond to Jeopardy! clues within three seconds, processing a combination of database searches with DB2 and text-mining analytics of unstructured data with IBM BigInsights.
IBM Watson combined servers, software and storage into an integrated supercomputer that was optimized for one particular workload: playing Jeopardy!
IBM Watson used many technologies prevalent in private and public cloud computing systems, storing its data on a modified version of SONAS for storage, using xCat administration tools, networking across 10GbE Ethernet, and massive parallel processing through lots of PowerVM guest images.
This week was the IBM Pulse 2011 converence in Las Vegas, Nevada, with over 7,000 attendees. I wasn't there, and my on-the-scene correspondent was too busy running the hands-on lab to get out and attend sessions. Fortunately, I was able to watch some of the [IBM Software live stream], and here are my thoughts and observations.
Fellow inventor [Dean Kamen] was the keynote speaker. His inventions help people, making the world a better place. Here are three examples I found interesting during his talk:
Helping third world countries
Dean started out with his favorite quote:
"A problem well defined is a problem half-solved." - John Dewey
Dean mentioned that we are fortunate, having both potable drinking water and a reliable supply of electricity, but 2 to 4 billion people on the planet do not. Sponsored by Coca-Cola, Dean and his team of innovators were able to come up with small units that can be placed in a village or town. One unit takes in wet liquid and produces potable drinking water. The other unit takes combustible materials, like cow dung, and products electricity. Each unit is roughly the size of half a standard server rack. What does Coca-Cola get out of this? New "vending machines"! By combining drinking water with flavored syrups, they can create soft drinks on demand.
Dean's opinion was that if you want something done, you need to work with large corporations, as governments are mired in beauracracy and rules. I agree. When I first joined IBM, I was introduced to [TRIZ] which was a systematic method for solving problems. IBM's best and brightest are working to solve some of the toughest computer science challenges. For more on TRIZ, see this blog post about [TRIZ in BusinessWeek].
Helping injured veterans
Dean Kamen is well known for inventing the two-wheeled [Segway Personal Transporter], but his company, [DEKA], makes all kinds of things, mostly medical equipment. To help wounded soldiers returning from Iraq or Afghanistan without one or both arms, Dean and his team developed a robotic arm that has enough motor dexterity to pick up a raisin or grape off the table without dropping or squashing it. Dean has appeared several times on the Colbert Report, and here is a video of the robotic arm:
I have myself enjoyed riding a Segway. A local place in Tucson uses them to lead tourists through downtown Tucson and the University of Arizona campus.
Helping young students to learn science and technology
Dean wrapped up his talking by talking about his passion about "For Inspiration and Recognition of Science and Technology" or [FIRST]. Modeled after sports competitions, FIRST encourages teams of kids to build robots that perform specific tasks. Every year, companies and universities sponsor teams by purchasing robot kits from FIRST. Teams compete in regional competitions, and then the best of those go on to compete in a stadium in Atlanta, Georgia, hosting 76,000 people cheering for their teams.
Unlike other school sports (Football, Basketball, Baseball, etc.) where a student is more likely to win the lottery than get a successful career as a professional athlete, every student involved in FIRST competitions can "go pro". A study of FIRST success tracked students who participated in competitions, and found a substantial improvement in percentage of those students attending college and working as science and engineering professionals.
I am a big fan of encouraging kids of all ages to learn more about science, technology, engineering and math [STEM]. Back in 2009, I blogged about my involvement with [One Laptop Per Child] and [Junior FIRST Lego League]. I've gotten a great reaction to my latest challenge, to build a Watson Jr. in your own basement, based on my [step-by-step] instructions.
If you attended IBM Pulse this week, please comment on your thoughts and observations!
It's Tuesday again, and that means one thing.... IBM Announcements! On the heels of [last week's announcements], IBM announced some additional products of interest to storage administrators.
IBM Information Archive
Back in 2008, IBM [unveiled the Information Archive]. This storage solution provides automated policy-based tiering between disk and tape, with non-erasable non-rewriteable enforcement to protect against unethical tampering of data. The initial release supported [both files and object storage], with support for different collections, each with its own set of policies for management. However, it only supported NFS initially for the file protocol. Today, IBM announces the addition of CIFS protocol support, which will be especially helpful in healthcare and life sciences, as much of the medical equipment is designed for CIFS protocol storage.
Also, Information Archive will now provide a full index and search feature capability to help with e-Discovery. Searches and retrievals can be done in the background without disrupting applications or the archiving operations.
IBM Tivoli Storage Manager for Virtual Environments V6.2 extends capabilities that currently exist in IBM Tivoli Storage Manager. TSM backup/archive clients run fine on guest operating systems, but now this new extension improves backup for VMware environments. TSM provides incremental block-level backups utilizing VMware's vStorage APIs for Data Protection and Changed Block Tracking features.
To minimize impact to the VMware host, TSM for VE make use of non-disruptive snapshots and offload the backup processing to a vStorage backup server. This supports file-level recovery, volume-level recovery, and full VM recovery. Of course, since it is based on TSM v6, you get advanced storage efficiency features such as compression and deduplication to minimize consumption of disk storage pools.
IBM Tivoli Monitor has been extended to support virtual servers, including VMware, Linux KVM, and Citrix XenServer. This can help with capacity planning, performance monitoring, and availability. Tivoli Monitor will help you understand the relationships between physical and virtual resources to help isolate problems to the correct resource, reducing the time it takes for debug issues between servers and storage. See the
Next week is [IBM Pulse2011 Conference] in Las Vegas, February 27 to March 2. Sorry, I don't plan to be there this year. It is looking to be a great conference, with fellow inventor Dean Kamen as the keynote speaker. For a blast from the past, read my blog posts from Pulse2008 [Main Tent sessions] and [Breakout sessions].
The IBM Challenge was a big success. One of the contestants, Ken Jennings, [welcomes our new computer overlords]. Congratulations are in order to the IBM Research team who pulled off this Herculean effort!
Some folks have poked fun at some of the odd responses and wager amounts from the IBM Watson computer during the three-day tournament. Others were surprised as I was that the impressive feat was done with less than 1TB of stored data. Here is what John Webster wrote in CNET yesterday, in hist article [What IBM's Watson says to storage systems developers]:
"All well and good. But here's what I find most interesting as a result of what IBM has done in response to the Grand Challenge that motivated Watson's creators. We know, from Tony Pearson's blog, that the foundation of Watson's data storage system is a modified IBM SONAS cluster with a total of 21.6TB of raw capacity. But Pearson also reveals another very significant, and to me, surprising data point: "When Watson is booted up, the 15TB of total RAM are loaded up, and thereafter the DeepQA processing is all done from memory. According to IBM Research, the actual size of the data (analyzed and indexed text, knowledge bases, etc.) used for candidate answer generation and evidence evaluation is under 1 Terabyte."
What Pearson just said is that the data set Watson actually uses to reach his push-the-button decision would fit on a 1TB drive. So much for big data?"
To better appreciate how difficult the challenge was, and how a small amount of data can answer a billion different questions, I thought I would cover Business Intelligence, Data Retrieval and Text Mining concepts.
"In this paper, business is a collection of activities carried
on for whatever purpose, be it science, technology,
commerce, industry, law, government, defense, et cetera.
The communication facility serving the conduct of a business
(in the broad sense) may be referred to as an intelligence
system. The notion of intelligence is also defined
here, in a more general sense, as the ability to apprehend
the interrelationships of presented facts in such a way as
to guide action towards a desired goal."
Ideally, when you need "Business Intelligence" to help you make a better decision, you perform data retrieval from a structured database for the specific information you are looking for. In other cases, you might be looking for insight, patterns or trends. In that case, you go "data mining" against your structured databases.
Here's a simple example. John runs a fruit stand. One day, he kept track of how many apples and oranges were bought by men and women. How many questions can we ask against this small set of data? Let's count them:
How many apples were sold to men?
How many apples were sold to women?
How many oranges were sold to men?
How many oranges were sold to women?
But wait! For each row and column, we can combine them into totals.
How many apples were sold in total?
How many oranges were sold in total?
How many fruit in total were sold to men?
How many fruit in total were sold to women?
How many fruit in total were sold?
But wait, there's more! Each row and column can be evaluated for relative percentages, as well as percentages of each cell compared to the total. You could make five relevant pie-charts from this data. This results in 16 more questions, such as:
Of the fruit purchased by men, what percentage for apples?
Of all the apples purchased, what percentage by women?
And that's not including more ethereal questions, such as:
Are there gender-specific preferences for different types of fruit?
What type of fruit do men prefer?
This is just for a small set, two market segments (by gender) and two products (apples and oranges). However, if you have many market segments (perhaps by age group, zip code, etc.) and many products, the number of queries that can be supported is huge. For small sets of data, you can easily do this with a spreadsheet program like IBM Lotus Symphony or Microsoft Excel.
But why limit yourself to two dimensions? The above example was just for one day's worth of activity, if John captures this data for every day for historical and seasonal trending, it can be represented as a three-dimensional cube. The number of queries becomes astronomical. This is the basis for Online Analytical Processing (OLAP), and three-dimensional tables are often referred to as [OLAP cubes].
Back in 1970, IBM invented the Structured Query Language [SQL], and today, nearly all modern relational databases support this, including IBM DB2, Informix, Microsoft SQL Server, and Oracle DB. SQL poses two challenges. First, you had to structure the data in advance to the way you expect to perform your ad-hoc queries. Deciding the groups and categories in advance can limit the way information is recorded and captured.
Second, you had to be skilled at SQL to phrase your queries correctly to retrieve the data you are after. What ended up happening was that skilled SQL programmers would develop "canned reports" with fixed SQL parameters, so that less-skilled business decision makers could base their decisions from these reports.
IBM has fully integrated stacks to help process structured data, combining servers, storage, and advanced analytics software into a complete appliance. IBM offers the [Smart Analytics System] for robust, customized deployments, and recently acquired [Netezza] for pre-configured, and more rapid deployments.
However, the bigger problem is that more than 80 percent of information is not structured!
Semi-structured data like email provides some searchable fields like From and Subject. The rest of the information is unstructured, such as text files, photographs, video and audio. To look for specific information in unstructured sources can be like looking for a needle in a haystack, and trying to get insight, patterns or trends involves text mining.
This, in effect, is what IBM Watson was able to perform so well this week. Finding the needle in the haystacks of unstructured data from 200 million pages of text stored in its system, combined with the ability to apprehend the interrelationships of meaning and subtle nuance, resulted in an impressive technology demonstration. Certainly, this new technology will be powerful for a variety of use cases across a broad set of industries!
The Tucson Executive Briefing Center hosted 20 dignitaries from local companies and academia.
This is a historic competition, an exhibition match pitting a computer against the top two celebrated Jeopardy champions:
Brad Rutter, won $3.2 million USD on Jeopardy!, winning 5 days on the show, and then three later tournamets.
Ken Jennings, winning $2.5 million in a 74-day winning streak on Jeopardy!
One of the members of the audience had never seen an episode of Jeopardy! in his life.
(Note: there are NO SPOILERS in this blog post. If you have not yet watched the show, you are safe to continue reading the rest of this post. I will not
disclose the correct responses to any of the clues nor how well each contestant scored.)
Calline Sanchez, IBM Director, Systems Storage Development for Data Protection and Retention, kicked off today's ceremonies.
The IBM Watson computer, named after IBM founder Thomas J. Watson, has been developed over the past 4 years by a team of IBM scientists who set out to accomplish a grand challenge - build a computing system that rivals a human's ability to answer questions posed in natural language with speed, accuracy and confidence. IBM Research labs in the United States, Japan, China and Israel [collaborated with Artificial Intelligence (AI) experts at eight universities], including Massachusetts Institute of Technology (MIT), University of Texas (UT) at Austin, University of Southern California (USC), Rensselaer Polytechnic Institute (RPI), University at Albany (UAlbany), University of Trento (Italy), University of Massachusetts Amherst, and Carnegie Mellon University.
(Disclaimer: I attended the University of Texas at Austin. My father attended Carnegie Mellon University.)
Last week, NOVA on PBS had a special episode on the making of IBM Watson, you can [watch it online] on their website. Delaney Turner, IBM Social Media Communications Manager for Business Analytics Software, has posted [his observations of Nova].
Since IBM Watson is the size of 10 refrigerators and weighs over 14,000 pounds, it was easier to design the Jeopardy! set at the TJ Watson Research lab in Yorktown Heights, NY, than to ship it over to California where the show is normally recorded. Two of the visual designers that worked on this set, as well as on the visual appearance of Watson, live in Tucson and were part of our audience today.
The IBM Challenge consists of a two-game tournament, where the scores of both games will be added to determine winner rankings. The producers of Jeopardy! will give $1 million dollars USD to first place, $300,000 to second place, and $200,000 to third place. Regardless of outcome, [IBM will donate all of its winings to charity]. The two human contestants plan to donate half of their earnings to their favorite charities as well.
Jeopardy! The IBM Challenge
Alex Trebek introduces IBM Watson, explaining that it can neither hear nor see. It will receive all information electronically. Categories and clues will be sent as text files via TCP/IP over Ethernet at the same time the two human contestants see them so that all have the same time to think about the right answer.
Watson has two rows of five racks, back to back. This was done so that cold air could rise up from holes in the tile floors around the unit, and all the hot air would be forced into the center and up to the ceiling return. This technique is known as "hot aisle/cold aisle" design. Alex Trebek opens one of the rack doors to show a series of 4U-high IBM Power 750 servers.
The avatar is a representation of Watson, as the machine itself is too big to fit behind the podium. The avatar is IBM's "Smarter Planet" logo with orbiting streaks and circles. It shows "Green" when it has high confidence, and orange when it gets an answer wrong. When busy thinking, the streaks and circles speed up, the closest we will see to "watching a computer sweat."
During the show, an "Answer panel" shows Watson's top three candidate responses, with confidence level compared to its current "buzz threshold".
Watson knows what it knows, and knows what it doesn't know. Here is an [Interactive Watson Game] on New York Times website to give you an idea of how the answer panel works. I was impressed with how close all three candidate answers were. In a question about Olympic swimmers, all three candidates are Olympic swimmers. In a question about the novel "Les Miserables", all three candidates were characters of that novel.
Well, IBM Watson did well, but missed answered some questions incorrectly. This [parody Slate video] pokes fun at this. Here were some discussions we had after the show ended:
IBM did not do well in categories that required [abductive reasoning]. For example, to identify two or three things that happened in different years, and then postulate that what they all have in common is a specific decade (such as the 1950s) is difficult.
Watson does not hear the wrong answers from the two human contestants. For one question, Ken buzzes in first, guesses wrong, then Watson buzzes in with the same exact response. Alex Trebek rebukes Watson with "No, Ken just said that!" Brad would learn from their mistakes and guess correctly for the score.
Watson is provided the correct answer after a contestant guesses it correctly, or if nobody does, when Alex provides the correct response. This is sent as a text message to Watson immediately, so that it can use this information to adjust its algorithms and machine-learning for future clues in that same category. This was evident in the "Answer panel" on the fourth and fifth attempts on the category of "Decades".
With this demonstration, IBM Research has advanced science by leaps and bounds for the Articial Intelligence community. IBM is a leader in Business Analytics, and this technology will find uses in a variety of industries. The average knowledge worker spends 30 percent of her time looking for information on corporate data repositories. By demonstrating a computer that can provide answers quickly, employees will be more productive, make stronger business decisions, and have greater insight.
Day 1 was only able to cover the first round of Game 1. This allowed more time to talk about the history and technology of IBM Watson. Tomorrow, the contestants will finish Game 1 and head into Game 2.