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000-610 DB2 10.1 Fundamentals

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000-610 exam Dumps Source : DB2 10.1 Fundamentals

Test Code : 000-610
Test name : DB2 10.1 Fundamentals
Vendor name : IBM
real questions : 138 real Questions

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IBM DB2 10.1 Fundamentals

beginning DB2: From tyro to professional | killexams.com real Questions and Pass4sure dumps

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Altova Introduces edition 2014 of Its Developer tools and Server software | killexams.com real Questions and Pass4sure dumps

BEVERLY, MA--(Marketwired - Oct 29, 2013) - Altova® (http://www.altova.com), creator of XMLSpy®, the trade leading XML editor, nowadays introduced the unencumber of version 2014 of its MissionKit® computer developer tools and server application items. MissionKit 2014 products now consist of integration with the lightning quickly validation and processing capabilities of RaptorXML®, uphold for Schema 1.1, XPath/XSLT/XQuery 3.0, guide for brand current databases and an dreadful lot extra. current features in Altova server products consist of caching alternate options in FlowForce® Server and multiplied performance powered via RaptorXML throughout the server product line.

"we're so excited to subsist in a position to extend the hyper-performance delivered via the unparalleled RaptorXML Server to builders working in their laptop tools. This performance, together with astounding abet for the very newest requisites, from XML Schema 1.1 to XPath 3.0 and XSLT 3.0, offers their valued clientele the advantages of accelerated efficiency alongside cutting-aspect technology help," spoke of Alexander Falk, President and CEO for Altova. "This, coupled with the skill to automate basic techniques by artery of their excessive-performance server items, offers their valued clientele a certain talents when pile and deploying purposes."

a brace of of the brand current facets available in Altova MissionKit 2014 consist of:

Integration of RaptorXML: introduced previous this yr, RaptorXML Server is excessive-performance server software capable of validating and processing XML at lightning speeds -- whereas delivering the strictest viable standards conformance. Now the equal hyper-efficiency engine that powers RaptorXML Server is thoroughly integrated in several Altova MissionKit tools, including XMLSpy, MapForce®, and SchemaAgent®, supplying lightning quick validation and processing of XML, XSLT, XQuery, XBRL, and extra. The third-technology validation and processing engine from Altova, RaptorXML changed into built from the floor as much as uphold the very newest of everysingle central XML requirements, including XML Schema 1.1, XSLT three.0, XPath three.0, XBRL 2.1, and myriad others.

guide for Schema 1.1: XMLSpy 2014 comprises crucial uphold for XML Schema 1.1 validation and enhancing. The latest edition of the XML Schema usual, 1.1 adds current features geared toward making schemas greater elastic and adaptable to company instances, corresponding to assertions, conditional varieties, open content, and extra.

All elements of XML Schema 1.1 are supported in XMLSpy's graphical XML Schema editor and are available in entry helpers and tabs. As everysingle the time, the graphical editing paradigm of the schema editor makes it convenient to subsist mindful and implement these current facets.

aid for XML Schema 1.1 is additionally provided in SchemaAgent 2014, permitting users to imagine and manage schema relationships by means of its graphical interface. this is moreover an edge when connecting to SchemaAgent in XMLSpy.

Coinciding with XML Schema 1.1 assist, Altova has additionally released a free, online XML Schema 1.1 expertise practising direction, which covers the basics of the XML Schema language as well because the adjustments added in XML Schema 1.1.

support for XPath three.0, XSLT 3.0, and XQuery three.0:

assist for XPath in XMLSpy 2014 has been up-to-date to comprehend the newest version of the XPath suggestion. XPath three.0 is a superset of the XPath 2.0 recommendation and adds potent current performance similar to: dynamic characteristic cells, inline feature expressions, and uphold for union varieties to name simply a number of. Full guide for brand current services and operators added in XPath three.0 is accessible via shrewd XPath auto-completion in textual content and Grid Views, as well as in the XPath Analyzer window.

support for enhancing, debugging, and profiling XSLT is now attainable for XSLT 3.0 in addition to former versions. tickle commemorate that a subset of XSLT 3.0 is supported considering the fact that the common remains a working draft that continues to adapt. XSLT three.0 assist conforms to the W3C XSLT 3.0 Working Draft of July 10, 2012 and the XPath 3.0 Candidate advice. despite the fact, aid in XMLSpy now gives developers the capacity to delivery working with this current edition automatically.

XSLT three.0 takes expertise of the brand current facets brought in XPath 3.0. in addition, a massive feature enabled with the aid of the current version is the current xsl:are trying / xsl:trap construct, which will moreover subsist used to trap and help from dynamic errors. other enhancements in XSLT three.0 encompass abet for bigger order services and partial functions.

Story continues

As with XSLT and XPath, XMLSpy assist for XQuery now additionally comprises a subset of edition three.0. builders will now believe the altenative to edit, debug, and profile XQuery 3.0 with effectual syntax coloring, bracket matching, XPath auto-completion, and other intellectual editing elements.

XQuery three.0 is, of path, an extension of XPath and for this understanding merits from the current functions and operators introduced in XPath three.0, akin to a current string concatenation operator, map operator, math capabilities, sequence processing, and greater -- everysingle of which are available within the context sensitive entry helper home windows and drop down menus in the XMLSpy 2014 XQuery editor.

New Database guide:

Database-enabled MissionKit items including XMLSpy, MapForce, StyleVision®, DatabaseSpy®, UModel®, and DiffDog®, now encompass complete uphold for more recent models of prior to now supported databases, as well as uphold for brand current database vendors:

  • Informix® eleven.70
  • PostgreSQL versions 9.0.10/9.1.6/9.2.1
  • MySQL® 5.5.28
  • IBM DB2® models 9.5/9.7/10.1
  • Microsoft® SQL Server® 2012
  • Sybase® ASE (Adaptive Server enterprise) 15/15.7
  • Microsoft entry™ 2010/2013
  • New in Altova Server application 2014:

    introduced prior in 2013, Altova's current line of pass-platform server application items comprises FlowForce Server, MapForce Server, StyleVision Server, and RaptorXML Server. FlowForce Server gives finished management, job scheduling, and security options for the automation of touchstone enterprise procedures, whereas MapForce Server and StyleVision Server present high-speed automation for projects designed using prevalent Altova MissionKit developer equipment. RaptorXML Server is the third-era, hyper-fast validation and processing engine for XML and XBRL.

    beginning with edition 2014, Altova server items are powered via RaptorXML for faster, greater efficient processing. furthermore, FlowForce Server now helps outcomes caching for jobs that require a very long time to method, for case when a job requires advanced database queries or should execute its personal internet provider information requests. FlowForce Server administrators can now schedule execution of a time-drinking job and cache the results to hold away from these delays. The cached facts can then subsist supplied when any user executes the job as a provider, delivering rapid effects. A job that generates a customized earnings report for the previous day could subsist a very proper software for caching.

    These and a lot of greater points can subsist found within the 2014 version of MissionKit desktop developer tools and Server software. For a complete checklist of current facets, supported necessities, and visitation downloads tickle consult with: http://www.altova.com/whatsnew.html

    About Altova Altova® is a utility company that specialize in gear to uphold developers with records administration, utility and utility development, and information integration. The creator of XMLSpy® and other award-successful XML, SQL and UML tools, Altova is a key player within the software tools commerce and the chief in XML solution construction equipment. Altova focuses on its shoppers' wants by means of offering a product line that fulfills a huge spectrum of requirements for software pile groups. With over four.5 million clients international, including 91% of Fortune 500 groups, Altova is supercilious to serve valued clientele from one-person shops to the world's biggest businesses. Altova is dedicated to delivering requisites-primarily based, platform-impartial options which are effective, low-cost and straightforward-to-use. founded in 1992, Altova is headquartered in Beverly, Massachusetts and Vienna, Austria. discuss with Altova on the internet at: http://www.altova.com.

    Altova, MissionKit, XMLSpy, MapForce, FlowForce, RaptorXML, StyleVision, UModel, DatabaseSpy, DiffDog, SchemaAgent, genuine, and MetaTeam are trademarks and/or registered logos of Altova GmbH within the u.s. and/or different international locations. The names of and reference to other companies and products outlined herein can subsist the logos of their respective house owners.


    MySQL stored process Programming | killexams.com real Questions and Pass4sure dumps

    Written by artery of guy Harrison and Steven Feuerstein, and published via O'Reilly Media in March 2006 under the ISBNs 0596100892 and 978-0596100896, this ebook is the primary one to present database programmers a plenary discussion of the syntax, utilization, and optimization of MySQL kept procedures, saved capabilities, and triggers — which the authors accurately check with jointly as "kept courses," to simplify the manuscript. Even a year after the introduction of those current capabilities in MySQL, they believe got obtained remarkably limited coverage with the aid of engage publishers. Admittedly, there are three such chapters in MySQL Administrator's e-book and Language Reference (2nd version), written by artery of one of the vital builders of MySQL, and published by means of MySQL Press. Yet this latter e-book — even if published a month after O'Reilly's — devotes fewer than 50 pages to stored courses, and the cloth isn't within the printed e-book itself, but within the "MySQL Language Reference" part, on the accompanying CD. That fabric, along with the on-line reference documentation, may well subsist enough for the more basic stored program construction wants. however for any MySQL developer who wishes to endure in reason in-depth the artery to execute the most of this current functionality in version 5.0, they'll probably want a much more gargantuan treatment — and that's precisely what Harrison and Feuerstein believe created.

    The authors are generous in both the technical information and construction tips that they offer. The ebook's fabric spans 636 pages, equipped into 23 chapters, grouped into four components, followed via an index. the first part, "saved Programming Fundamentals," offers an introduction after which an instructional, both taking a huge view of MySQL kept courses. The final four chapters cowl language fundamentals; blocks, conditional statements, and iterative programming; SQL; and oversight coping with. The publication's 2d half, "saved program construction," can subsist considered the coronary heart of the book, as a result of its five chapters latest the details of developing saved courses in general, the disburse of transaction management, using MySQL's built-in functions, and creating one's own stored functions, in addition to triggers. The third half, "the disburse of MySQL stored programs and functions," explains one of the most merits and disadvantages of stored courses, and then illustrates a artery to name these stored classes from source code written in any one of 5 diverse programming languages: php, Java, Perl, Python, and Microsoft.web. within the fourth and closing part, "Optimizing kept classes," the authors center of attention on the safety and tuning of saved programs, tuning SQL, optimizing the code, and optimizing the progress system itself.

    this is a substantial e-book, encompassing a fine deal of technical as well as advisory tips. as a result, no overview similar to this may hope to warrant or seriously comment upon every component to every chapter of every half. Yet the accustomed nice and utility of the manuscript may moreover subsist discerned simply through picking only 1 of the aforesaid internet programming languages, and writing some code in that language to muster some MySQL kept tactics and capabilities, to comeby consequences from a test database — and setting up everysingle of this code while relying fully upon the ebook under evaluate. growing some touchstone kept procedures, and calling them from some Hypertext Preprocessor and Perl scripts, verified to me that MySQL kept technique Programming contains greater than sufficient coverage of the themes to subsist a useful ebook in developing the most average performance that a programmer would deserve to build into effect.

    The ebook appears to believe very few features or particular sections in exigency of growth. The discussion of variable scoping, in Chapter 4, is too cursory (no database pun intended). when it comes to the booklet's sample code, I found countless instances of inconsistency of formatting — mainly, operators similar to "||" and "=" being jammed up against their adjacent aspects, without any whitespace to enhance readability. These minor flaws may subsist effectively remedied in the next version. Some programming books execute equivalent blunders, but everysingle over their text, which is even worse. fortunately, many of the code in this engage is neatly formatted, and the variable and application names are commonly descriptive satisfactory.

    one of the crucial publication's fabric could believe been disregarded without high-quality loss — thereby decreasing the book's dimension, weight, and possibly price. the two chapters on simple and superior SQL tuning accommodate innovations and suggestions lined with equal skill in other MySQL books, and were not necessary in this one. on the other hand, slovenly developers who churn out lamentable code may argue that the final chapter, which makes a speciality of most excellent programming practices, could moreover subsist excised; however those are the very people who want these recommendations probably the most.

    fortunately, the few weaknesses in the publication are completely overwhelmed via its wonderful traits, of which there are lots of. The coverage of the topic matters is rather wide, but without the repetition frequently considered in many different technical books of this dimension. the explanations are written with clarity, and provide ample aspect for any skilled database programmer to grasp into account the conventional ideas, as well because the selected details. The sample code without problems illustrates the ideas offered in the narration. The font, design, company, and fold-flat binding of this ebook, everysingle execute it a pleasure to read — as is characteristic of many of O'Reilly's titles.

    in addition, any programming publication that manages to lighten the load of the reader by artery of providing a splash of humor birthright here and there, can't subsist everysingle bad. Steven Feuerstein is the creator of a brace of well-considered books on Oracle, and it become remarkable to peer him poke some enjoyable on the database heavyweight, in his altenative of pattern code to demonstrate the my_replace() function: my_replace( 'we prize the Oracle server', 'Oracle', 'MySQL').

    The prospective reader who would want to learn extra about this publication, can check with its net web page on O'Reilly's web site. There they are going to determine both short and plenary descriptions, established and unconfirmed errata, a link for writing a reader overview, an internet table of contents and index, and a pattern chapter (number 6, "Error dealing with"), in PDF structure. in addition, the traveler can download the entire sample code in the e-book (562 data) and the sample database, as a mysqldump file.

    general, MySQL saved system Programming is adeptly written, neatly geared up, and exhaustive in its coverage of the topics. it's and unavoidable will remain the premier printed useful resource for internet and database developers who wish to learn the artery to create and optimize stored methods, features, and triggers within MySQL.

    Michael J. Ross is a web programmer, freelance author, and the editor of PristinePlanet.com's free publication. He can subsist reached at www.ross.ws, hosted with the aid of SiteGround.


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    Altova Introduces Version 2014 of Its Developer Tools and Server Software | killexams.com real questions and Pass4sure dumps

    BEVERLY, MA--(Marketwired - Oct 29, 2013) - Altova® (http://www.altova.com), creator of XMLSpy®, the industry leading XML editor, today announced the release of Version 2014 of its MissionKit® desktop developer tools and server software products. MissionKit 2014 products now comprehend integration with the lightning posthaste validation and processing capabilities of RaptorXML®, uphold for Schema 1.1, XPath/XSLT/XQuery 3.0, uphold for current databases and much more. current features in Altova server products comprehend caching options in FlowForce® Server and increased performance powered by RaptorXML across the server product line.

    "We are so excited to subsist able to extend the hyper-performance delivered by the unparalleled RaptorXML Server to developers working in their desktop tools. This functionality, along with robust uphold for the very latest standards, from XML Schema 1.1 to XPath 3.0 and XSLT 3.0, provides their customers the benefits of increased performance alongside cutting-edge technology support," said Alexander Falk, President and CEO for Altova. "This, coupled with the talent to automate essential processes via their high-performance server products, gives their customers a distinct edge when pile and deploying applications."

    A few of the current features available in Altova MissionKit 2014 include:

    Integration of RaptorXML: Announced earlier this year, RaptorXML Server is high-performance server software capable of validating and processing XML at lightning speeds -- while delivering the strictest viable standards conformance. Now the selfsame hyper-performance engine that powers RaptorXML Server is fully integrated in several Altova MissionKit tools, including XMLSpy, MapForce®, and SchemaAgent®, delivering lightning posthaste validation and processing of XML, XSLT, XQuery, XBRL, and more. The third-generation validation and processing engine from Altova, RaptorXML was built from the ground up to uphold the very latest of everysingle germane XML standards, including XML Schema 1.1, XSLT 3.0, XPath 3.0, XBRL 2.1, and myriad others.

    Support for Schema 1.1: XMLSpy 2014 includes necessary uphold for XML Schema 1.1 validation and editing. The latest version of the XML Schema standard, 1.1 adds current features aimed at making schemas more elastic and adaptable to commerce situations, such as assertions, conditional types, open content, and more.

    All aspects of XML Schema 1.1 are supported in XMLSpy's graphical XML Schema editor and are available in entry helpers and tabs. As always, the graphical editing paradigm of the schema editor makes it effortless to understand and implement these current features.

    Support for XML Schema 1.1 is moreover provided in SchemaAgent 2014, allowing users to visualize and manage schema relationships via its graphical interface. This is moreover an edge when connecting to SchemaAgent in XMLSpy.

    Coinciding with XML Schema 1.1 support, Altova has moreover released a free, online XML Schema 1.1 technology training course, which covers the fundamentals of the XML Schema language as well as the changes introduced in XML Schema 1.1.

    Support for XPath 3.0, XSLT 3.0, and XQuery 3.0:

    Support for XPath in XMLSpy 2014 has been updated to comprehend the latest version of the XPath Recommendation. XPath 3.0 is a superset of the XPath 2.0 recommendation and adds powerful current functionality such as: dynamic duty cells, inline duty expressions, and uphold for union types to name just a few. Full uphold for current functions and operators added in XPath 3.0 is available through intellectual XPath auto-completion in Text and Grid Views, as well as in the XPath Analyzer window.

    Support for editing, debugging, and profiling XSLT is now available for XSLT 3.0 as well as previous versions. tickle note that a subset of XSLT 3.0 is supported since the touchstone is soundless a working draft that continues to evolve. XSLT 3.0 uphold conforms to the W3C XSLT 3.0 Working Draft of July 10, 2012 and the XPath 3.0 Candidate Recommendation. However, uphold in XMLSpy now gives developers the talent to start working with this current version immediately.

    XSLT 3.0 takes edge of the current features added in XPath 3.0. In addition, a major feature enabled by the current version is the current xsl:try / xsl:catch construct, which can subsist used to trap and recoup from dynamic errors. Other enhancements in XSLT 3.0 comprehend uphold for higher order functions and partial functions.

    Story continues

    As with XSLT and XPath, XMLSpy uphold for XQuery now moreover includes a subset of version 3.0. Developers will now believe the option to edit, debug, and profile XQuery 3.0 with helpful syntax coloring, bracket matching, XPath auto-completion, and other intellectual editing features.

    XQuery 3.0 is, of course, an extension of XPath and therefore benefits from the current functions and operators added in XPath 3.0, such as a current string concatenation operator, map operator, math functions, sequence processing, and more -- everysingle of which are available in the context sensitive entry helper windows and drop down menus in the XMLSpy 2014 XQuery editor.

    New Database Support:

    Database-enabled MissionKit products including XMLSpy, MapForce, StyleVision®, DatabaseSpy®, UModel®, and DiffDog®, now comprehend complete uphold for newer versions of previously supported databases, as well as uphold for current database vendors:

  • Informix® 11.70
  • PostgreSQL versions 9.0.10/9.1.6/9.2.1
  • MySQL® 5.5.28
  • IBM DB2® versions 9.5/9.7/10.1
  • Microsoft® SQL Server® 2012
  • Sybase® ASE (Adaptive Server Enterprise) 15/15.7
  • Microsoft Access™ 2010/2013
  • New in Altova Server Software 2014:

    Introduced earlier in 2013, Altova's current line of cross-platform server software products includes FlowForce Server, MapForce Server, StyleVision Server, and RaptorXML Server. FlowForce Server provides comprehensive management, job scheduling, and security options for the automation of essential commerce processes, while MapForce Server and StyleVision Server present high-speed automation for projects designed using close Altova MissionKit developer tools. RaptorXML Server is the third-generation, hyper-fast validation and processing engine for XML and XBRL.

    Starting with Version 2014, Altova server products are powered by RaptorXML for faster, more efficient processing. In addition, FlowForce Server now supports results caching for jobs that require a long time to process, for instance when a job requires complicated database queries or needs to execute its own Web service data requests. FlowForce Server administrators can now schedule execution of a time-consuming job and cache the results to forestall these delays. The cached data can then subsist provided when any user executes the job as a service, delivering instant results. A job that generates a customized sales report for the previous day would subsist a proper application for caching.

    These and many more features are available in the 2014 Version of MissionKit desktop developer tools and Server software. For a complete list of current features, supported standards, and visitation downloads tickle visit: http://www.altova.com/whatsnew.html

    About Altova Altova® is a software company specializing in tools to assist developers with data management, software and application development, and data integration. The creator of XMLSpy® and other award-winning XML, SQL and UML tools, Altova is a key player in the software tools industry and the leader in XML solution progress tools. Altova focuses on its customers' needs by offering a product line that fulfills a broad spectrum of requirements for software progress teams. With over 4.5 million users worldwide, including 91% of Fortune 500 organizations, Altova is supercilious to serve clients from one-person shops to the world's largest organizations. Altova is committed to delivering standards-based, platform-independent solutions that are powerful, affordable and easy-to-use. Founded in 1992, Altova is headquartered in Beverly, Massachusetts and Vienna, Austria. Visit Altova on the Web at: http://www.altova.com.

    Altova, MissionKit, XMLSpy, MapForce, FlowForce, RaptorXML, StyleVision, UModel, DatabaseSpy, DiffDog, SchemaAgent, Authentic, and MetaTeam are trademarks and/or registered trademarks of Altova GmbH in the United States and/or other countries. The names of and reference to other companies and products mentioned herein may subsist the trademarks of their respective owners.


    Unleashing MongoDB With Your OpenShift Applications | killexams.com real questions and Pass4sure dumps

    Current progress cycles face many challenges such as an evolving landscape of application architecture (Monolithic to Microservices), the exigency to frequently deploy features, and current IaaS and PaaS environments. This causes many issues throughout the organization, from the progress teams everysingle the artery to operations and management.

    In this blog post, they will attest you how you can set up a local system that will uphold MongoDB, MongoDB Ops Manager, and OpenShift. They will walk through the various installation steps and demonstrate how effortless it is to carryout agile application progress with MongoDB and OpenShift.

    MongoDB is the next-generation database that is built for rapid and iterative application development. Its elastic data model — the talent to incorporate both structured or unstructured data — allows developers to build applications faster and more effectively than ever before. Enterprises can dynamically modify schemas without downtime, resulting in less time preparing data for the database, and more time putting data to work. MongoDB documents are more closely aligned to the structure of objects in a programming language. This makes it simpler and faster for developers to model how data in the application will map to data stored in the database, resulting in better agility and rapid development.

    MongoDB Ops Manager (also available as the hosted MongoDB Cloud Manager service) features visualization, custom dashboards, and automated alerting to abet manage a complicated environment. Ops Manager tracks 100+ key database and systems health metrics including operations counters, CPU utilization, replication status, and any node status. The metrics are securely reported to Ops Manager where they are processed and visualized. Ops Manager can moreover subsist used to provide seamless no-downtime upgrades, scaling, and backup and restore.

    Red Hat OpenShift is a complete open source application platform that helps organizations develop, deploy, and manage existing and container-based applications seamlessly across infrastructures. Based on Docker container packaging and Kubernetes container cluster management, OpenShift delivers a high-quality developer suffer within a stable, secure, and scalable operating system. Application lifecycle management and agile application progress tooling multiply efficiency. Interoperability with multiple services and technologies and enhanced container and orchestration models let you customize your environment.

    Setting Up Your Test Environment

    In order to supervene this example, you will exigency to meet a number of requirements. You will exigency a system with 16 GB of RAM and a RHEL 7.2 Server (we used an instance with a GUI for simplicity). The following software is moreover required:

  • Ansible
  • Vagrant
  • VirtualBox
  • Ansible Install

    Ansible is a very powerful open source automation language. What makes it unique from other management tools, is that it is moreover a deployment and orchestration tool. In many respects, aiming to provide great productivity gains to a wide variety of automation challenges. While Ansible provides more productive drop-in replacements for many core capabilities in other automation solutions, it moreover seeks to solve other major unsolved IT challenges.

    We will install the Automation Agent onto the servers that will become Part of the MongoDB replica set. The Automation Agent is Part of MongoDB Ops Manager.

    In order to install Ansible using yum you will exigency to enable the EPEL repository. The EPEL (Extra Packages for Enterprise Linux) is repository that is driven by the Fedora Special Interest Group. This repository contains a number of additional packages guaranteed not to replace or combat with the base RHEL packages.

    The EPEL repository has a dependency on the Server Optional and Server Extras repositories. To enable these repositories you will exigency to execute the following commands:

    $ sudo subscription-manager repos --enable rhel-7-server-optional-rpms $ sudo subscription-manager repos --enable rhel-7-server-extras-rpms

    To install/enable the EPEL repository you will exigency to carryout the following:

    $ wget https://dl.fedoraproject.org/pub/epel/epel-release-latest-7.noarch.rpm $ sudo yum install epel-release-latest-7.noarch.rpm

    Once complete you can install ansible by executing the following command:

    $ sudo yum install ansible Vagrant Install

    Vagrant is a command line utility that can subsist used to manage the lifecycle of a virtual machine. This instrument is used for the installation and management of the Red Hat Container progress Kit.

    Vagrant is not included in any touchstone repository, so they will exigency to install it. You can install Vagrant by enabling the SCLO repository or you can comeby it directly from the Vagrant website. They will disburse the latter approach:

    $ wget https://releases.hashicorp.com/vagrant/1.8.3/vagrant_1.8.3_x86_64.rpm $ sudo yum install vagrant_1.8.3_x86_64.rpm VirtualBox Install

    The Red Hat Container progress Kit requires a virtualization software stack to execute. In this blog they will disburse VirtualBox for the virtualization software.

    VirtualBox is best done using a repository to ensure you can comeby updates. To carryout this you will exigency to supervene these steps:

  • You will want to download the repo file:
  • $ wget http://download.virtualbox.org/virtualbox/rpm/el/virtualbox.repo $ mv virtualbox.repo /etc/yum.repos.d $ sudo yum install VirtualBox-5.0

    Once the install is complete you will want to launch VirtualBox and ensure that the Guest Network is on the remedy subnet as the CDK has a default for it setup. The blog will leverage this default as well. To verify that the host is on the remedy domain:

  • Open VirtualBox, this should subsist under you Applications->System Tools menu on your desktop.
  • Click on File->Preferences.
  • Click on Network.
  • Click on the Host-only Networks, and a popup of the VirtualBox preferences will load.
  • There should subsist a vboxnet0 as the network, click on it and click on the edit icon (looks love a screwdriver on the left side of the popup) 6.Ensure that the IPv4 Address is 10.1.2.1.
  • Ensure the IPv4 Network Mask is 255.255.255.0.
  • Click on the DHCP Server tab.
  • Ensure the server address is 10.1.2.100.
  • Ensure the Server mask is 255.255.255.0.
  • Ensure the Lower Address Bound is 10.1.2.101.
  • Ensure the Upper Address Bound is 10.1.2.254.
  • Click on OK.
  • Click on OK.
  • CDK Install

    Docker containers are used to package software applications into portable, isolated stores. Developing software with containers helps developers create applications that will elude the selfsame artery on every platform. However, modern microservice deployments typically disburse a scheduler such as Kubernetes to elude in production. In order to fully simulate the production environment, developers require a local version of production tools. In the Red Hat stack, this is supplied by the Red Hat Container progress Kit (CDK).

    The Red Hat CDK is a customized virtual machine that makes it effortless to elude complicated deployments resembling production. This means complicated applications can subsist developed using production grade tools from the very start, significance developers are unlikely to suffer problems stemming from differences in the progress and production environments.

    Now let's walk through installation and configuration of the Red Hat CDK. They will create a containerized multi-tier application on the CDK’s OpenShift instance and Go through the entire workflow. By the suspension of this blog post you will know how to elude an application on top of OpenShift and will subsist close with the core features of the CDK and OpenShift. Let’s comeby started…

    Installing the CDK

    The prerequisites for running the CDK are Vagrant and a virtualization client (VirtualBox, VMware Fusion, libvirt). execute certain that both are up and running on your machine.

    Start by going to Red Hat Product Downloads (note that you will exigency a Red Hat subscription to access this). Select ‘Red Hat Container progress Kit’ under Product Variant, and the commandeer version and architecture. You should download two packages:

  • Red Hat Container Tools.
  • RHEL Vagrant Box (for your preferred virtualization client).
  • The Container Tools package is a set of plugins and templates that will abet you start the Vagrant box. In the components subfolder you will find Vagrant files that will configure the virtual machine for you. The plugins folder contains the Vagrant add-ons that will subsist used to register the current virtual machine with the Red Hat subscription and to configure networking.

    Unzip the container tools archive into the root of your user folder and install the Vagrant add-ons.

    $ cd ~/cdk/plugins $ vagrant plugin install vagrant-registration vagrant-adbinfo landrush vagrant-service-manager

    You can check if the plugins were actually installed with this command:

    $ vagrant plugin list

    Add the box you downloaded into Vagrant. The path and the name may vary depending on your download folder and the box version:

    $ vagrant box add --name cdkv2 \ ~/Downloads/rhel-cdk-kubernetes-7.2-13.x86_64.vagrant-virtualbox.box

    Check that the vagrant box was properly added with the box list command:

    $ vagrant box list

    We will disburse the Vagrantfile that comes shipped with the CDK and has uphold for OpenShift.

    $ cd $HOME/cdk/components/rhel/rhel-ose/ $ ls README.rst Vagrantfile

    In order to disburse the landrush plugin to configure the DNS they exigency to add the following two lines to the Vagrantfile exactly as below (i.e. PUBLIC_ADDRESS is a property in the Vagrantfile and does not exigency to subsist replaced) :

    config.landrush.enabled = true config.landrush.host_ip_address = "#{PUBLIC_ADDRESS}"

    This will allow us to access their application from outside the virtual machine based on the hostname they configure. Without this plugin, your applications will subsist reachable only by IP address from within the VM.

    Save the changes and start the virtual machine :

    $ vagrant up

    During initialization, you will subsist prompted to register your Vagrant box with your RHEL subscription credentials.

    Let’s review what just happened here. On your local machine, you now believe a working instance of OpenShift running inside a virtual machine. This instance can talk to the Red Hat Registry to download images for the most common application stacks. You moreover comeby a private Docker registry for storing images. Docker, Kubernetes, OpenShift and Atomic App CLIs are moreover installed.

    Now that they believe their Vagrant box up and running, it’s time to create and deploy a sample application to OpenShift, and create a continuous deployment workflow for it.

    The OpenShift console should subsist accessible at https://10.1.2.2:8443 from a browser on your host (this IP is defined in the Vagrantfile). By default, the login credentials will subsist openshift-dev/devel. You can moreover disburse your Red Hat credentials to login. In the console, they create a current project:

    Next, they create a current application using one of the built-in ‘Instant Apps’. Instant Apps are predefined application templates that tug specific images. These are an effortless artery to quickly comeby an app up and running. From the list of Instant Apps, select “nodejs-mongodb-example” which will start a database (MongoDB) and a web server (Node.js).

    For this application, they will disburse the source code from the OpenShift GitHub repository located here. If you want to supervene along with the webhook steps later, you’ll exigency to fork this repository into your own. Once you’re ready, enter the URL of your repo into the SOURCE_REPOSITORY_URL field:

    There are two other parameters that are necessary to us – GITHUB_WEBHOOK_SECRET and APPLICATION_DOMAIN:

  • GITHUB_WEBHOOK_SECRET: this province allows us to create a stealthy to disburse with the GitHub webhook for automatic builds. You don’t exigency to specify this, but you’ll exigency to recall the value later if you do.
  • APPLICATION_DOMAIN: this province will determine where they can access their application. This value must comprehend the Top flush Domain for the VM, by default this value is rhel-ose.vagrant.dev. You can check this by running vagrant landrush ls.
  • Once these values are configured, they can ‘Create’ their application. This brings us to an information page which gives us some helpful CLI commands as well as their webhook URL. Copy this URL as they will disburse it later on.

    OpenShift will then tug the code from GitHub, find the commandeer Docker image in the Red Hat repository, and moreover create the build configuration, deployment configuration, and service definitions. It will then kick off an initial build. You can view this process and the various steps within the web console. Once completed it should searchfor love this:

    In order to disburse the Landrush plugin, there is additional steps that are required to configure dnsmasq. To carryout that you will exigency to carryout the following:

  • Ensure dnsmasq is installed  $ sudo yum install dnsmasq
  • Modify the vagrant configuration for dnsmasq: $ sudo sh -c 'echo "server=/vagrant.test/127.0.0.1#10053" > /etc/dnsmasq.d/vagrant-landrush'
  • Edit /etc/dnsmasq.conf and verify the following lines are in this file: conf-dir=/etc/dnsmasq.d listen-address=127.0.0.1
  • Restart the dnsmasq service $ sudo systemctl restart dnsmasq
  • Add nameserver 127.0.0.1 to /etc/resolv.conf
  • Great! Their application has now been built and deployed on their local OpenShift environment. To complete the Continuous Deployment pipeline they just exigency to add a webhook into their GitHub repository they specified above, which will automatically update the running application.

    To set up the webhook in GitHub, they exigency a artery of routing from the public internet to the Vagrant machine running on your host. An effortless artery to achieve this is to disburse a third party forwarding service such as ultrahook or ngrok. They exigency to set up a URL in the service that forwards traffic through a tunnel to the webhook URL they copied earlier.

    Once this is done, open the GitHub repo and Go to Settings -> Webhooks & services -> Add webhook. Under Payload URL enter the URL that the forwarding service gave you, plus the stealthy (if you specified one when setting up the OpenShift project). If your webhook is configured correctly you should view something love this:

    To test out the pipeline, they exigency to execute a change to their project and push a confide to the repo.

    Any effortless artery to carryout this is to edit the views/index.html file, e.g: (Note that you can moreover carryout this through the GitHub web interface if you’re zeal lazy). confide and push this change to the GitHub repo, and they can view a current build is triggered automatically within the web console. Once the build completes, if they again open their application they should view the updated front page.

    We now believe Continuous Deployment configured for their application. Throughout this blog post, we’ve used the OpenShift web interface. However, they could believe performed the selfsame actions using the OpenShift console (oc) at the command-line. The easiest artery to experiment with this interface is to ssh into the CDK VM via the Vagrant ssh command.

    Before wrapping up, it’s helpful to understand some of the concepts used in Kubernetes, which is the underlying orchestration layer in OpenShift.

    Pods

    A pod is one or more containers that will subsist deployed to a node together. A pod represents the smallest unit that can subsist deployed and managed in OpenShift. The pod will subsist assigned its own IP address. everysingle of the containers in the pod will share local storage and networking.

    A pod lifecycle is defined, deploy to node, elude their container(s), exit or removed. Once a pod is executing then it cannot subsist changed. If a change is required then the existing pod is terminated and recreated with the modified configuration.

    For their case application, they believe a Pod running the application. Pods can subsist scaled up/down from the OpenShift interface.

    Replication Controllers

    These manage the lifecycle of Pods.They ensure that the remedy number of Pods are always running by monitoring the application and stopping or creating Pods as appropriate.

    Services

    Pods are grouped into services. Their architecture now has four services: three for the database (MongoDB) and one for the application server JBoss.

    Deployments

    With every current code confide (assuming you set-up the GitHub webhooks) OpenShift will update your application. current pods will subsist started with the abet of replication controllers running your current application version. The former pods will subsist deleted. OpenShift deployments can fulfill rollbacks and provide various deploy strategies. It’s difficult to overstate the advantages of being able to elude a production environment in progress and the efficiencies gained from the posthaste feedback cycle of a Continuous Deployment pipeline.

    In this post, they believe shown how to disburse the Red Hat CDK to achieve both of these goals within a short-time frame and now believe a Node.js and MongoDB application running in containers, deployed using the OpenShift PaaS. This is a remarkable artery to quickly comeby up and running with containers and microservices and to experiment with OpenShift and other elements of the Red Hat container ecosystem.

    MongoDB VirtualBox

    In this section, they will create the virtual machines that will subsist required to set up the replica set. They will not walk through everysingle of the steps of setting up Red Hat as this is prerequisite knowledge.

    What they will subsist doing is creating a base RHEL 7.2 minimal install and then using the VirtualBox interface to clone the images. They will carryout this so that they can easily install the replica set using the MongoDB Automation Agent.

    We will moreover subsist installing a no password generated ssh keys for the Ansible Playbook install of the automation engine.

    Please fulfill the following steps:

  • In VirtualBox create a current guest image and muster it RHEL Base. They used the following information: a. remembrance 2048 MB b. Storage 30GB c. 2 Network cards i. Nat ii. Host-Only
  • Do a minimal Red Hat install, they modified the disk layout to remove the /home directory and added the reclaimed space to the / partition
  • Once this is done you should attach a subscription and carryout a yum update on the guest RHEL install.

    The final step will subsist to generate current ssh keys for the root user and transfer the keys to the guest machine. To carryout that tickle carryout the following steps:

  • Become the root user $ sudo -i
  • Generate your ssh keys. carryout not add a passphrase when requested.  # ssh-keygen
  • You exigency to add the contents of the id_rsa.pub to the authorized_keys file on the RHEL guest. The following steps were used on a local system and are not best practices for this process. In a managed server environment your IT should believe a best rehearse for doing this. If this is the first guest in your VirtualBox then it should believe an ip of 10.1.2.101, if it has another ip then you will exigency to replace for the following. For this blog tickle execute the following steps # cd ~/.ssh/ # scp id_rsa.pub 10.1.2.101: # ssh 10.1.2.101 # mkdir .ssh # cat id_rsa.pub > ~/.ssh/authorized_keys # chmod 700 /root/.ssh # chmod 600 /root/.ssh/authorized_keys
  • SELinux may shroud sshd from using the authorized_keys so update the permissions on the guest with the following command # restorecon -R -v /root/.ssh
  • Test the connection by trying to ssh from the host to the guest, you should not subsist asked for any login information.
  • Once this is complete you can shut down the RHEL base guest image. They will now clone this to provide the MongoDB environment. The steps are as follows:

  • Right click on the RHEL guest OS and select Clone.
  • Enter the name 7.2 RH Mongo-DB1.
  • Ensure to click the Reinitialize the MAC Address of everysingle network cards.
  • Click on Next.
  • Ensure the plenary Clone option is selected.
  • Click on Clone.
  • Right click on the RHEL guest OS and select Clone.
  • Enter the name 7.2 RH Mongo-DB2.
  • Ensure to click the Reinitialize the MAC Address of everysingle network cards.
  • Click on Next.
  • Ensure the plenary Clone option is selected.
  • Click on Clone.
  • Right click on the RHEL guest OS and select Clone.
  • Enter the name 7.2 RH Mongo-DB3.
  • Ensure to click the Reinitialize the MAC Address of everysingle network cards.
  • Click on Next.
  • Ensure the plenary Clone option is selected.
  • Click on Clone.
  • The final step for getting the systems ready will subsist to configure the hostnames, host-only ip and the host files. They will exigency to moreover ensure that the systems can communicate on the port for MongoDB, so they will disable the firewall which is not meant for production purposes but you will exigency to contact your IT departments on how they manage opening of ports.

    Normally in a production environment, you would believe the servers in an internal DNS system, however for the sake of this blog they will disburse hosts files for the purpose of names. They want to edit the /etc/hosts file on the three MongoDB guests as well as the hosts.

    The information they will subsist using will subsist as follows:

    To carryout so on each of the guests carryout the following:

  • Log in.
  • Find your host only network interface by looking for the interface on the host only network 10.1.2.0/24: # sudo ip addr
  • Edit the network interface, in their case the interface was enp0s8: # sudo vi /etc/sysconfig/network-scripts/ifcfg-enp0s8
  • You will want to change the ONBOOT and BOOTPROTO to the following and add the three lines for IP address, netmask, and Broadcast. Note: the IP address should subsist based upon the table above. They should match the info below: ONBOOT=yes BOOTPROTO=static IPADDR=10.1.2.10 NETMASK-255.255.255.0 BROADCAST=10.1.2.255
  • Disable the firewall with: # systemctl discontinue firewalld # systemctl disable firewalld
  • Edit the hostname using the commandeer values from the table above.  # hostnamectl set-hostname "mongo-db1" --static
  • Edit the hosts file adding the following to etc/hosts, you should moreover carryout this on the guest: 10.1.2.10 mongo-db1 10.1.2.11 mongo-db2 10.1.2.12 mongo-db3
  • Restart the guest.
  • Try to SSH by hostname.
  • Also, try pinging each guest by hostname from guests and host.
  • Ops Manager

    MongoDB Ops Manager can subsist leveraged throughout the development, test, and production lifecycle, with faultfinding functionality ranging from cluster performance monitoring data, alerting, no-downtime upgrades, advanced configuration and scaling, as well as backup and restore. Ops Manager can subsist used to manage up to thousands of distinct MongoDB clusters in a tenants-per-cluster fashion — isolating cluster users to specific clusters.

    All major MongoDB Ops Manager actions can subsist driven manually through the user interface or programmatically through the comfort API, where Ops Manager can subsist deployed by platform teams offering Enterprise MongoDB as a Service back-ends to application teams.

    Specifically, Ops Manager can deploy any MongoDB cluster topology across bare metal or virtualized hosts, or in private or public cloud environments. A production MongoDB cluster will typically subsist deployed across a minimum of three hosts in three distinct availability areas — physical servers, racks, or data centers. The loss of one host will soundless preserve a quorum in the remaining two to ensure always-on availability.

    Ops Manager can deploy a MongoDB cluster (replica set or sharded cluster) across the hosts with Ops Manager agents running, using any desired MongoDB version and enabling access control (authentication and authorization) so that only client connections presenting the remedy credentials are able to access the cluster. The MongoDB cluster can moreover disburse SSL/TLS for over the wire encryption.

    Once a MongoDB cluster is successfully deployed by Ops Manager, the cluster’s connection string can subsist easily generated (in the case of a MongoDB replica set, this will subsist the three hostname:port pairs separated by commas). An OpenShift application can then subsist configured to disburse the connection string and authentication credentials to this MongoDB cluster.

    To disburse Ops Manager with Ansible and OpenShift:

  • Install and disburse a MongoDB Ops Manager, and record the URL that it is accessible at (“OpsManagerCentralURL”)
  • Ensure that the MongoDB Ops Manager is accessible over the network at the OpsManagerCentralURL from the servers (VMs) where they will deploy MongoDB. (Note that the transpose is not necessary; in other words, Ops Manager does not exigency to subsist able to compass into the managed VMs directly over the network).
  • Spawn servers (VMs) running Red Hat Enterprise Linux, able to compass each other over the network at the hostnames returned by “hostname -f” on each server respectively, and the MongoDB Ops Manager itself, at the OpsManagerCentralURL.
  • Create an Ops Manager Group, and record the group’s unique identifier (“mmsGroupId”) and Agent API key (“mmsApiKey”) from the group’s ‘Settings’ page in the user interface.
  • Use Ansible to configure the VMs to start the MongoDB Ops Manager Automation Agent (available for download directly from the Ops Manager). disburse the Ops Manager UI (or comfort API) to instruct the Ops Manager agents to deploy a MongoDB replica set across the three VMs.
  • Ansible Install

    By having three MongoDB instances that they want to install the automation agent it would subsist effortless enough to login and elude the commands as seen in the Ops Manager agent installation information. However they believe created an ansible playbook that you will exigency to change to customize.

    The playbook looks like:

    - hosts: mongoDBNodes vars: OpsManagerCentralURL: <baseURL> mmsGroupId: <groupID> mmsApiKey: <ApiKey> remote_user: root tasks: - name: install automation agent RPM from OPS manager instance @ {{ OpsManagerCentralURL }} yum: name={{ OpsManagerCentralURL }}/download/agent/automation/mongodb-mms-automation-agent-manager-latest.x86_64.rhel7.rpm state=present - name: write the MMS Group ID as {{ mmsGroupId }} lineinfile: dest=/etc/mongodb-mms/automation-agent.config regexp=^mmsGroupId= line=mmsGroupId={{ mmsGroupId }} - name: write the MMS API Key as {{ mmsApiKey }} lineinfile: dest=/etc/mongodb-mms/automation-agent.config regexp=^mmsApiKey= line=mmsApiKey={{ mmsApiKey }} - name: write the MMS base URL as {{ OpsManagerCentralURL }} lineinfile: dest=/etc/mongodb-mms/automation-agent.config regexp=^mmsBaseUrl= line=mmsBaseUrl={{ OpsManagerCentralURL }} - name: create MongoDB data directory file: path=/data state=directory owner=mongod group=mongod - name: ensure MongoDB MMS Automation Agent is started service: name=mongodb-mms-automation-agent state=started

    You will exigency to customize it with the information you gathered from the Ops Manager.

    You will exigency to create this file as your root user and then update the /etc/ansible/hosts file and add the following lines:

    [mongoDBNodes] mongo-db1 mongo-db2 mongo-db3

    Once this is done you are ready to elude the ansible playbook. This playbook will contact your Ops Manager Server, download the latest client, update the client config files with your APiKey and Groupid, install the client and then start the client. To elude the playbook you exigency to execute the command as root:

    ansible-playbook –v mongodb-agent-playbook.yml

    Use MongoDB Ops Manager to create a MongoDB Replica Set and add database users with commandeer access rights:

  • Verify that everysingle of the Ops Manager agents believe started in the MongoDB Ops Manager group’s Deployment interface.
  • Navigate to "Add” > ”New Replica Set" and define a Replica Set with desired configuration (MongoDB 3.2, default settings).
  • Navigate to "Authentication & SSL Settings" in the "..." menu and enable MongoDB Username/Password (SCRAM-SHA-1) Authentication.
  • Navigate to the "Authentication & Users" panel and add a database user to the sampledb a. Add the testUser@sampledb user, with password set to "password", and with Roles: readWrite@sampledb dbOwner@sampledb dbAdmin@sampledb userAdmin@sampledb Roles.
  • Click Review & Deploy.
  • OpenShift Continuous Deployment

    Up until now, we’ve explored the Red Hat container ecosystem, the Red Hat Container progress Kit (CDK), OpenShift as a local deployment, and OpenShift in production. In this final section, we’re going to grasp a searchfor at how a team can grasp edge of the advanced features of OpenShift in order to automatically skedaddle current versions of applications from progress to production — a process known as Continuous Delivery (or Continuous Deployment, depending on the flush of automation).

    OpenShift supports different setups depending on organizational requirements. Some organizations may elude a completely sever cluster for each environment (e.g. dev, staging, production) and others may disburse a lone cluster for several environments. If you elude a sever OpenShift PaaS for each environment, they will each believe their own dedicated and isolated resources, which is costly but ensures isolation (a problem with the progress cluster cannot strike production). However, multiple environments can safely elude on one OpenShift cluster through the platform’s uphold for resource isolation, which allows nodes to subsist dedicated to specific environments. This means you will believe one OpenShift cluster with common masters for everysingle environments, but dedicated nodes assigned to specific environments. This allows for scenarios such as only allowing production projects to elude on the more powerful / expensive nodes.

    OpenShift integrates well with existing Continuous Integration / Continuous Delivery tools. Jenkins, for example, is available for disburse inside the platform and can subsist easily added to any projects you’re planning to deploy. For this demo however, they will stick to out-of-the-box OpenShift features, to attest workflows can subsist constructed out of the OpenShift fundamentals.

    A Continuous Delivery Pipeline with CDK and OpenShift Enterprise

    The workflow of their continuous delivery pipeline is illustrated below:

    The diagram shows the developer on the left, who is working on the project in their own environment. In this case, the developer is using Red Hat’s CDK running on their local-machine, but they could equally subsist using a progress environment provisioned in a remote OpenShift cluster.

    To skedaddle code between environments, they can grasp edge of the image streams concept in OpenShift. An image stream is superficially similar to an image repository such as those found on Docker Hub — it is a collection of related images with identifying names or “tags”. An image stream can advert to images in Docker repositories (both local and remote) or other image streams. However, the killer feature is that OpenShift will generate notifications whenever an image stream changes, which they can easily configure projects to listen and react to. They can view this in the diagram above — when the developer is ready for their changes to subsist picked up by the next environment in line, they simply tag the image appropriately, which will generate an image stream notification that will subsist picked up by the staging environment. The staging environment will then automatically rebuild and redeploy any containers using this image (or images who believe the changed image as a base layer). This can subsist fully automated by the disburse of Jenkins or a similar CI tool; on a check-in to the source control repository, it can elude a test-suite and automatically tag the image if it passes.

    To skedaddle between staging and production they can carryout exactly the selfsame thing — Jenkins or a similar instrument could elude a more thorough set of system tests and if they pass tag the image so the production environment picks up the changes and deploys the current versions. This would subsist real Continuous Deployment — where a change made in dev will propagate automatically to production without any manual intervention. Many organizations may instead opt for Continuous Delivery — where there is soundless a manual “ok” required before changes hit production. In OpenShift this can subsist easily done by requiring the images in staging to subsist tagged manually before they are deployed to production.

    Deployment of an OpenShift Application

    Now that we’ve reviewed the workflow, let’s searchfor at a real case of pushing an application from progress to production. They will disburse the simple MLB Parks application from a previous blog post that connects to MongoDB for storage of persistent data. The application displays various information about MLB parks such as league and city on a map. The source code is available in this GitHub repository. The case assumes that both environments are hosted on the selfsame OpenShift cluster, but it can subsist easily adapted to allow promotion to another OpenShift instance by using a common registry.

    If you don’t already believe a working OpenShift instance, you can quickly comeby started by using the CDK, which they moreover covered in an earlier blogpost. Start by logging in to OpenShift using your credentials:

    $ oc login -u openshift-dev

    Now we’ll create two current projects. The first one represents the production environment (mlbparks-production):

    $ oc new-project mlbparks-production Now using project "mlbparks-production" on server "https://localhost:8443".

    And the second one will subsist their progress environment (mlbparks):

    $ oc new-project mlbparks Now using project "mlbparks" on server "https://localhost:8443".

    After you elude this command you should subsist in the context of the progress project (mlbparks). We’ll start by creating an external service to the MongoDB database replica-set.

    Openshift allows us to access external services, allowing their projects to access services that are outside the control of OpenShift. This is done by defining a service with an blank selector and an endpoint. In some cases you can believe multiple IP addresses assigned to your endpoint and the service will act as a load balancer. This will not travail with the MongoDB replica set as you will encounter issues not being able to connect to the PRIMARY node for writing purposes. To allow for this in this case you will exigency to create one external service for each node. In their case they believe three nodes so for illustrative purposes they believe three service files and three endpoint files.

    Service Files: replica-1_service.json

    { "kind": "Service", "apiVersion": "v1", "metadata": { "name": "replica-1" }, "spec": { "selector": { }, "ports": [ { "protocol": "TCP", "port": 27017, "targetPort": 27017 } ] } }

    replica-1_endpoints.json

    { "kind": "Endpoints", "apiVersion": "v1", "metadata": { "name": "replica-1" }, "subsets": [ { "addresses": [ { "ip": "10.1.2.10" } ], "ports": [ { "port": 27017 } ] } ] }

    replica-2_service.json

    { "kind": "Service", "apiVersion": "v1", "metadata": { "name": "replica-2" }, "spec": { "selector": { }, "ports": [ { "protocol": "TCP", "port": 27017, "targetPort": 27017 } ] } }

    replica-2_endpoints.json

    { "kind": "Endpoints", "apiVersion": "v1", "metadata": { "name": "replica-2" }, "subsets": [ { "addresses": [ { "ip": "10.1.2.11" } ], "ports": [ { "port": 27017 } ] } ] }

    replica-3_service.json

    { "kind": "Service", "apiVersion": "v1", "metadata": { "name": "replica-3" }, "spec": { "selector": { }, "ports": [ { "protocol": "TCP", "port": 27017, "targetPort": 27017 } ] } }

    replica-3_endpoints.json

    { "kind": "Endpoints", "apiVersion": "v1", "metadata": { "name": "replica-3" }, "subsets": [ { "addresses": [ { "ip": "10.1.2.12" } ], "ports": [ { "port": 27017 } ] } ] }

    Using the above replica files you will exigency to elude the following commands:

    $ oc create -f replica-1_service.json $ oc create -f replica-1_endpoints.json $ oc create -f replica-2_service.json $ oc create -f replica-2_endpoints.json $ oc create -f replica-3_service.json $ oc create -f replica-3_endpoints.json

    Now that they believe the endpoints for the external replica set created they can now create the MLB parks using a template. They will disburse the source code from their demo GitHub repo and the s2i build strategy which will create a container for their source code (note this repository has no Dockerfile in the offshoot they use). everysingle of the environment variables are in the mlbparks-template.json, so they will first create a template then create their current app:

    $ oc create -f https://raw.githubusercontent.com/macurwen/openshift3mlbparks/master/mlbparks-template.json $ oc new-app mlbparks --> Success Build scheduled for "mlbparks" - disburse the logs command to track its progress. elude 'oc status' to view your app.

    As well as pile the application, note that it has created an image stream called mlbparks for us.

    Once the build has finished, you should believe the application up and running (accessible at the hostname found in the pod of the web ui) built from an image stream.

    We can comeby the name of the image created by the build with the abet of the record command:

    $ oc record imagestream mlbparks Name: mlbparks Created: 10 minutes ago Labels: app=mlbparks Annotations: openshift.io/generated-by=OpenShiftNewApp openshift.io/image.dockerRepositoryCheck=2016-03-03T16:43:16Z Docker tug Spec: 172.30.76.179:5000/mlbparks/mlbparks Tag Spec Created PullSpec Image latest <pushed> 7 minutes ago 172.30.76.179:5000/mlbparks/mlbparks@sha256:5f50e1ffbc5f4ff1c25b083e1698c156ca0da3ba207c619781efcfa5097995ec

    So OpenShift has built the image mlbparks@sha256:5f50e1ffbc5f4ff1c25b083e1698c156ca0da3ba207c619781efcfa5097995ec, added it to the local repository at 172.30.76.179:5000 and tagged it as latest in the mlbparks image stream.

    Now they know the image ID, they can create a tag that marks it as ready for disburse in production (use the SHA of your image here, but remove the IP address of the registry):

    $ oc tag mlbparks/mlbparks\ @sha256:5f50e1ffbc5f4ff1c25b083e1698c156ca0da3ba207c619781efcfa5097995ec \ mlbparks/mlbparks:production Tag mlbparks:production set to mlbparks/mlbparks@sha256:5f50e1ffbc5f4ff1c25b083e1698c156ca0da3ba207c619781efcfa5097995ec.

    We’ve intentionally used the unique SHA hash of the image rather than the tag latest to identify their image. This is because they want the production tag to subsist tied to this particular version. If they hadn’t done this, production would automatically track changes to latest, which would comprehend untested code.

    To allow the production project to tug the image from the progress repository, they exigency to vouchsafe tug rights to the service account associated with production environment. Note that mlbparks-production is the name of the production project:

    $ oc policy add-role-to-group system:image-puller \ system:serviceaccounts:mlbparks-production \ --namespace=mlbparks To verify that the current policy is in place, they can check the rolebindings: $ oc comeby rolebindings NAME ROLE USERS GROUPS SERVICE ACCOUNTS SUBJECTS admins /admin catalin system:deployers /system:deployer deployer system:image-builders /system:image-builder builder system:image-pullers /system:image-puller system:serviceaccounts:mlbparks, system:serviceaccounts:mlbparks-production

    OK, so now they believe an image that can subsist deployed to the production environment. Let’s switch the current project to the production one:

    $ oc project mlbparks-production Now using project "mlbparks" on server "https://localhost:8443".

    To start the database we’ll disburse the selfsame steps to access the external MongoDB as previous:

    $ oc create -f replica-1_service.json $ oc create -f replica-1_endpoints.json $ oc create -f replica-2_service.json $ oc create -f replica-2_endpoints.json $ oc create -f replica-3_service.json $ oc create -f replica-3_endpoints.json

    For the application Part we’ll subsist using the image stream created in the progress project that was tagged “production”:

    $ oc new-app mlbparks/mlbparks:production --> found image 5621fed (11 minutes old) in image stream "mlbparks in project mlbparks" under tag :production for "mlbparks/mlbparks:production" * This image will subsist deployed in deployment config "mlbparks" * Port 8080/tcp will subsist load balanced by service "mlbparks" --> Creating resources with label app=mlbparks ... DeploymentConfig "mlbparks" created Service "mlbparks" created --> Success elude 'oc status' to view your app.

    This will create an application from the selfsame image generated in the previous environment.

    You should now find the production app is running at the provided hostname.

    We will now demonstrate the talent to both automatically skedaddle current items to production, but they will moreover attest how they can update an application without having to update the MongoDB schema. They believe created a offshoot of the code in which they will now add the division to the league for the ballparks, without updating the schema.

    Start by going back to the progress project:

    $ oc project mlbparks Now using project "mlbparks" on server "https://10.1.2.2:8443". And start a current build based on the confide “8a58785”: $ oc start-build mlbparks --git-repository=https://github.com/macurwen/openshift3mlbparks/tree/division --commit='8a58785'

    Traditionally with a RDBMS if they want to add a current component to in their application to subsist persisted to the database, they would exigency to execute the changes in the code as well as believe a DBA manually update the schema at the database. The following code is an case of how they can modify the application code without manually making changes to the MongoDB schema.

    BasicDBObject updateQuery = current BasicDBObject(); updateQuery.append("$set", current BasicDBObject() .append("division", "East")); BasicDBObject searchQuery = current BasicDBObject(); searchQuery.append("league", "American League"); parkListCollection.updateMulti(searchQuery, updateQuery);

    Once the build finishes running, a deployment stint will start that will replace the running container. Once the current version is deployed, you should subsist able to view East under Toronto for example.

    If you check the production version, you should find it is soundless running the previous version of the code.

    OK, we’re joyful with the change, let’s tag it ready for production. Again, elude oc to comeby the ID of the image tagged latest, which they can then tag as production:

    $ oc tag mlbparks/mlbparks@\ sha256:ceed25d3fb099169ae404a52f50004074954d970384fef80f46f51dadc59c95d \ mlbparks/mlbparks:production Tag mlbparks:production set to mlbparks/mlbparks@sha256:ceed25d3fb099169ae404a52f50004074954d970384fef80f46f51dadc59c95d.

    This tag will trigger an automatic deployment of the current image to the production environment.

    Rolling back can subsist done in different ways. For this example, they will roll back the production environment by tagging production with the former image ID. Find the birthright id by running the oc command again, and then tag it:

    $ oc tag mlbparks/mlbparks@\ sha256:5f50e1ffbc5f4ff1c25b083e1698c156ca0da3ba207c619781efcfa5097995ec \ mlbparks/mlbparks:production Tag mlbparks:production set to mlbparks/mlbparks@sha256:5f50e1ffbc5f4ff1c25b083e1698c156ca0da3ba207c619781efcfa5097995ec. Conclusion

    Over the course of this post, we’ve investigated the Red Hat container ecosystem and OpenShift Container Platform in particular. OpenShift builds on the advanced orchestration capabilities of Kubernetes and the reliability and stability of the Red Hat Enterprise Linux operating system to provide a powerful application environment for the enterprise. OpenShift adds several ideas of its own that provide necessary features for organizations, including source-to-image tooling, image streams, project and user isolation and a web UI. This post showed how these features travail together to provide a complete CD workflow where code can subsist automatically pushed from progress through to production combined with the power and capabilities of MongoDB as the backend of altenative for applications.


    Beginning DB2: From Novice to Professional | killexams.com real questions and Pass4sure dumps

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    Trainers [3 Certification Exam(s) ]
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    USMLE [1 Certification Exam(s) ]
    VCE [6 Certification Exam(s) ]
    Veeam [2 Certification Exam(s) ]
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    References :


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    Dropmark-Text : http://killexams.dropmark.com/367904/12946362
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