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February 18, 2019 Timothy Prickett Morgan
well, that took reasonably a long time. After what appears fancy eons of nudging and cajoling and pushing, IBM is making the IBM i operating system and its built-in database administration system, as neatly as the utility edifice tackle and other techniques application, available on its self-branded IBM Cloud public cloud.
massive Blue previewed its plans to deliver both IBM i and AIX to the IBM Cloud at its annual feel conference in Las Vegas, on scale out machines aimed at little and medium groups in addition to to purchasers who exigency to sprint clusters of machines, and on scale up programs that tolerate NUMA electronics that greater tightly cluster them into shared remembrance systems.
There are a lot of questions about how this will be every be packaged up and bought below the unwieldy designation of the IBM power programs virtual Server on IBM Cloud. however they can let you know every that they know and fill you in as they study extra.
The dash techniques slices served up on the IBM Cloud working IBM i and AIX were first rolled out for early access to chosen clients to verify the APIs for the manage plane, which they postulate is in keeping with the PowerVC implementation of OpenStack. The initial shoppers who are kicking the tires tolerate been imagined to simplest deploy edifice and check environments or protype code, under no circumstances anything operating in construction. This was totally intended to be a proof of concept setup at this factor, as that you can note from the rollout roadmap:
The alpha and beta checking out for the power methods slices on the IBM Cloud is on an attractive speedy song, operating from February into March, as you can see, and well-liked availability is slated for some time in March. probably somewhere in opposition t the conclusion, we'd guess. IBM is originally making the dash puffs – what else are you able to designation them as shorthand? – available in the early entry assessments in its US East datacenter in the Washington DC metro enviornment; it isn't transparent what iron became used. The alpha and beta checking out is being finished on a collection of energy S922 scale out machines, that are in response to a pair of Power9 processors and which frankly is a big field for most IBM i stores every by passage of itself, in addition to on vigour E880 scale up systems, that are being scaled up to sixteen sockets and which exercise the older Power8 processors. every of the machines exercise ten-core processors, that are the sweet spot between performance, chip yield, and cost in the dash techniques line. The Power9 chips within the power S922 servers sprint at 2.8 GHz and can faster up to 3.9 GHz if there's enough thermal headroom; these chips search for fancy they may tolerate 4 threads per core (often known as SMT4), which isn't as a all lot threading because the middling Power8 chip presents in scale out machines with SMT8 threading (eight threads per core) and twice as many cores per die (24 cores versus 12 cores). Anyway, it appears fancy the dash S922 is being outfitted with the ponderous cores, not the gentle ones. The Power8 chips in the power E880 are running at 4.19 GHz and additionally back SMT8 threading (there become handiest a ponderous core here); every sixteen cores are populated with ten-core Power8 chips, with a optimum scalability of 160 cores in a lone ratiocinative partition on the IBM Cloud.
each of the machines are being configured with 32 GB reminiscence sticks, which are again at the candy spot between skill, bandwidth, and value per bit, and IBM is allowing valued clientele to configure the machines with anyplace from 8 GB to sixty four GB of leading remembrance per core. if you desire denser remembrance to bolster the ability, that you may double it up the usage of sixty four GB reminiscence sticks, and then double it up once again to 128 GB sticks, however this may be a custom order and it will charge considerably more, they think. IBM is offering disk and flash storage up to 2 TB for aboriginal storage on the circumstances and growing to be at 10 GB increments. exterior storage for applications and databases is on Storwize V7000 disk arrays within the racks near this power iron, and are linked to the servers by using Fibre Channel switches. valued clientele can participate machines or employ dedicated iron, depending on their proclivities for absolute safety and coping with Noisy neighbors on the digital infrastructure.
Steve Sibley vice chairman and offering manager for the Cognitive programs division at IBM, gave me a sneak peek at the future energy cloud slices on a consult with to the Austin, Texas labs final week, forward of the respect convention. here is how the facets and functions of the ratiocinative partitions on the IBM Cloud are shaping up:
Sibley advised us that the pricing became now not yet set in stone for the digital energy skill on the IBM Cloud, but when pressed about comparing the charge between purchasing tackle and renting it on the cloud, Sibley estimated that for a given IBM i or AIX workload running on in a similar passage configured hardware and ratiocinative partitions, running the cloud sample would cost about 30 percent to 40 p.c extra on the instance running full out over three years compared to purchasing the iron and using it for 3 years. The change, of route, is that IBM is managing the power methods and paying for the datacenter, the electrical energy, the cooling, the safety, patch updates on firmware, the installing of the PowerVM hypervisor and its update, and the installing of the IBM i or AIX operating gadget. When agencies buy their own dash programs machines, except they regain augmented services from IBM or a enterprise accomplice, it’s every on them. Pricing for the digital machines, the memory, the storage, and the operating gadget and databases are every set per hour.
incidentally, it is not transparent what IBM i and AIX releases are supported on the machines, but most likely the current IBM i 7.2 and IBM i 7.three releases are supported on the IBM Cloud in addition to AIX 7.1 and AIX 7.2, which are moreover latest. Linux is not mentioned as a supported platform, but SAP HANA workloads are and that implies that there's a Linux – and in particular pink Hat commercial enterprise Linux – below it on account that HANA in-reminiscence databases don't look to be supported on any Unix variant, or IBM i for that rely.
by passage of March, IBM plans to tolerate the IBM i and AIX cases purchasable in creation in its US East (Washington DC) and US South (Dallas) areas, and in the 2d quarter IBM plans to roll it in its European datacenter in its european valuable (Frankfurt) vicinity, with different datacenters coming out as claim pulls and IBM pushes.
we will Take a glance on the pricing as soon as it turns into accessible and note the passage it every stacks up, and regain the suggestions of other IBM i cloud avid gamers about what astronomical Blue is doing.
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In September 2018, IBM announced a brand modern product, IBM Db2 AI for z/OS. This synthetic intelligence engine monitors facts access patterns from executing SQL statements, makes exercise of laptop gaining scholarship of algorithms to opt for most fulfilling patterns and passes this counsel to the Db2 query optimizer to be used by subsequent statements.machine studying on the IBM z Platform
In may additionally of 2018, IBM announced version 1.2 of its laptop learning for z/OS (MLz) product. here is a hybrid zServer and cloud software suite that ingests performance statistics, analyzes and builds models that characterize the health status of numerous indicators, monitors them over time and gives precise-time scoring capabilities.
several elements of this product offering are geared toward assisting a group of mannequin developers and bosses. as an example:
This laptop gaining scholarship of suite become firstly aimed at zServer-based analytics purposes. one of the first obtrusive selections became zSystem performance monitoring and tuning. system management Facility (SMF) facts which are instantly generated by the operating device supply the uncooked statistics for tackle aid consumption corresponding to crucial processor utilization, I/O processing, reminiscence paging and so forth. IBM MLz can collect and save these facts over time, and construct and train fashions of tackle habits, score those behaviors, determine patterns no longer with no distress foreseen with the aid of humans, enhance key performance warning signs (KPIs) and then feed the model effects again into the device to tolerate an result on device configuration changes that can enrich efficiency.
The next step turned into to invoke this suite to resolve Db2 performance statistics. One solution, called the IBM Db2 IT Operational Analytics (Db2 ITOA) solution template, applies the machine getting to know know-how to Db2 operational statistics to capitalize an figuring out of Db2 subsystem health. it may dynamically build baselines for key performance warning signs, supply a dashboard of those KPIs and provides operational group of workers precise-time insight into Db2 operations.
whereas well-liked Db2 subsystem performance is an distinguished aspect in basic application fitness and performance, IBM estimates that the DBA back workforce spends 25% or greater of its time, " ... combating entry route issues which antecedent efficiency degradation and repair tolerate an impact on.". (See Reference 1).AI comes to Db2
accept as upright with the plight of modern DBAs in a Db2 atmosphere. In modern IT world they must back one or extra big facts purposes, cloud software and database services, application installation and configuration, Db2 subsystem and application efficiency tuning, database definition and management, catastrophe restoration planning, and extra. query tuning has been in being considering that the origins of the database, and DBAs are constantly tasked with this as well.
The coronary heart of query path analysis in Db2 is the Optimizer. It accepts SQL statements from functions, verifies authority to entry the information, stories the areas of the objects to be accessed and develops a list of candidate records access paths. These entry paths can embrace indexes, desk scans, quite a lot of table join strategies and others. in the records warehouse and massive facts environments there are continually additional choices obtainable. One of these is the being of abstract tables (every now and then known as materialized question tables) that embrace pre-summarized or aggregated records, therefore allowing Db2 to avoid re-aggregation processing. one other option is the starjoin access course, regular within the facts warehouse, where the order of desk joins is changed for efficiency causes.
The Optimizer then experiences the candidate access paths and chooses the entry direction, "with the lowest can charge." cost during this context means a weighted summation of useful resource usage together with CPU, I/O, remembrance and different components. at last, the Optimizer takes the bottom cost entry direction, shops it in remembrance (and, optionally, in the Db2 directory) and starts off entry path execution.
big information and facts warehouse operations now embrace application suites that allow the industry analyst to exercise a graphical interface to build and maneuver a miniature records model of the data they want to analyze. The programs then generate SQL statements in accordance with the users’ requests.
The issue for the DBA
with a view to achieve respectable analytics on your dissimilar facts stores you exigency a expedient knowing of the data necessities, an figuring out of the analytical services and algorithms accessible and a high-performance statistics infrastructure. lamentably, the quantity and location of data sources is expanding (both in dimension and in geography), records sizes are turning out to be, and applications proceed to proliferate in number and complexity. How may silent IT managers assist this environment, specially with essentially the most skilled and ripen staff nearing retirement?
take into account additionally that a astronomical a piece of reducing the total charge of possession of these methods is to regain Db2 functions to sprint faster and more effectively. This continually interprets into using fewer CPU cycles, doing fewer I/Os and transporting less statistics throughout the network. considering that it is commonly intricate to even identify which functions could odds from efficiency tuning, one strategy is to automate the detection and correction of tuning concerns. here's where computer learning and synthetic intelligence can be used to incredible effect.Db2 12 for z/OS and synthetic Intelligence
Db2 version 12 on z/OS uses the machine discovering amenities outlined above to accumulate and store SQL question text and entry course details, in addition to precise performance-related historic assistance comparable to CPU time used, elapsed times and result set sizes. This offering, described as Db2 AI for z/OS, analyzes and stores the records in laptop discovering models, with the model evaluation consequences then being scored and made available to the Db2 Optimizer. The next time a scored SQL commentary is encountered, the Optimizer can then exercise the model scoring facts as enter to its access route alternative algorithm.
The outcome should silent be a discount in CPU consumption because the Optimizer uses mannequin scoring input to choose more advantageous access paths. This then lowers CPU charges and speeds software response times. a significant potential is that the usage of AI software does not require the DBA to tolerate information science odds or abysmal insights into query tuning methodologies. The Optimizer now chooses the ultimate entry paths based not only on SQL query syntax and records distribution records but on modelled and scored historical efficiency.
This will moreover be primarily crucial in case you preserve records in discrete locations. as an example, many analytical queries against massive statistics require concurrent access to confident information warehouse tables. These tables are commonly referred to as dimension tables, and that they comprise the information aspects usually used to manage subsetting and aggregation. for instance, in a retail atmosphere confidence a desk referred to as StoreLocation that enumerates each store and its region code. Queries against save sales statistics may exigency to compund or summarize revenue by passage of region; hence, the StoreLocation table may be used by means of some massive statistics queries. during this ambiance it is common to Take the dimension tables and copy them always to the huge records software. within the IBM world this location is the IBM Db2 Analytics Accelerator (IDAA).
Now suppose about SQL queries from both operational functions, facts warehouse users and massive facts company analysts. From Db2's point of view, every these queries are equal, and are forwarded to the Optimizer. youngsters, within the case of operational queries and warehouse queries they may silent surely be directed to entry the StoreLocation desk within the warehouse. however, the question from the company analyst against big statistics tables may silent likely access the replica of the desk there. This effects in a proliferations of skills access paths, and extra drudgery for the Optimizer. thankfully, Db2 AI for z/OS can provide the Optimizer the assistance it needs to build prudent access course decisions.the passage it Works
The sequence of events in Db2 AI for z/OS (See Reference 2) is frequently the following:
There are moreover a considerable number of user interfaces that supply the administrator visibility to the reputation of the accumulated SQL commentary efficiency records and mannequin scoring.abstract
IBM's computer learning for zOS (MLz) offering is getting used to notable result in Db2 edition 12 to increase the efficiency of analytical queries as well as operational queries and their linked functions. This requires management consideration, as you should examine that your enterprise is prepared to consume these ML and AI conclusions. How will you measure the charges and merits of using laptop learning? Which IT back team of workers exigency to be tasked to reviewing the outcome of model scoring, and perhaps approving (or overriding) the results? How will you overview and justify the assumptions that the application makes about access path decisions?
In other phrases, how neatly were you cognizant your records, its distribution, its integrity and your latest and proposed entry paths? this will assess the region the DBAs spend their time in assisting analytics and operational application efficiency.
# # #
John Campbell, IBM Db2 distinctive EngineerFrom "IBM Db2 AI for z/OS: raise IBM Db2 utility performance with computer learning"https://www.worldofdb2.com/activities/ibm-db2-ai-for-z-os-enhance-ibm-db2-application-efficiency-with-ma
Db2 AI for z/OShttps://www.ibm.com/guide/knowledgecenter/en/SSGKMA_1.1.0/src/ai/ai_home.html
Apple CEO Tim cook dinner speaks at the Anti-Defamation League's "on no account is Now" zenith in modern york city, manhattan, U.S., December 3, 2018. REUTERS/Brendan McDermid
(Reuters) - the manager executives of Apple Inc, Walmart Inc, IBM Corp and other most distinguished groups are becoming a member of a Trump administration advisory board that hopes to region together U.S. employees to deal with job practicing considerations and the worforce shift introduced with the aid of synthetic intelligence and automation, the U.S. Commerce department said on Wednesday.
President Donald Trump signed an executive order in July creating the 25-member board, co-chaired through adviser Ivanka Trump and Commerce Secretary Wilbur Ross, to wield workforce considerations together with “automation, and synthetic intelligence it is shaping many industries.” different chief executives becoming a member of the board are those of Lockheed Martin Corp, Siemens usa, home Depot Inc and Visa Inc.
The board contributors will serve unless 2020 and will drudgery with the administration’s countrywide Council for the American worker “to develop and region in compel a methodology to revamp the American team of workers to stronger meet the challenges of the 21st century.”
Trump’s executive order said “for too long, their country’s education and job training programs tolerate prepared american citizens for the economic system of the previous.”
Ivanka Trump stated in an announcement the administration desires “all americans to tolerate the capabilities and opportunities to cozy first rate paying jobs and successfully navigate technological disruptions and the unexpectedly altering nature of work.”
also becoming a member of are the manager executives of the Chamber of Commerce and country wide association of manufacturers, as well because the governors of Iowa and Indiana.
On Tuesday, the Bureau of Labor information stated U.S. job openings reached a record excessive in December at 7.3 million. The White residence says the job openings present “a mismatch between the competencies obligatory and people being taught, requiring instant consideration to back more americans enter the carcass of workers.”In August 2017, Trump disbanded two high-profile company advisory councils after a lot of chief executives halt in protest over his remarks blaming violence in Virginia on anti-racism activists as well as white nationalists.
Trump dissolved the American Manufacturing Council and the Strategic and policy discussion board after eight executives, including the CEOS of Campbell Soup Co and 3M Co, halt the panels. both councils tolerate been relocating to disband on their personal when Trump made his announcement on Twitter.
Reporting by David Shepardson; editing by Chizu Nomiyama and David Gregorio
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Skill Level: Foundation Status: Active
Low Cost: Not available
Summary:For individuals who demonstrate the basic scholarship and skill to successfully execute basic role or job related tasks associated with an IBM software product, solution, or related technology.
Initial Requirements:You must pass the IBM BPM Blueprint: IBM WebSphere Lombardi Edition (V 7.1), Administration exam ($200). The exam consists of 73 questions and has a 2 hour time limit. A passing score of 70% is required. Training is available but not required.
Continuing Requirements:None specified
See every Ibm Certifications
Vendor's page for this certification
Diversity and inclusion. Words repeated so often they’re virtually mantra in corporate America. Hardly a day goes by without some CEO extolling the virtues of a more diverse and inclusive workplace. But when it comes to showing their progress for the world to see, some of the biggest names in Silicon Valley are turning to a novel legal defense: asserting they’re trade secrets.
More and more, firms including Oracle and Palantir Technologies quarrel that detailed, government-mandated figures on the number of women and people of color they employ must remain confidential. Making them public, they say, would be tantamount to giving away proprietary technology and hand competitors a “road map” to poach talent.
So while tech companies often voluntarily give the public a glimpse of their diversity strategies, the tactic every too often lets them tolerate it both ways, according to Georgetown University’s Jamillah Bowman Williams, who explores the trend in the tech industry for a forthcoming paper. And as criticism grows over Silicon Valley’s bro culture and its want of minority representation, claiming the figures are too valuable an asset to participate could allow companies to pay lip service to diversity with itsy-bitsy or no accountability.
Also read| Google CEO Sundar Pichai focuses on job creation, to spend $13 bn on facilities
“This is almost fancy the extreme case of the industry case for diversity,” Williams, an associate professor at Georgetown University Law Center, said in an interview. By blocking the release of these figures, she writes that “companies can exercise this tactic to cloak gender and race disparities and tamper with the advancement of civil rights law and workplace equity.”
Changing the status quo has never been easy. A growing carcass of research shows diverse perspectives bring tangible benefits to firms that back them, yet black and female CEOs lead just 5 percent of S&P 500 companies, a number that’s tumbled in recent years. That’s compounded by the fact that almost three-quarters of corporate leaders pick protégés of the selfsame race or gender. Just terminal month, the Labor Department alleged Oracle shorted women and minority workers $400 million in wages by paying them less and steering them into lower-level positions. (Oracle declined to comment.)
Tech’s race and gender problem has become a focal point as the industry has risen to dominate big swaths of the U.S. economy. Everyone from Apple to Google and Facebook has publicly embraced the importance of diversity and made repeated commitments to become less homogeneous. Yet thus far, the industrywide efforts tolerate yielded scant progress.
The latest U.S. government data, released in 2016, reinforces the point. While the proportion of women has crept up, racial disparities persist. Black employees made up less than 3 percent of the Silicon Valley workforce and Hispanic workers accounted for less than 7 percent — itsy-bitsy improvement from prior years. (Another study showed that Asians drudgery in disproportionately high numbers in tech, but are the least likely to regain leadership roles. Those, as you might expect, are occupied mostly by white men.)
At issue is the EEO-1 employment data report, which firms must submit to the Equal Employment opportunity Commission each year. In her research, Williams looks at how tech firms responded when asked for them to be released. Her paper cites media inquiries covering more than 200 tech companies.
She writes that the vast majority, both big and small, refused to release their data and subsequent requests were often rebuffed with the trade-secrets argument. Because diversity has become such a buzzword in tech and firms routinely vie for the same, and often limited, pool of talent, they Say releasing workforce numbers that are too specific can region them at a disadvantage.
Palantir, the data mining startup co-founded by Peter Thiel, for example, aired those concerns in a 2017 missive to the Labor Department, adding it risked losing its investment in recruiting a diverse workforce. Rivals could note where it was making progress and which hiring initiatives it had undertaken, giving them a key to “raid” its growing ranks of women and minorities. Palantir didn’t respond to requests for comment.
Granted, trade-secret protection is a fairly common drill with a long history in corporate America. Applying it to diversity, though, is not only unusual, but fairly specific to tech, according to Gerardo Con Diaz, an assistant professor of science and technology studies at University of California at Davis.
Tech’s exercise of the trade-secret defense goes back to at least 2011. That year, CNN asked 20 tech companies for their diversity stats. Only three — Dell, Intel and Ingram Micro — complied. When CNN submitted liberty of Information Act requests to the government, Apple, Google, Hewlett-Packard, IBM and Microsoft invoked an exemption covering trade secrets, maxim disclosure would antecedent “competitive harm,” Williams says. (Apple, Google, HP and Microsoft tolerate since begun publicly releasing their EEO-1s and some moreover succumb annual diversity reports. IBM, which hasn’t made its report public, declined to comment.)
The drill has only gotten more popular. terminal year, when nonprofit betray from the focus for Investigative Reporting requested the EEO-1s from 211 tech companies, an overwhelming majority declined. Just 26 complied or had already released the reports. While the organization successfully sued for release of the data from federal contractors fancy Oracle and Palantir over their objections, most are silent free to exercise the trade-secret argument.
Federal regulations tolerate made it easier. After President Barack Obama signed a law in 2016 that let companies file trade secrets on a federal level, filings jumped 30 percent the next year, Williams found. Under the Trump administration, Labor Department officials provide firms with detailed instructions on how to invoke the exemption, she said. IBM went as far as to sue its former chief diversity officer terminal year to secrete her walkaway to Microsoft, claiming she would Take confidential data on its diversity initiatives and strategies with her. (The case was settled out of court.)
When it comes to diversity, Williams argues the legal rationale is flimsy. To be a trade secret, a company needs to note there’s value in keeping information confidential and that it might visage economic harm if it becomes public. Yet firms routinely participate parts of their demographic data and diversity strategies, on websites or at conferences, often for marketing and recruiting talent.
“This is not fancy McDonald’s and their sauce that goes on the astronomical Mac or the Google algorithm that’s the core of its industry strategy,” Williams said. “For workforce demographics, it’s unclear what’s so economically valuable to where it would be a detriment, other than reputational harm.”
In other words, the defense is often a convenient passage for companies to shield themselves from public scrutiny and embarrassment.
Palantir’s diversity numbers, which the Labor Department made public in January, achieve itsy-bitsy to quell that perception. Its report, compiled by the focus for Investigative Reporting, showed over three-quarters of its 1,328 professionals were men and just 1.4 percent were black. Palantir employed no female executives or senior officials and managers that year, either.
Tech companies, for their part, often point to the “pipeline” problem. That is, firms would admire to hire more women and people of color, if only there were enough qualified candidates. The numbers though, don’t quite add up. In 2014 to 2015, black students earning a bachelor’s degree in science, technology, engineering and mathematics accounted for 7.1 percent of graduates in those fields, according to the Department of Education. Yet in Silicon Valley, black employees made up less than half that.
That makes transparency crucial, Williams says. Without it, it’s arduous to know what the problems are — whether hiring and retention or pay and promotion — making it harder to fight workplace discrimination and change the culture. If anything, making workforce demographics public lets everyone note what works and what doesn’t. It can be a measuring stick to note whether the tens of millions of dollars Silicon Valley invests to recruit and retain more women and non-white workers is money well spent.
“If they’re really concerned about equity and diversity in the long term, not only in their company but in the industry and society as a whole,” she says, “then you would hope that they would tolerate a broader dialogue around it.”
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