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P2020-079 | IBM Initiate Master Data Service Support Mastery Test v1

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P2020-079 - IBM Initiate Master Data Service Support Mastery Test v1 - braindump

Vendor IBM
Exam Number P2020-079
Exam Name IBM Initiate Master Data Service Support Mastery Test v1
Questions 30 Q & A
Recent Update March 14, 2019
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P2020-079 exam Dumps Source : IBM Initiate Master Data Service Support Mastery Test v1

Test Code : P2020-079
Test Name : IBM Initiate Master Data Service Support Mastery Test v1
Vendor Name : IBM
Q&A : 30 Real Questions

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IBM IBM Initiate Master Data

IBM to acquire MDM supplier initiate methods | killexams.com Real Questions and Pass4sure dumps

IBM noted today that it plans to purchase initiate methods, one of the vital few remaining unbiased grasp information administration (MDM) vendors.

provoke methods, primarily based in Chicago, focuses on MDM and statistics integration application for healthcare and government groups. The proposed acquisition confirms rumors that IBM would make a play within the MDM market and springs just days after Informatica announced its buy of provoke competitor Siperian.

"With the addition of provoke's software and its trade potential, IBM will offer clients a complete solution for providing the information they need to enhance the neatly-being of patients at a lessen can charge," Arvind Krishna, generic manager of advice administration at IBM, observed in an announcement. "similarly, our executive consumers will now have much more capabilities for gathering and applying tips to serve citizens in a timely and effective manner."

The aim of MDM is to create a single view of grasp information -- most commonly client and product statistics -- to be used all the way through a company's operational, transactional and analytical applications.

IBM has invested heavily in its statistics management and analytics stack over the closing a couple of years, and the acquisition of initiate will continue that style. IBM competes with Oracle, SAP and now Informatica within the right away consolidating MDM market.

IBM is additionally likely trying to capitalize on the anticipated enhance in adoption of electronic medical facts, which provoke's MDM expertise supports by way of helping healthcare companies consolidate patient records.

Rob Karel, an analyst with Cambridge, Mass.-primarily based Forrester analysis, pointed out that each Siperian and provoke systems have struggled to expand their customer bases as independent carriers, making the fresh acquisitions a logical circulate for the two.

"We reached an inflection aspect," stated invoice Conroy, provoke's president and CEO, in a joint conference call with IBM. "could we as a small business keep up with the calls for of our consumers [for a more complete data management stack]?" The reply, apparently, turned into no.

The proposed acquisition should still improvement IBM in a couple of methods, wrote Ray Wang, an analyst with Altimeter neighborhood in San Mateo, Calif., in a weblog put up following the announcement. IBM will inherit initiate's "amazing" information integration platform and "deep healthcare and public sector event."

The acquisition should still additionally support IBM differentiate its MDM offering from rival Oracle, based on Wang -- but not earlier than IBM does the difficult work of harmonizing its numerous MDM applied sciences.

"today, IBM offers Infosphere MDM Server for PIM according to Trigo product assistance administration [PIM] and Infosphere MDM Server 9 in accordance with DWL for customer records integration [CDI]," Wang wrote. "initiate programs provides a third and equipped product into the lineup it truly is optimized for customer information."

Arvind Krishna, GM of IBM's suggestions management business, stated IBM plans to present both product records and consumer information MDM as separate choices.

initiate has 347 personnel and counts CVS/Caremark, Humana, and the North Dakota department of Human functions amongst its consumers. Neither business printed phrases of the deal, which is anticipated to shut within the first quarter.


IBM preps Watson AI features to run on Kubernetes | killexams.com Real Questions and Pass4sure dumps

Two of IBM’s Watson-branded assortment of computing device-intelligence features could be obtainable to run as standalone applications in the public or inner most cloud of your choice. IBM is offering these local Watson services atop IBM Cloud inner most for statistics, a combined analytics and information governance platform that may also be deployed on Kubernetes. 

Ruchir Puri, CTO and chief architect for IBM Watson, mentioned this was driven by way of consumer demand for machine discovering options that can be run the place consumer information already resides, customarily a multicloud or hybrid cloud environment (see related interview).

“as opposed to trying to move the statistics to a single cloud, and create a lockin in this open compute-atmosphere-pushed world, we are making purchasable AI and relocating it to the statistics,” Puri stated. The concept follows how Hadoop and other mass statistics-processing systems perform work on statistics in location, rather than moving the information to the processing.

at present, handiest two services—Watson Assistant and Watson OpenScale, which Puri described as “flagship products”—can be provided to consumers as standalone applications. Watson Assistant is used to construct “conversational interfaces” similar to chatbots; Watson OpenScale gives “automated neural community design and deployment,” or a means to train, installation, and oversee laptop researching models and neural networks in an enterprise surroundings.

IBM Cloud inner most for facts is composed of preconfigured microservices that run on a multinode, Kubernetes-based mostly IBM Cloud inner most cluster. Puri referred to the consumer is expected to perform their personal integration between IBM Cloud inner most for records and its native information outlets; such integration isn’t dealt with with the aid of IBM without delay. 

Puri made it clear these local Watson incarnations don't just forward API calls from a local proxy into IBM-hosted Watson. The customer runs its personal local incarnation of the service, delivered atop IBM Cloud inner most and working within the atmosphere of option. Supported environments include Amazon web features, Google Cloud, Microsoft Azure, and crimson Hat OpenShift. local Watson features are API-compatible with Watson services running in IBM Cloud.

What’s more likely to change is the effects delivered from local Watson incarnations versus the master version of Watson, since the native types needs to be periodically updated. Puri could not provide a particular timeline for a way commonly new models of native Watson features will come down the pike (quarterly, annually, and so on.), but he did verify that it can be up to date “on a comparatively usual foundation.”

The volume of equipment materials vital to dedicate to a Watson carrier instance varies reckoning on the workload. Some SLAs for the provided products encompass a prescription for the computing environment (memory, cores, GPUs) required for the preferred efficiency, Puri noted. both virtualized and bare-steel deployments are supported.

other Watson features might be made available in the community atop IBM Cloud inner most later. IBM plans later in 2019 to convey Watson capabilities Studio, which “discovers meaningful insights from unstructured textual content without writing any code,” and Watson herbal Language understanding, an automatic metadata extraction tool. The latter, Puri noted, is already used in Watson Assistant as an interior microservice, so most of the work to port it to a native incarnation has already been completed.

This new incarnation of Watson services provides a glimpse into probably the most reasons around IBM’s acquisition of red Hat. IBM Cloud deepest can use the Kubernetes-powered OpenShift as its base, and Watson’s features had been remodeled over a three-12 months duration around Kubernetes and containers, Puri mentioned. once purple Hat is totally beneath IBM’s umbrella, it seems likely that pink Hat’s infrastructure skills will free up cloud portability for future IBM records-centric features, Watson and otherwise.


IBM pronounces the Closing of its Acquisition of initiate techniques | killexams.com Real Questions and Pass4sure dumps

IBM recently announced the closing of its acquisition of provoke programs, a privately held utility company with a focus on statistics integrity and master statistics administration applied sciences. initiate's software helps valued clientele in lots of industries -- exceptionally in healthcare and govt -- share information across distinctive programs to enhance the services they deliver to patients, citizens and customers.

The closing comes less than a month after IBM's announcement on February three that it had entered right into a definitive agreement to acquire provoke.

organizations in both healthcare and executive have invested heavily in business utility purposes as they are trying to find more advantageous operational efficiency and productiveness. The proliferation of these functions has yielded big volumes of information about americans, locations and things. This information is fragmented throughout working environments and sometimes represented inconsistently. initiate's know-how helps acquire this facts no depend the place it resides to establish a single a single, multi-goal view of crucial business suggestions, which is also called master statistics.

provoke's utility helps healthcare shoppers work more intelligently and successfully with timely entry to affected person and clinical records. with the aid of including initiate's application to its application portfolio, IBM might be improved equipped to help clients draw on records from hospitals, doctors' places of work and payers to create a single, trusted shareable view of millions individual affected person statistics. The acquisition will additionally boost IBM's means to permit governments to access assistance from numerous methods and groups to provide more advantageous capabilities to residents.

"IBM's acquisition of provoke underscores our commitment to the use of superior know-how to support resolve complications faced through each healthcare groups and governments world wide," noted Arvind Krishna, time-honored supervisor, tips administration, IBM. "via stronger entry to depended on counsel, these shoppers can serve americans better and more effectively."

initiate's healthcare purchasers consist of payers and providers in addition to dealers promoting prescription medicine. among these valued clientele are Alberta Ministry of fitness and wellness, BMI Healthcare (UK), Calgary fitness location, CVS/Caremark, Humana, Ochsner fitness system, the State of North Dakota's department of health and Human capabilities and the institution of Pittsburgh clinical core.

consistent with the business's utility strategy, initiate's technologies and operations might be built-in into IBM's advice management business, expanding its capabilities for establishing, supplying and examining depended on counsel for valued clientele throughout all industries and geographic regions. initiate personnel will be a part of IBM.

through its acquisition of provoke IBM is additionally extending its capabilities in enterprise analytics -- one in all its fundamental funding areas -- through improving its capacity to deliver a foundation of trusted suggestions. besides provoke, IBM has invested $10 billion in 14 strategic acquisitions to build its enterprise analytics portfolio on the grounds that 2005. These acquisitions delivered powerful effects in 2009, generating 9 % salary increase at consistent foreign money. among the many business's choices during this enviornment is a brand new company Analytics and Optimization Consulting company which is supported by way of crew of four,000 consultants and a community of analytics answer facilities.


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IBM GDPS V3.3: Improving Disaster Recovery Capabilities to Help Ensure a Highly Available, Resilient Business Environment | killexams.com real questions and Pass4sure dumps

Overview

GDPS(TM) is IBM's premier continuous availability and disaster recovery solution. IBM is proud to announce the general availability of GDPS V3.3. Available on January 25, 2006, GDPS V3.3 offers:

Enhanced availability with autonomic detection of "Soft Failures" on disk control units to trigger a HyperSwap(TM)Exploitation of XRC enhancements for increased scalability in large I/O configurations and configurations with intensive I/O characteristicsEase of use to support z/OS® V7 XRC+ staging data setsExpanded functionality to provide data consistency between disk and duplexed Coupling Facility (CF) structures

In addition, IBM is reannouncing the general availability of GDPS/Global Mirror (GDPS/GM). Based upon IBM TotalStorage® Global Mirror technology, IBM GDPS/Global Mirror automation can help simplify data replication across any number of IBM System z(TM) and/or open system servers to a remote site that can be at virtually any distance from the primary site. This can help ensure rapid recovery and restart capability for your IBM System z9(TM), zSeries®, and open systems data for testing purposes as well as both planned and unplanned outages. GDPS/GM also provides automation facilities to reconfigure your System z9 and zSeries servers and to restart the systems that run on these servers for testing and for actual disaster recovery.

GDPS/Global Mirror automation technology is designed to manage the IBM TotalStorage Global Mirror copy technology, monitor the mirroring configuration, and automate management and recovery tasks.

GDPS is also providing a new "three-site" solution combining the benefits of GDPS/PPRC using Metro Mirror with GDPS/Global Mirror using Global Mirror technology. This solution, GDPS Metro/Global Mirror, is designed to provide the near-continuous availability aspects of HyperSwap and help prevent data loss within the Metro Mirror environment, along with providing a long-distance disaster recovery solution with no response-time impact. Metro/Global Mirror has been available via an RPQ since October 31, 2005.

More detailed information on the GDPS service offerings is available on the Internet at

http://www.ibm.com/servers/eserver/zseries/gdps

Availability date

Available now (as of January 25, 2006):RCMF/PPRC V3.3GDPS/PPRC V3.3GDPS/PPRC HyperSwap Manager V3.3RCMF/XRC V3.3GDPS/XRC V3.3GDPS/Global Mirror V3.3GDPS Metro/Global Mirror V3.3

Description

IBM Global Services continues to enhance GDPS with:

Extended HyperSwap functionality with IOS timing triggerImproved availability with enhanced recovery support in a CF structure duplexing environmentPerformance improvements for System Logger in a z/OS Global Mirror (previously known as XRC) environmentScalability improvements for XRCUnlimited distance solution for z/OS and open data with the new GDPS/Global Mirror offering

Unplanned HyperSwap IOS timing trigger

If a disk subsystem experiences a "hard failure" such as a boxed device, rank array failure, or disk subsystem failure, current versions of GDPS/PPRC and GDPS/PPRC HyperSwap Manager (GDPS/PPRC HM) are designed to detect this and automatically invoke HyperSwap to transparently switch all primary PPRC disks with the secondary disks within seconds.

Occasionally, no signal comes back after an I/O operation has started. The I/O starts, but it is as if it doesn't end. There are no errors returned. The only indication that something is wrong is that the z/OS I/O Missing Interrupt Handler (MIH) detects this and generates a message. It is then up to the operator to see the message and figure out what to do. By that time, it is possible that the transactions waiting for I/O and holding on to resources can in turn cause other transactions to wait, and can bring the entire system to a stop.

The HyperSwap IOS timing trigger is designed to allow HyperSwap to be invoked automatically when user-defined I/O timing thresholds are exceeded. In a matter of seconds, transactions can now resume processing on the secondary disk, providing availability benefits and avoiding operator intervention.

The HyperSwap IOS Timing trigger requires APAR OA11750 available on z/OS V1.4.

HyperSwap is available with the GDPS/PPRC and GDPS/PPRC HyperSwap Manager offerings.

GDPS enhanced recovery support

In the event of a primary site failure, the current GDPS/PPRC cannot ensure that the CF structure data may be time-consistent with the "frozen" copy of data on disk, so GDPS must discard all CF structures at the secondary site when restarting workloads. This results in loss of "changed" data in CF structures. Users must execute potentially long-running and highly variable data recovery procedures to restore the lost CF data.

GDPS enhanced recovery is designed to ensure that the secondary PPRC volumes and the CF structures are time consistent, thereby helping to provide consistent application restart times without any special recovery procedures.

If you specify the FREEZE=STOP policy with GDPS/PPRC and duplex the appropriate CF structures, when CF structure duplexing drops into simplex, GDPS is designed to direct z/OS to always keep the CF structures in the site where the secondary disks reside. This helps to insure the PPRC volumes and recovery-site CF structures are time consistent thereby providing consistent application restart times without any special recovery procedures. This is especially significant for customers using DB2® data sharing, IMS(TM) with shared DEDB/VSO, or WebSphere® MQ shared queues.

GDPS enhanced recovery support requires z/OS APAR OA11719, available back to z/OS V1.5.

Improving performance

System logger provides new support for XRC+ by allowing you to choose asynchronous writes to staging data sets for logstreams. Previously, all writes had to be synchronous. This limited the throughput for high-volume logging applications such as WebSphere, CICS®, and IMS. The ability to do asynchronous writes can allow the use of z/OS Global Mirror (XRC) for some applications for which it was not previously practical. XRC+ is available on z/OS and z/OS.e V1.7.

Refer to Preview: IBM z/OS V1.7 and z/OS.e V1.7: World-class computing for On Demand Business, Software Announcement 205-034 dated February 15, 2005.

GDPS/XRC has extended its automation to support XRC+. It is designed to provide the ability to configure and manage the staging data set remote copy pairs.

Scalability

GDPS/XRC support is being extended to help improve XRC scalability for large systems by:

Write PacingAPAR OA09239 provides for the new XRC Write Pacing support. By automatically inserting delays into the I/O response for high-intensity update applications, XRC can then prevent the secondary disk in the remote site from falling behind, delaying the RPO for all applications.

Exploitation of the Write Pacing function on GDPS/XRC systems requires APAR 65 (AG31D65), which is fully compatible with all existing supported GDPS/XRC software levels.

Parallel executionPreviously, GDPS typically processed all XRC System Data Movers (SDMs) in sequence within an LPAR. With GDPS V3.3, many XRC commands can now be done in parallel across all the SDMs. A parallel execution of XRC commands across all SDMs allows for improved responsiveness, improved usability, and reduced recovery time.

Support for more than 14 SDMsPreviously, XRC supported up to 14 coupled SDMs, split across up to five SDM address spaces per z/OS LPAR. New support expands this to allow up to 14 Coupled eXtended Remote Copy (CXRC) sessions. Each CXRC can consist of one or more XRC logical sessions. Additionally, Multiple eXtended Remote Copy (MXRC) currently allows the user to run up to five XRC logical sessions within a single LPAR. This enhancement will allow significantly more SDMs, thereby increasing the number of parallel paths to transfer data. This allows GDPS/XRC to handle larger configurations and higher throughputs while maintaining the client's service level agreements. More information on CXRC can be found in z/OS DFSMS Advanced Copy Services (SC35-0428-09).

The planned availability of GDPS support for more than 14 coupled SDMs is second quarter 2006.

XRC Performance Monitor (XPM) updates

In addition to the above enhancements, XPM is being modified to support the new larger master sessions. XPM will have the ability to display (via the Interactive Interface) and process (via the Exception Batch Monitor) cluster-level data. The Interactive Interface will be modified to recognize and display consolidated cluster data and larger values for data-movement-related statistics. The planned availability of the XPM updates is March 31, 2006.

GDPS V3.3 is available as of January 25, 2006. GDPS is designed to work in conjunction with the z9-109, z990, z890, z900, and z800 servers. For a complete list of other supported hardware platforms and software prerequisites, refer to the GDPS Web site

http://www.ibm.com/server/eserver/zseries/gdpsGDPS/Global Mirror has been available as of October 2005. Contact your IBM representative or send an e-mail to GDPS@us.ibm.com for information regarding ordering GDPS.

GDPS/Global Mirror was previewed in IBM zSeries 990 and 890 FICON(TM) enhancements Hardware Announcement 105-012 , dated January 25, 2005.

Accessibility by people with disabilities

A U.S. Section 508 Voluntary Product Accessibility Template (VPAT) containing details on the product's accessibility compliance can be requested via IBM's Web site

http://3.ibm.com/able/product_accessibility/index.html

Product positioning

The GDPS solution suite includes six different service offerings to meet different customer requirements:

RCMF/PPRCRemote Copy Management Facility (RCMF) provides management of the remote copy environment and disk configuration from a central point of control. The RCMF/PPRC offering can be used to manage a PPRC (Metro Mirror) remote copy environment.

RCMF/XRCRCMF/XRC is a disaster recovery offering which can be used to manage an XRC (z/OS Global Mirror) remote copy environment.

GDPS/PPRC HyperSwap ManagerGDPS/PPRC HyperSwap Manager provides either a single-site near-continuous availability solution or a multi-site disaster recovery solution. It is an entry-level solution available at a cost-effective price. GDPS/PPRC HyperSwap Manager is designed to allow customers to increase availability and provide applications with continuous access to data. Today, GDPS/PPRC HyperSwap Manager appeals to zSeries customers who require continuous availability and extremely fast recovery.

Within a single site, or multiple sites, GDPS/PPRC HyperSwap Manager extends Parallel Sysplex® availability to disk subsystems by masking planned and unplanned disk outages caused by disk maintenance and disk failures. It also provides management of the data replication environment and automates switching between the two copies of the data without causing an application outage, therefore providing near-continuous access to data.

The GDPS/PPRC HyperSwap Manager solution is a subset of the full GDPS/PPRC solution, designed to provide a very affordable entry point to the full family of GDPS/PPRC offerings. It features specially priced limited-function Tivoli® System Automation and NetView® software products, thus satisfying the GDPS software automation prerequisites with a lower price and a cost-effective entry point to the GDPS family of offerings. Users who already have the full-function Tivoli System Automation and NetView software products may continue to use them as the prerequisites for GDPS/PPRC HyperSwap Manager.

A customer can migrate from a GDPS/PPRC HyperSwap Manager implementation to the full-function GDPS/PPRC capability as business requirements demand shorter recovery time objectives. The initial investment in GDPS/PPRC HyperSwap Manager is protected when you choose to move to full-function GDPS/PPRC by leveraging the existing GDPS/PPRC HyperSwap Manager implementation and skills.

GDPS/PPRCGDPS/PPRC complements a multisite Parallel Sysplex implementation by providing a single, automated solution to dynamically manage storage subsystem mirroring, disk and tape, processors, and network resources. It is designed to help a business attain continuous availability and near-transparent business continuity (disaster recovery) with data consistency and no or minimal data loss. GDPS/PPRC is designed to minimize and potentially eliminate the impact of any failure, including disasters, or a planned outage.

GDPS/PPRC is a full-function offering that includes the capabilities of GDPS/PPRC HM. It is designed to provide an automated end-to-end solution to dynamically manage storage system mirroring, processors, and network resources for planned and unplanned events that could interrupt continued IT business operations.

The GDPS/PPRC offering is a world-class solution built on the z/OS platform and yet can manage a heterogeneous environment.

GDPS/PPRC is designed to provide the ability to perform a controlled site switch for both planned and unplanned site outages, with no or minimal data loss, maintaining full data integrity across multiple volumes and storage subsystems and the ability to perform a normal Data Base Management System (DBMS) restart - not DBMS recovery - in the second site. GDPS/PPRC is application-independent and therefore can cover your complete application environment.

GDPS/XRCBased upon IBM TotalStorage z/OS Global Mirror (Extended Remote Copy, or XRC), GDPS/XRC is a combined hardware and z/OS software asynchronous remote-copy solution. Consistency of the data is maintained via the Consistency Group function within the System Data Mover. GDPS/XRC includes automation to manage remote copy pairs and automates the process of recovering the production environment with limited manual intervention, including invocation of CBU, thus providing significant value in reducing the duration of the recovery window and requiring less operator interaction. GDPS/XRC is capable of the following attributes:

Disaster recovery solutionRTO between an hour to two hoursRPO less than one minuteProtects against localized or regional disasters, depending on the distance between the application site and the disaster recovery site (distance between sites is unlimited)Minimal remote copy performance impactGDPS/XRC is well suited for large System z workloads and can be used for business continuance solutions, workload movement, and data migration.

Because of the asynchronous nature of XRC, it is possible to have the secondary disk at greater distances than would be acceptable for Metro Mirror (synchronous PPRC). Channel extender technology can be used to place the secondary disk thousands of kilometers away.

In some cases an asynchronous disaster recovery solution is more desirable than one that uses synchronous technology. Sometimes applications are too sensitive to accept the additional latency incurred when using synchronous copy technology.

GDPS/Global Mirror

The latest member of the GDPS suite of offerings, GDPS/Global Mirror offers a multisite, end-to-end disaster recovery solution for your IBM z/OS systems and open systems data.

IBM GDPS/Global Mirror automation technology can help simplify data replication across any number of System z(TM) systems and/or open system servers to a remote site that can be at virtually any distance from the primary site. This can help ensure rapid recovery and restart capability of your environment for both testing and disaster recovery, and restart capability for your open systems environment for testing and disaster recovery. Being able to test and practice recovery allows you to build skills in order to be ready when a disaster occurs.

GDPS/Global Mirror automation technology is designed to manage the IBM TotalStorage Global Mirror copy services and the disk configuration, monitor the mirroring environment, and automate management and recovery tasks. It can perform failure recovery from a central point of control. This can provide the ability to synchronize System z and open systems data at virtually any distance from your primary site.

The point-in-time copy functionality offered by the IBM TotalStorage Global Mirror technology allows you to initiate a restart of your database managers on any supported platform, to help reduce complexity and avoid having to create and maintain different recovery procedures for each of your database managers.

All this helps provide a comprehensive disaster recovery solution.

The six offerings listed above can be combined as follows:

GDPS/PPRC used with GDPS/XRC (GDPS PPRC/XRC)GDPS PPRC/XRC provides the ability to combine the advantages of metropolitan-distance Business Continuity and regional or long-distance Disaster Recovery. This can provide a near-continuous availability solution with no data loss and minimum application impact across two sites located at metropolitan distances, and a disaster recovery solution with recovery at an out-of-region site with minimal data loss.

A typical GDPS PPRC/XRC configuration has the primary disk copying data synchronously to a location within the metropolitan area using Metro Mirror (PPRC), as well as asynchronously to a remote disk subsystem a long distance away via z/OS Global Mirror (XRC). This enables a z/OS three-site high availability and disaster recovery solution for even greater protection from planned and unplanned outages.

Combining the benefits of PPRC and XRC, GDPS PPRC/XRC enables:

HyperSwap capability for near-continuous availability for a disk control unit failureOption for no data lossData consistency to allow restart, not recoveryLong-distance disaster recovery site for protection against a regional disasterMinimal application impactGDPS automation to manage remote copy pairs, manage a Parallel Sysplex configuration, and perform planned as well as unplanned reconfigurationsThe same primary volume is used for both PPRC and XRC data replication and can support two different GDPSs: GDPS/PPRC for metropolitan distance and business continuity, and GDPS/XRC for regional distance and disaster recovery.

The two mirroring technologies and GDPS implementations work independently of each other, yet provide the synergy of a common management scheme and common skills.

Since GDPS/XRC supports zSeries data only (z/OS, Linux on zSeries), GDPS XRC is a zSeries solution only.

GDPS/PPRC used with GDPS/Global Mirror (GDPS Metro/Global Mirror)

GDPS Metro/Global Mirror has the benefit of being able to manage across the configuration all formats of data, as Global Mirror is not limited to zSeries formatted data.

GDPS Metro/Global Mirror combines the benefits of GDPS/PPRC using Metro Mirror, with GDPS/Global Mirror using IBM TotalStorage Global Mirror. A typical configuration has the secondary disk from a Metro Mirror remote copy configuration in turn becoming the primary disk for a Global Mirror remote copy pair. Data is replicated in a "cascading" fashion.

Combining the benefits of PPRC and Global Mirror, GDPS Metro/Global Mirror enables:

HyperSwap capability for near-continuous availability for a disk control unit failureOption for no data lossMaintain disaster recovery capability after a HyperSwapData consistency to allow restart, not recovery, at either site 2 or site 3Long-distance disaster recovery site for protection against a regional disasterMinimal application impactGDPS automation to manage remote copy pairs, manage a Parallel Sysplex configuration, and perform planned as well as unplanned reconfigurations

In addition, GDPS Metro/Global Mirror can do this for both zSeries as well as open data, and provide consistency between them.

GDPS Metro/Global Mirror is only available via RPQ.

Reference information

Enhancements to the IBM zSeries 900 Family of Servers, Hardware Announcement 101-308 , dated October 4, 2001New Functions for IBM zSeries Servers Enhance Connectivity, Hardware Announcement 102-209 , dated August 13, 2002IBM Introduces the IBM zSeries 990 Family of Servers, Hardware Announcement 103-142 , dated May 13, 2003IBM enhances the IBM zSeries 990 family of servers, Hardware Announcement 103-280 , dated October 7, 2003IBM Implementation Services, Installation Services, and Operational Support Services Now Available for Selected IBM Products, Services Announcement 603-015 , dated June 17, 2003IBM TotalStorage PtP VTS includes FICON connectivity for increased performance and distance, Hardware Announcement 103-204 , dated July 15, 2004IBM enhances the IBM zSeries 990 family of servers, Hardware Announcement 104-118 , dated April 7, 2004Significant IBM zSeries mainframe security, SAN, and LAN innovations, Hardware Announcement 104-346 , dated October 7, 2004IBM zSeries 990 and 890 FICON enhancements, Hardware Announcement 105-012 , dated January 25, 2005Preview: IBM z/OS V1.7 and z/OS.e V1.7: World-class computing for On Demand Business, Software Announcement 205-034 , dated February 15, 2005GDPS/PPRC HyperSwap Manager: Providing continuous availability of consistent data, Marketing Announcement 305-015 , dated February 15, 2005IBM System z9 109 - The server built to protect and grow with your on demand enterprise, Hardware Announcement 105-241 , dated July 27, 2005IBM Implementation Services for Geographically Dispersed Parallel Sysplex(TM) for managing disk mirroring using IBM Global Mirroring, Services Announcement 605-035 , dated October 18, 2005

Order now

To order, contact the Americas Call Centers or your local IBM representative.

To identify your local IBM representative, call 800-IBM-4YOU (426-4968).

Phone: 888-426-4343. (Select option for IBMService Offering.)Internet: If you are an IBM Business Partner, sign onto PartnerWorld. From Shortcuts, selectOnline Technical Request. The Americas Call Centers, our national direct marketing organization, can add your name to the mailing list for catalogs of IBM products.

Business Partner information

If you are a Direct Reseller - System Reseller acquiring products from IBM, you may link directly to Business Partner information for this announcement. A PartnerWorld ID and password are required (use IBM ID).

BP Attachment for Announcement Letter 306-024

Related Thomas Industry Update Thomas For Industry

AWS CodeCommit triggers bolster use of Git | killexams.com real questions and Pass4sure dumps

AWS CodeCommit was launched in 2015, allowing developers to run repositories of Git on AWS. But the announcement was mostly quiet because it didn't add any special features. However, I suspected it marked a first step in integrating a cloud-based workflow for Git on AWS. That has now come to fruition -- with support for triggers based on events in a Git repository in AWS CodeCommit.

Triggers allow IT teams to respond to events that happen in a repository, such as a developer pushing out new code. The GitFlow methodology, along with trigger use, allow developers to properly implement both continuous integration -- testing code as it is committed -- and continuous delivery -- deploying code as soon as it is verified and committed. With CodeCommit, developers can use Git on AWS to deploy new versions to both development and production environments entirely by pushing code to specified branches.

One very common use case for triggers is to automatically build new releases of code pushed to either a development or master branch of a repository. Developers can completely automate testing and deploy a Node.js application from AWS CodeCommit directly to AWS Elastic Beanstalk.

The Lambda test function

Make sure code validates a given set of tests before deploying it from a repository. Unit tests or even general "lint" compilations can prevent simple syntax errors. For Node, I prefer to use the simple ESLint script -- installable through npm. This "linter" checks to make sure basic syntax is obeyed. It also checks for common errors like typos and the use of reserved keywords where they're not allowed.

Before AWS CodeCommit executes a Lambda function, it must have the appropriate access. Developers need to create a new JSON permission file, like this one:

{

   "FunctionName": "MyCodeCommitFunction",

   "StatementId": "1",

   "Action": "lambda:InvokeFunction",

   "Principal": "codecommit.amazonaws.com",

   "SourceArn": "arn:aws:codecommit:us-east-1:80398EXAMPLE:MyDemoRepo",

   "SourceAccount": "80398EXAMPLE"

}

 Then, upload it through the AWS command-line interface.

aws lambda add-permission --cli-input-json file://AllowAccessfromMyDemoRepo.json

The data your Lambda function will receive looks like:

{ Records: [

 {

   awsRegion: 'us-east-1',

   codecommit: {

    references: [ {

      commit: '0000000000000000000000000000000000000000',

      ref: 'refs/heads/all'

    } ]

   },

   eventId: '123456-7890-ABCD-EFGH-IJKLMNOP',

   eventName: 'TriggerEventTest',

   eventPartNumber: 1,

   eventSource: 'aws:codecommit',

   eventSourceARN: 'arn:aws:codecommit:us-east-1:80398EXAMPLE:MyDemoRepo',

   eventTime: '2016-03-08T20:29:32.887+0000',

   eventTotalParts: 1,

   eventTriggerConfigId: ‘123456-7890-ABCD-EFGH-IJKLMNOP',

   eventTriggerName: 'MyCodeCommitFunction',

   eventVersion: '1.0',

   userIdentityARN: 'arn:aws:sts::80398EXAMPLE:assumed-role/DevOps/cmoyer'

} ] }

There are some important fields to observe here. The "userIdentityARN" indicates the user who initiated the push. At a minimum, the Lambda function should log this so developers know who initiated the build request. But developers can also authorize who is allowed to initiate new build requests. For example, the Lambda function can be designed to only build new versions to production initiated by developers who are trusted to push production code.

AWS CodeCommit was launched in 2015, allowing developers to run repositories of Git on AWS.

The second important field to note here is under "code commit/references/ref," which shows the branch or branches that were committed.

This check needs to examine code and run a custom command, which may end up taking longer than five minutes. Instead, I use my Lambda function to execute an EC2 Container Service (ECS) task. This also allows developers to trigger other events, such as building and deploying new releases right through an ECS task.

This Lambda function triggers an ECS task:

/**

 * Execute an ESLint Task

 * to check the Code that was committed

 */

var AWS = require('aws-sdk');

var ecs = new AWS.ECS({ region: 'us-east-1' });

 

exports.handler = function(data, context){

   console.log(JSON.stringify(data));

 

   var counter = data.Records.length;

   function done(){

      counter--;

      if(counter === 0){

         context.succeed('OK');

      }

   }

 

   data.Records.forEach(function processRecord(record){

      console.log('CHANGES from', record.userIdentityARN);

      record.codecommit.references.forEach(function(ref){

       counter++;

       ecs.runTask({

          taskDefinition: ‘ECSBuilder',

          overrides: {

             containerOverrides: [

               {

                  command: [

                     ‘./checkBuild',

                     record.eventSourceARN.split(':')[5],

                    ref.ref.replace(‘refs/heads‘,''),

                    ref.commit,

                  ],

                  name: ‘ECSBuilder',

               },

             ],

          },

          startedBy: 'ESLint: ' + record.userIdentityARN.split('/')[1],

       }, function(err, resp){

          if(err){

             console.error('ERROR', err);

          } else {

             console.log('Successfully started', resp);

          }

          done();

      });

      });

     done();

   });

}

Note the use of a "counter" function; a single push event could actually trigger multiple repository updates. This code makes certain to test them all.

Adding triggers to a CodeCommit repository

After creating the Lambda function, developers configure CodeCommit to fire the Lambda function on specific events. This can be configured in multiple ways, but it is generally best to make sure the CodeCommit repository fires the event for any push events to the repository. The function can also be configured to filter pushes to specific branches.

Click on the newly added "triggers" option and choose "Create trigger" to get started.

Create a trigger in AWS CodeCommit Developers can create a trigger for a Lambda function in AWS CodeCommit.

Next, fill out the details to create the trigger:

Configure the Lambda trigger. Fill in the details to set up the trigger for the Lambda function.

In this example, the function only executes on a push to existing branches. If a development cycle uses GitFlow, developers may also need to include "Create branch or tag" to make sure new release branches also trigger this function. In both cases, make sure to fill out the branch names either to "All branches" or choose specific branches. Choose "AWS Lambda" as the service to send to, and select the Lambda function. Once everything is set, use the "Test trigger" option to make sure the code repository has access. If it doesn't, retrace the steps to authorize the CodeCommit repository to call Lambda functions.

Creating an ECS task

The final step is to create an ECS task and authorize the Lambda role to execute it. ECS tasks execute Docker repositories from Amazon EC2 Container Registry (ECR), so the easiest method is to push a Docker image up to ECR where the task can run it.

A simple Docker script may look like this:

FROM node:5.6.0

 

# make sure apt is up to date

RUN apt-get update

 

# Install global packages

RUN npm install --global grunt-cli eslint

 

# install Git and curl

# Python is required by the "memcached" node module

RUN apt-get install -y Git Git-core curl python build-essential

 

# Create a bashrc

RUN touch ~/.bashrc

 

# Copy our bundled code

COPY . /usr/local/app

 

# Set the working directory to where we installed our app

WORKDIR /usr/local/app

This script needs to be in a directory with the script to check the build within the repository. In the Lambda script we created above, we run a script called "checkBuild" that contains the last part of the repository's name -- "eventSourceARN" -- as well as a reference to the commit branch and the exact commit ID. With these three items, developers can build a check script that examines the exact version that pushes the trigger.

The checkBuild.sh script should look like this:

#!/bin/sh

REPOSITORY=$1

BRANCH=$2

COMMIT=$3

 

# Add the Known Host

ssh-keyscan -H Git-codecommit.us-east-1.amazonaws.com >> ~/.ssh/known_hosts

 

# Check out the repository

Git clone ssh://USERNAME@Git-codecommit.us-east-1.amazonaws.com/v1/repos/${REPOSITORY} build -b ${BRANCH}

 

cd build && Git checkout ${COMMIT} && eslint .

Make sure to replace "USERNAME" with a valid Identity and Access Management (IAM) user that has secure shell (SSH) access to the AWS CodeCommit repositories you're testing. It's best to create a new IAM user specifically for this build service, give it access to the repositories and upload an SSH public key for it.

Once this is set, developers can build and deploy the Docker image to the ECR and then use that to create the ECS task. The Lambda function sets up the command, so the task just needs to point to the Docker repository for the image.

Although this code runs "ESlint" on the checked out code, it neither notifies anyone of the results nor does it automatically deploy anything if the build succeeds. Unit tests can also be executed here to make sure everything passes. A good way to do this is to build notifications right into grunt to make sure the results are sent to developers through integrations with Slack, Flowdock or email notifications.

This one new option from AWS for adding basic hook support for CodeCommit can open up a whole new world of opportunities for using Git on AWS for continuous integration and deployment.


Web Services and SOA | killexams.com real questions and Pass4sure dumps

People sometimes ask what a service-oriented architecture enables today that could not have been done with the older, proprietary integration stacks of the past 5 to 15 years, such as those from Tibco, IBM, or Vitria. One such ability is the greater degree of interoperability between heterogeneous technology stacks that is made possible by the standards SOA is built on, such as Web services and BPEL. Although interoperability is only one facet of the SOA value proposition, it is one that has become increasingly more important, due in large part to the evolving IT environment, merger and acquisition activity, and increased partner connectivity.

Building business solutions for SOA requires the ability to secure data exchanged over a network, and control access to services in an environment where long-running business processes and asynchronous services are increasingly common. To meet these key requirements, two WS-* standards have moved to the forefront: WS-Security for authentication and encryption of service data, and WS-Addressing for correlation of messages exchanged with asynchronous services.

As these standards have begun to take hold, many commercial technologies have been introduced that add support for them. Likewise, many developers are implementing them in custom applications or with open source frameworks. Furthermore, standards that are logically layers above core Web services and security are referencing them. For example, the WS-BPEL specification is a Web service orchestration language with rich support for both synchronous and asynchronous services. BPEL, as it is commonly known, is highly complementary with WS-Security and WS-Addressing.

This article focuses on interoperability with asynchronous messaging and on the security challenges of using BPEL processes to orchestrate Web services deployed onto various technology platforms. The specific example used is BPEL processes deployed on Oracle BPEL Process Manager, invoking services implemented with Microsoft .NET Windows Communication Foundation (WCF).

WS-BPEL and WS-Addressing Interoperability ChallengesFor those readers who may not be versed in asynchronous service requirements, we will first provide some background on why a standard such as WS-Addressing is needed. The core Web services standards, including WSDL, SOAP, and XML schema are sufficient for synchronous service operations in which a client of a service sends a request and either gets no response at all (a "one-way" operation) or gets a result back as the output of the operation itself. In either case, the operation completes the interaction between the service client and the service itself.

However, for logical operations that may take a long time to complete, the concept of an asynchronous operation whereby the client initiates a service operation but does not wait for an immediate response makes sense. At some later time, the service will call the client back with the result of the operation - or with an error or exception message. In this case, the client must pass at least two pieces of information to the service: a location where the service can call the client back with the result, and an identifier of some sort that will allow the client to uniquely identify the operation with which the callback is associated. Early in the development of Web services standards, individual projects would include custom mechanisms for interacting with asynchronous services; however, this meant that developers had to explicitly code this support, and interoperability among toolkits was nonexistent.

WS-Addressing provides a standard for describing the mechanisms by which the information needed to interact reliably with asynchronous Web services can be exchanged. In the long term, this promises seamless interoperability, even for asynchronous services, between clients and services implemented on different technology stacks.

The main purpose of WS-Addressing is to incorporate message-addressing information into SOAP messages (for example, where the provider should send a response). SOAP is an envelope-encoding specification that represents Web service messages in a transport neutral format. However, SOAP itself does not provide any features that identify endpoints. The usual endpoints, such as message destination, fault destination, and message intermediary are delegated up to the transport layer. Combining WS-Addressing with SOAP creates a complete messaging specification. WS-Addressing specifies that address information be stored in SOAP headers in an independent manner, instead of embedding that information into the payload of the message itself. WS-Addressing is complemented by two other specifications, WS-Addressing SOAP Binding, and WS-Addressing WSDL Binding which specify how to represent the WS-Addressing properties into SOAP and WSDL respectively.

At a high level, WS-Addressing defines an EndpointReference construct to represent a Web service endpoint. It also defines a set of headers, ReplyTo, FaultTo, RelatesTo, and MessageId which are used to dynamically define an asynchronous message flow between endpoints.

BPEL relies on WS-Addressing to enhance endpoint representation and asynchronous Web services invocations. However, because WS-Addressing has evolved through several versions, interoperability can be a challenge. Today up to four different WS-Addressing versions are commonly used-three versions of the specification are named by their release date: the March 2003 version, the March 2004 version, and the August 2004 version, developed before the specification moved to W3C. The 1.0 version, recently completed in May 2006, was developed after the specification went under the umbrella of W3C. After moving to W3C, the specification split into multiple parts: a core specification, and two specifications that describe bindings for SOAP and WSDL.

Explicit vs. Implicit Addressing MechanismsIdeally, all server platforms would support all possible versions of WS-Addressing, but we are forced to live (and code) in the real world. At this time, many servers support one or more active WS-Addressing versions, but it is still all too possible that a service and client will be built on platforms that support incompatible WS-Addressing versions. However, interoperability is possible with a minimal amount of developer effort.

When the same WS-Addressing version is supported by both the process (client) and service layers, it is called "implicit" addressing because the developer need only state at the metadata level which version of WS-Addressing should be used to correlate asynchronous messages. In this case, WS-Addressing manipulation is completely transparent to the BPEL process itself, and the SOAP layer simply adds the requested SOAP headers as needed.

However, in order to interoperate with WS-Addressing versions not implicitly supported, a server should provide an explicit mechanism by which developers can build and attach WS-Addressing to SOAP messages easily. The following section describes an explicit addressing mechanism used to achieve asynchronous service interoperability between Microsoft WCF using WS-Addressing 1.0 and Oracle BPEL Process Manager using WS-Addressing March 2003; however, the same principles should hold true for interoperability between any two BPEL and Web service toolkits.

WS-Addressing Interoperability Example: WCF and WS-Addressing Microsoft's Windows Communication Foundation (WCF) represents the next generation of distributed programming and service-oriented technologies built on top of the Microsoft .NET platform for the upcoming Windows Vista release. WCF unifies the existing set of distributed programming technologies such as ASP .NET Web services, .NET Remoting, COM+, and so on, under a common, simple, and service-oriented programming model. WCF implements a vast set of WS-* protocols, including WS-Addressing 1.0.

To demonstrate explicit interoperability with WCF, we use Oracle BPEL Process Manager. It has had rich support for WS-Addressing for several years and includes WS-Addressing of March 2003, March 2004, and August 2004. This example uses BPEL with WS-Addressing March 2003 and WCF with WS-Addressing 1.0 to demonstrate explicit addressing support. Consider the WS-Addressing interoperability scenario illustrated in Figure 1.

The following explains the occurrences in Figure 1:

  • A BPEL process exposes WS-Addressing headers on the process WSDL to expose a long-running process as an asynchronous service.
  • A WCF client invokes the BPEL process, and passes the ReplyTo the WS-Addressing v1.0 (www.w3.org/TR/2005/CR-ws-addr-core-20050817/) header representing the URL of a WCF service that is expecting the operation response message. The client also sends a MessageID WS-Addressing v1.0 header to uniquely identify the request (step 1).
  • The BPEL process receives the message, performs various operations, and uses the ReplyTo address to define a dynamic endpoint using the WS-Addressing 03/2003 (http://msdn.microsoft.com/webservices/webservices/ default.aspx?pull=/library/en-us/dnglobspec/html/ws-addressing0303.asp). (steps 2-4).
  • The BPEL process sends a reply message to the WCF service specified on the ReplyTo address, and passes the RelatesTo WS-Addressing v1.0 header to enable the WCF client to correlate the original request with the response (step 5).
  • The WCF service receives the response message and is able to correlate it back to the request (step 6).
  • In this example, WCF uses WS-Addressing v1.0; however, the BPEL service uses the March 2003 version of WS-Addressing. To make this work, explicit strategies for interoperability need to be applied, as described below.

    As part of the process, the WSDL, which represents the interface of the BPEL process, imports the WS-Addressing v1.0 XSD and declares the ReplyTo and MessageID headers as part of the binding section. It also declares messages of type ReplyTo, MessageID, and RelatesTo as variable types in the BPEL process, as shown in Listing 1. Note: By using this technique, we're explicitly declaring that the BPEL process expects the WS-Addressing ReplyTo and MessageID headers as part of the incoming message.

    Based on the messages types in Listing 1, the BPEL process also defines variables of message type ReplyTo, MessageID, and RelatesTo:

    <variable name="wcfServiceAddr" messageType="ns1:wsaReplyTo"/><variable name="wcfRequestId" messageType="ns1:wsaMessageId"/><variable name="wcfResponseId" messageType="ns1:wsaRelatesTo"/>

    With this in place, we can assign the SOAP header information to them later on and vice versa. The next step is to populate these variables from incoming SOAP message:

    <receive name="receiveInput" partnerLink="client"      portType="client:WCFAddr" operation="initiate"      variable="inputVariable" createInstance="yes"      bpelx:headerVariable="wcfServiceAddr wcfRequestId"/>

    By using bpelx:headerVariable (an extension of the WS-BPEL standard), the process code has access to the MessageID sent from the client as well as to its callback location.

    Let's define a variable of type EndpointReference, which will provide the dynamic endpoint reference, needed for initiating the partnerLink later:

    <variable name="wcfEndpoint" element="ns3:EndpointReference"/>

    Note that the ns3 prefix is associated with the WS-Addressing 03/2003 namespace (xmlns:ns3=http://schemas.xmlsoap.org/ws/2003/03/addressing).

    The next step is to populate the wcfEndpoint variable (defined in the previous step) using the ReplyTo header from wcfServiceAddr (Note the <copy> sections, marked yellow).

    By using standard BPEL activities, these values are assigned by using a series of copy rules in an <assign> construct, as shown in Listing 2.

    Assign the wcfEndpoint variable to the wcfService partnerLink, which represents an outgoing reference to a Web service. With this in place, the partnerLink knows which location to call:

    <assign name="PartnerlinkWSAAssign">   <copy>     <from variable="wcfEndpoint"/>     <to partnerLink="wcfService"/>   </copy></assign>

    In order to allow the client to correlate the request and response messages, we have to copy the value of the wcfRequestId (the unique MessageID) to wcfResponseId (RelatesTo):

    <copy>   <from variable="wcfRequestId" part="parameters" query="/ns2:MessageID"/>   <to variable="wcfResponseId" part="parameters" query="/ns2:RelatesTo"/></copy>

    The last step on the BPEL server-side is to use an invoke activity, which will call the WCF service (defined through the wcfService partnerLink), and to pass the RelatesTo header, available within the wcfResponseId variable. Make sure to use bpelx:inputHeaderVariable for this.

        <invoke name="Invoke_ExternalWCFService" partnerLink="wcfService"       portType="ns1:IOperationCallback" operation="SendResult"       inputVariable="wcfRequest"       bpelx:inputHeaderVariable="wcfResponseId"/>

    After the server side, create a WCF client, which invokes the BPEL process through SOAP. Then create a WCF BindingElement that allows the use of WS-Addressing v1.0, and wrap the call to the BPEL process within an OperationContextScope to populate the WS-Addressing headers, as shown in Listing 3.

    Testing the code in Listing 3 produces a SOAP message that follows. Note the <a:Address> field containing the service address:

    <s:Envelope xmlns:s="http://schemas.xmlsoap.org/soap/envelope/"    xmlns:a="http://www.w3.org/2005/08/addressing">    <s:Header>      <a:Action s:mustUnderstand="1">http://tempuri.org/IOperationCallback/SendResult</a:Action>      <a:ReplyTo>        <a:Address>WCF Service Address...</a:Address>      </a:ReplyTo>      <a:To s:mustUnderstand="1">Oracle BPEL Process Address...</a:To>      <a:MessageID>urn:uuid:847b546e-16e5-4ea9-8267-b6fe559f0c1f</a:MessageID>    </s:Header>    <s:Body>Body</s:Body></s:Envelope>



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