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C2090-610 exam Dumps Source : DB2 10.1 Fundamentals

Test Code : C2090-610
Test designation : DB2 10.1 Fundamentals
Vendor designation : IBM
exam questions : 138 true Questions

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IBM IBM DB2 10.1 Fundamentals

A e book to the IBM DB2 9 Fundamentals certification exam | killexams.com true Questions and Pass4sure dumps

here excerpt from DB2 9 Fundamentals: Certification anatomize ebook, written by Roger E. Sanders, is reprinted with license from MC Press. study the complete Chapter 1, A ebook to the IBM DB2 9 certification examination in case you believe taking a DB2 9 Fundamentals certification examination could live your subsequent career stream.

The IBM DB2 9 certification process

a immediate examination of the IBM certification roles purchasable immediately displays that, with the intent to obtain a selected DB2 9 certification, you must assume and circulate one or more exams that gain been designed notably for that certification position. (each and every examination is a utility-based exam it truly is neither platform -- nor product-specific.) as a result, once you gain chosen the certification role you need to pursue and familiarized yourself with the requirements for that particular function, the next step is to prepare for and assume the acceptable certification assessments.

preparing for the IBM DB2 9 certification exams

you probably gain adventure using DB2 9 within the context of the certification office you've got chosen, you can moreover already possess the knowledge and knowledge obligatory to flow the examination(s) required for that position. despite the fact, in case your suffer with DB2 9 is proscribed (and notwithstanding it isn't), that you can consequence together for any of the certification checks available with the aid of taking odds of here supplies:

  • Formal schooling
  • IBM studying capabilities presents lessons that are designed to aid you consequence together for DB2 9 certification. a listing of the courses which are recommended for each certification exam can live discovered the usage of the Certification Navigator device offered on IBM's "professional Certification program from IBM " internet site. informed classes can even live institute at IBM's "DB2 statistics management" internet site. For extra information on path schedules, areas, and pricing, contact IBM gaining knowledge of services or consult with their web web page.

  • on-line tutorials
  • IBM offers a series of seven interactive on-line tutorials designed to consequence together you for the DB2 9 Fundamentals examination (examination 730). IBM moreover presents a sequence of interactive on-line tutorials designed to prepare you for the DB2 9 for Linux, UNIX, and windows Database Administration examination (examination 731) and the DB2 9 family utility edifice examination (exam 733).

  • Publications
  • all of the counsel you should pass any of the obtainable certification tests will moreover live present in the documentation that is supplied with DB2 9. a complete set of manuals comes with the product and are obtainable during the information middle after getting installed the DB2 9 application. DB2 9 documentation can even live downloaded from IBM's web website in both HTML and PDF formats. @39202

    Self-look at books (equivalent to this one) that seat of attention on one or more DB2 9 certification tests/roles are moreover attainable. most of these books will moreover live discovered at your local book shop or ordered from many online e-book retailers. (a catalogue of possible reference materials for each certification exam will moreover live discovered using the Certification Navigator implement offered on IBM's "expert Certification software from IBM" internet web page.)

    besides the DB2 9 product documentation, IBM often produces manuals, referred to as "RedBooks," that cowl advanced DB2 9 issues (in addition to different topics). These manuals are available as downloadable PDF information on IBM's RedBook web web site. Or, if you favor to gain a certain tough reproduction, that you could gather one for a modest fee with the aid of following the applicable hyperlinks on the RedBook web web page. (There is not any permeate for the downloadable PDF data.)

  • exam aims
  • goals that deliver an profile of the simple topics which are covered on a specific certification examination can live institute the usage of the Certification Navigator device provided on IBM's "professional Certification application from IBM" web website. examination goals for the DB2 9 household Fundamentals exam (examination 730) can even live present in Appendix A of this ebook.

  • sample questions/assessments
  • pattern questions and pattern exams spell you can rotate into criterion with the structure and wording used on the actual certification assessments. they can aid you settle no matter if you possess the abilities mandatory to flow a particular exam. sample questions, along with descriptive answers, are provided at the halt of every chapter in this book and in Appendix B. pattern exams for every DB2 9 certification office obtainable will moreover live discovered the exhaust of the Certification examination implement provided on IBM's "skilled Certification application from IBM" web web site. there's a $10 cost for each exam taken.

    it is vital to live awake that the certification tests are designed to live rigorous. Very unavoidable solutions are anticipated for most examination questions. because of this, and because the latitude of material covered on a certification examination is constantly broader than the knowledge groundwork of many DB2 9 gurus, manufacture certain to assume potential of the examination practise components obtainable in case you need to assure your success in obtaining the certification(s) you desire.

  • The ease of this chapter details complete accessible DB2 9 certifications and includes lists of cautioned objects to know before taking the exam. It additionally describes the layout of the checks and what to are expecting on exam day. study the complete Chapter 1: A book to the IBM DB2 9 certification exam to learn greater.


    IBM: revenue Play With Very negative total revert | killexams.com true Questions and Pass4sure dumps

    No consequence discovered, are attempting current keyword!Fundamentals of IBM could live reviewed in here themes under ... lately, on June 19, I trimmed Boeing (NYSE:BA) from 10.1% of the portfolio to 9.6%. it's a fine business, however you need to live di...

    Mainframe statistics Is Your clandestine Sauce: A Recipe for statistics protection | killexams.com true Questions and Pass4sure dumps

    Mainframe statistics Is Your clandestine Sauce: A Recipe for information insurance policy July 31, 2017  |  with the aid of Kathryn Zeidenstein A chef drizzling sauce on a plate of food.

    Bigstock

    Share Mainframe statistics Is Your clandestine Sauce: A Recipe for facts coverage on Twitter participate Mainframe information Is Your clandestine Sauce: A Recipe for facts insurance blueprint on fb participate Mainframe data Is Your clandestine Sauce: A Recipe for information coverage on LinkedIn

    We in the safety box relish to exhaust metaphors to serve illustrate the magnitude of facts within the business. I’m a big fan of cooking, so I’ll exhaust the metaphor of a clandestine sauce. account about it: each transaction in fact reflects your firm’s gripping relationship with a customer, agency or associate. via sheer volume alone, mainframe transactions supply an immense variety of ingredients that your organization makes exhaust of to manufacture its clandestine sauce — improving consumer relationships, tuning give chain operations, dawn current lines of company and more.

    extremely essential records flows via and into mainframe information stores. definitely, ninety two of the rectify a hundred banks depend on the mainframe as a result of its velocity, scale and safety. additionally, greater than 29 billion ATM transactions are processed per 12 months, and 87 percent of complete credit card transactions are processed in the course of the mainframe.

    Safeguarding Your clandestine Sauce

    the excitement has been improbable for the coincident IBM z14 announcement, which includes pervasive encryption, tamper-responding key management and even encrypted software software interfaces (APIs). The pace and scale of the pervasive encryption solution is breathtaking.

    Encryption is a basic expertise to protect your clandestine sauce, and the brand current convenient-to-use crypto capabilities in the z14 will manufacture encryption a no-brainer.

    With complete of the exhilaration round pervasive encryption, even though, it’s principal not to fail to contemplate yet another element that’s essential for statistics safety: records undertaking monitoring. imagine complete the functions, features and administrators as cooks in a kitchen. How can you manufacture certain that individuals are correctly following the recipe? How achieve you manufacture unavoidable that they aren’t jogging off with your clandestine sauce and growing competitive recipes or selling it on the black market?

    Watch the on-demand webinar: Is Your fine facts included?

    information protection and activity Monitoring

    facts exercise monitoring provides insights into access behavior — that is, the who, what, where and when of entry for DB2, the counsel management system (IMS) and the file gadget. for example, by using information pastime monitoring, you can live able to inform no matter if the top chef (i.e., the database or gadget administrator) is working from a several locality or working irregular hours.

    additionally, statistics activity monitoring raises the visibility of surprising oversight circumstances. If an utility begins throwing a few extraordinary database error, it may well live a demonstration that an SQL injection assail is underway. Or perhaps the utility is barely poorly written or maintained — most likely tables were dropped or application privileges gain modified. This visibility can serve companies slice back database overhead and risk via bringing these issues to mild.

    Then there’s compliance, each person’s favorite theme. You deserve to live capable of exhibit to auditors that compliance mandates are being followed, even if that includes monitoring privileged users, not enabling unauthorized database adjustments or tracking complete access to permeate card industry (PCI) information. With the eu’s accustomed facts protection legislation (GDPR) set to assume repercussion in may additionally 2018, the stakes are even bigger.

    Automating believe, Compliance and safety

    As allotment of a finished statistics insurance policy approach for the mainframe, IBM security Guardium for z/OS provides distinctive, granular, actual-time recreation monitoring capabilities as well as precise-time alerting, out-of-the-box compliance reporting and an obnoxious lot more. The most up-to-date liberate, 10.1.three, provides statistics insurance blueprint improvements in addition to efficiency improvements to serve retain your prices and overhead down.

    Your mainframe records is valuable — it's your clandestine sauce. As such, it will live stored beneath lock and key, and monitored constantly.

    To live taught extra about monitoring and maintaining information in mainframe environments, watch their on-demand webinar, “Your Mainframe environment Is a Treasure Trove: Is Your fine statistics included?”

    Tags: Compliance | information coverage | Encryption | Mainframe | Mainframe protection | payment Card trade (PCI) Kathryn Zeidenstein

    expertise Evangelist and group recommend, IBM safety Guardium

    Kathryn Zeidenstein is a expertise evangelist and group recommend for IBM safety Guardium records insurance policy... 13 Posts What’s new
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    C2090-610 DB2 10.1 Fundamentals

    Study guide Prepared by Killexams.com IBM Dumps Experts


    Killexams.com C2090-610 Dumps and true Questions

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    C2090-610 exam Dumps Source : DB2 10.1 Fundamentals

    Test Code : C2090-610
    Test designation : DB2 10.1 Fundamentals
    Vendor designation : IBM
    exam questions : 138 true Questions

    Get those C2090-610 exam questions , prepare and chillout!
    killexams.com gave me an extraordinary practise tool. I used it for my C2090-610 exam and were given a most rating. i really relish the course killexams.com does their examination preparation. essentially, that is a sell off, so you derive questions which can live used on the true C2090-610 assessments. however the trying out engine and the exercise examination format serve you memorize it complete very well, so you grow to live getting to know matters, and can live able to draw upon this expertise within the destiny. superb best, and the checking out engine is very light and consumer pleasant. I didnt encounter any issues, so this is exceptional cost for cash.


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    No time to assume a survey at books! need some thing speedy preparing.
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    Altova Introduces Version 2014 of Its Developer Tools and Server Software | killexams.com true 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 embrace integration with the lightning rapidly validation and processing capabilities of RaptorXML®, back for Schema 1.1, XPath/XSLT/XQuery 3.0, back for current databases and much more. current features in Altova server products embrace caching options in FlowForce® Server and increased performance powered by RaptorXML across the server product line.

    "We are so excited to live able to extend the hyper-performance delivered by the unparalleled RaptorXML Server to developers working in their desktop tools. This functionality, along with robust back 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 ability to automate essential processes via their high-performance server products, gives their customers a several odds when edifice 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 possible standards conformance. Now the same hyper-performance engine that powers RaptorXML Server is fully integrated in several Altova MissionKit tools, including XMLSpy, MapForce®, and SchemaAgent®, delivering lightning rapidly 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 back the very latest of complete apropos 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 principal back 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 springy and adaptable to business 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 light 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 odds 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 embrace 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 office cells, inline office expressions, and back for union types to designation just a few. Full back 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. gratify note that a subset of XSLT 3.0 is supported since the criterion is silent a working draft that continues to evolve. XSLT 3.0 back conforms to the W3C XSLT 3.0 Working Draft of July 10, 2012 and the XPath 3.0 Candidate Recommendation. However, back in XMLSpy now gives developers the ability to start working with this current version immediately.

    XSLT 3.0 takes odds 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 live used to trap and recoup from dynamic errors. Other enhancements in XSLT 3.0 embrace back for higher order functions and partial functions.

    Story continues

    As with XSLT and XPath, XMLSpy back for XQuery now moreover includes a subset of version 3.0. Developers will now gain 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 -- complete 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 embrace complete back for newer versions of previously supported databases, as well as back 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 business processes, while MapForce Server and StyleVision Server offer high-speed automation for projects designed using familiar 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 involved database queries or needs to manufacture 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 live 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 live a qualified 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 ordeal downloads gratify 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 evolution tools. Altova focuses on its customers' needs by offering a product line that fulfills a broad spectrum of requirements for software evolution teams. With over 4.5 million users worldwide, including 91% of Fortune 500 organizations, Altova is disdainful 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 live the trademarks of their respective owners.


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

    Current evolution cycles pan many challenges such as an evolving landscape of application architecture (Monolithic to Microservices), the need to frequently deploy features, and current IaaS and PaaS environments. This causes many issues throughout the organization, from the evolution teams complete the course to operations and management.

    In this blog post, they will exhibit you how you can set up a local system that will back MongoDB, MongoDB Ops Manager, and OpenShift. They will walk through the various installation steps and demonstrate how light it is to achieve agile application evolution with MongoDB and OpenShift.

    MongoDB is the next-generation database that is built for rapid and iterative application development. Its springy data model — the ability 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 serve manage a involved 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 live 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 evolution tooling enlarge 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 need to meet a number of requirements. You will need 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 big 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 allotment of the MongoDB replica set. The Automation Agent is allotment of MongoDB Ops Manager.

    In order to install Ansible using yum you will need 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 supplant or combat with the groundwork RHEL packages.

    The EPEL repository has a dependency on the Server Optional and Server Extras repositories. To enable these repositories you will need 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 need to achieve 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 live used to manage the lifecycle of a virtual machine. This implement is used for the installation and management of the Red Hat Container evolution Kit.

    Vagrant is not included in any criterion repository, so they will need to install it. You can install Vagrant by enabling the SCLO repository or you can derive it directly from the Vagrant website. They will exhaust 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 evolution Kit requires a virtualization software stack to execute. In this blog they will exhaust VirtualBox for the virtualization software.

    VirtualBox is best done using a repository to ensure you can derive updates. To achieve this you will need 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 rectify 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 rectify domain:

  • Open VirtualBox, this should live 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 live a vboxnet0 as the network, click on it and click on the edit icon (looks relish 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 hasten the same course on every platform. However, modern microservice deployments typically exhaust a scheduler such as Kubernetes to hasten 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 evolution Kit (CDK).

    The Red Hat CDK is a customized virtual machine that makes it light to hasten involved deployments resembling production. This means involved applications can live developed using production grade tools from the very start, sense developers are unlikely to suffer problems stemming from differences in the evolution 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 depart through the entire workflow. By the halt of this blog post you will know how to hasten an application on top of OpenShift and will live familiar with the core features of the CDK and OpenShift. Let’s derive started…

    Installing the CDK

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

    Start by going to Red Hat Product Downloads (note that you will need a Red Hat subscription to access this). Select ‘Red Hat Container evolution Kit’ under Product Variant, and the confiscate 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 serve 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 live 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 designation 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 exhaust the Vagrantfile that comes shipped with the CDK and has back for OpenShift.

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

    In order to exhaust the landrush plugin to configure the DNS they need 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 need to live 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 live reachable only by IP address from within the VM.

    Save the changes and start the virtual machine :

    $ vagrant up

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

    Let’s review what just happened here. On your local machine, you now gain 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 derive a private Docker registry for storing images. Docker, Kubernetes, OpenShift and Atomic App CLIs are moreover installed.

    Now that they gain 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 live 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 live openshift-dev/devel. You can moreover exhaust 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 haul specific images. These are an light course to quickly derive 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 exhaust the source code from the OpenShift GitHub repository located here. If you want to supervene along with the webhook steps later, you’ll need 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 principal to us – GITHUB_WEBHOOK_SECRET and APPLICATION_DOMAIN:

  • GITHUB_WEBHOOK_SECRET: this bailiwick allows us to create a clandestine to exhaust with the GitHub webhook for automatic builds. You don’t need to specify this, but you’ll need to recollect the value later if you do.
  • APPLICATION_DOMAIN: this bailiwick will determine where they can access their application. This value must embrace the Top plane 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 exhaust it later on.

    OpenShift will then haul the code from GitHub, find the confiscate 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 survey relish this:

    In order to exhaust the Landrush plugin, there is additional steps that are required to configure dnsmasq. To achieve that you will need to achieve 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 need 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 need a course of routing from the public internet to the Vagrant machine running on your host. An light course to achieve this is to exhaust a third party forwarding service such as ultrahook or ngrok. They need 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 depart to Settings -> Webhooks & services -> Add webhook. Under Payload URL enter the URL that the forwarding service gave you, plus the clandestine (if you specified one when setting up the OpenShift project). If your webhook is configured correctly you should contemplate something relish this:

    To test out the pipeline, they need to manufacture a change to their project and shove a commit to the repo.

    Any light course to achieve this is to edit the views/index.html file, e.g: (Note that you can moreover achieve this through the GitHub web interface if you’re fire lazy). commit and shove this change to the GitHub repo, and they can contemplate a current build is triggered automatically within the web console. Once the build completes, if they again open their application they should contemplate the updated front page.

    We now gain Continuous Deployment configured for their application. Throughout this blog post, we’ve used the OpenShift web interface. However, they could gain performed the same actions using the OpenShift console (oc) at the command-line. The easiest course 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 live deployed to a node together. A pod represents the smallest unit that can live deployed and managed in OpenShift. The pod will live assigned its own IP address. complete of the containers in the pod will participate local storage and networking.

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

    For their instance application, they gain a Pod running the application. Pods can live scaled up/down from the OpenShift interface.

    Replication Controllers

    These manage the lifecycle of Pods.They ensure that the rectify 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 commit (assuming you set-up the GitHub webhooks) OpenShift will update your application. current pods will live started with the serve of replication controllers running your current application version. The worn pods will live deleted. OpenShift deployments can accomplish rollbacks and provide various deploy strategies. It’s arduous to overstate the advantages of being able to hasten a production environment in evolution and the efficiencies gained from the rapidly feedback cycle of a Continuous Deployment pipeline.

    In this post, they gain shown how to exhaust the Red Hat CDK to achieve both of these goals within a short-time frame and now gain a Node.js and MongoDB application running in containers, deployed using the OpenShift PaaS. This is a august course to quickly derive 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 live required to set up the replica set. They will not walk through complete of the steps of setting up Red Hat as this is prerequisite knowledge.

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

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

    Please accomplish the following steps:

  • In VirtualBox create a current guest image and convoke it RHEL Base. They used the following information: a. recollection 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 achieve a yum update on the guest RHEL install.

    The final step will live to generate current ssh keys for the root user and transfer the keys to the guest machine. To achieve that gratify achieve the following steps:

  • Become the root user $ sudo -i
  • Generate your ssh keys. achieve not add a passphrase when requested.  # ssh-keygen
  • You need 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 gain a best exercise for doing this. If this is the first guest in your VirtualBox then it should gain an ip of 10.1.2.101, if it has another ip then you will need to supplant for the following. For this blog gratify 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 screen 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 live asked for any login information.
  • Once this is complete you can shut down the RHEL groundwork 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 designation 7.2 RH Mongo-DB1.
  • Ensure to click the Reinitialize the MAC Address of complete 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 designation 7.2 RH Mongo-DB2.
  • Ensure to click the Reinitialize the MAC Address of complete 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 designation 7.2 RH Mongo-DB3.
  • Ensure to click the Reinitialize the MAC Address of complete network cards.
  • Click on Next.
  • Ensure the plenary Clone option is selected.
  • Click on Clone.
  • The final step for getting the systems ready will live to configure the hostnames, host-only ip and the host files. They will need 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 need to contact your IT departments on how they manage opening of ports.

    Normally in a production environment, you would gain the servers in an internal DNS system, however for the sake of this blog they will exhaust 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 live using will live as follows:

    To achieve so on each of the guests achieve 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 live 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 confiscate values from the table above.  # hostnamectl set-hostname "mongo-db1" --static
  • Edit the hosts file adding the following to etc/hosts, you should moreover achieve 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 live leveraged throughout the development, test, and production lifecycle, with critical functionality ranging from cluster performance monitoring data, alerting, no-downtime upgrades, advanced configuration and scaling, as well as backup and restore. Ops Manager can live used to manage up to thousands of several MongoDB clusters in a tenants-per-cluster fashion — isolating cluster users to specific clusters.

    All major MongoDB Ops Manager actions can live driven manually through the user interface or programmatically through the ease API, where Ops Manager can live 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 live deployed across a minimum of three hosts in three several availability areas — physical servers, racks, or data centers. The loss of one host will silent 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 rectify credentials are able to access the cluster. The MongoDB cluster can moreover exhaust SSL/TLS for over the wire encryption.

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

    To exhaust Ops Manager with Ansible and OpenShift:

  • Install and exhaust 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 reverse is not necessary; in other words, Ops Manager does not need to live 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). exhaust the Ops Manager UI (or ease 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 live light enough to login and hasten the commands as seen in the Ops Manager agent installation information. However they gain created an ansible playbook that you will need 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 groundwork 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 need to customize it with the information you gathered from the Ops Manager.

    You will need 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 hasten 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 hasten the playbook you need 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 confiscate access rights:

  • Verify that complete of the Ops Manager agents gain 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 evolution Kit (CDK), OpenShift as a local deployment, and OpenShift in production. In this final section, we’re going to assume a survey at how a team can assume odds of the advanced features of OpenShift in order to automatically ramble current versions of applications from evolution to production — a process known as Continuous Delivery (or Continuous Deployment, depending on the plane of automation).

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

    OpenShift integrates well with existing Continuous Integration / Continuous Delivery tools. Jenkins, for example, is available for exhaust inside the platform and can live 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 exhibit workflows can live 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 live using a evolution environment provisioned in a remote OpenShift cluster.

    To ramble code between environments, they can assume odds of the image streams concept in OpenShift. An image stream is superficially similar to an image repository such as those institute 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 contemplate this in the diagram above — when the developer is ready for their changes to live picked up by the next environment in line, they simply tag the image appropriately, which will generate an image stream notification that will live picked up by the staging environment. The staging environment will then automatically rebuild and redeploy any containers using this image (or images who gain the changed image as a groundwork layer). This can live fully automated by the exhaust of Jenkins or a similar CI tool; on a check-in to the source control repository, it can hasten a test-suite and automatically tag the image if it passes.

    To ramble between staging and production they can achieve exactly the same thing — Jenkins or a similar implement could hasten 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 live perquisite 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 silent a manual “ok” required before changes hit production. In OpenShift this can live easily done by requiring the images in staging to live tagged manually before they are deployed to production.

    Deployment of an OpenShift Application

    Now that we’ve reviewed the workflow, let’s survey at a true instance of pushing an application from evolution to production. They will exhaust 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 instance assumes that both environments are hosted on the same OpenShift cluster, but it can live easily adapted to allow promotion to another OpenShift instance by using a common registry.

    If you don’t already gain a working OpenShift instance, you can quickly derive 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 live their evolution environment (mlbparks):

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

    After you hasten this command you should live in the context of the evolution 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 gain multiple IP addresses assigned to your endpoint and the service will act as a load balancer. This will not labor 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 need to create one external service for each node. In their case they gain three nodes so for illustrative purposes they gain 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 need to hasten 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 gain the endpoints for the external replica set created they can now create the MLB parks using a template. They will exhaust 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 branch they use). complete 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" - exhaust the logs command to track its progress. hasten 'oc status' to view your app.

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

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

    We can derive the designation of the image created by the build with the serve of the narrate command:

    $ oc narrate 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 haul 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 exhaust 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 live tied to this particular version. If they hadn’t done this, production would automatically track changes to latest, which would embrace untested code.

    To allow the production project to haul the image from the evolution repository, they need to award haul rights to the service account associated with production environment. Note that mlbparks-production is the designation 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 derive 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 gain an image that can live 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 exhaust the same 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 allotment we’ll live using the image stream created in the evolution project that was tagged “production”:

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

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

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

    We will now demonstrate the ability to both automatically ramble current items to production, but they will moreover exhibit how they can update an application without having to update the MongoDB schema. They gain created a branch 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 evolution project:

    $ oc project mlbparks Now using project "mlbparks" on server "https://10.1.2.2:8443". And start a current build based on the commit “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 element to in their application to live persisted to the database, they would need to manufacture the changes in the code as well as gain a DBA manually update the schema at the database. The following code is an instance 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 job will start that will supplant the running container. Once the current version is deployed, you should live able to contemplate East under Toronto for example.

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

    OK, we’re joyful with the change, let’s tag it ready for production. Again, hasten oc to derive 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 live done in different ways. For this example, they will roll back the production environment by tagging production with the worn image ID. Find the perquisite 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 principal features for organizations, including source-to-image tooling, image streams, project and user isolation and a web UI. This post showed how these features labor together to provide a complete CD workflow where code can live automatically pushed from evolution through to production combined with the power and capabilities of MongoDB as the backend of election for applications.


    MySQL Stored Procedure Programming | killexams.com true questions and Pass4sure dumps

    Written by Guy Harrison and Steven Feuerstein, and published by O'Reilly Media in March 2006 under the ISBNs 0596100892 and 978-0596100896, this book is the first one to offer database programmers a plenary discussion of the syntax, usage, and optimization of MySQL stored procedures, stored functions, and triggers — which the authors wisely advert to collectively as "stored programs," to simplify the manuscript. Even a year after the introduction of these current capabilities in MySQL, they gain received remarkably limited coverage by book publishers. Admittedly, there are three such chapters in MySQL Administrator's guide and Language Reference (2nd Edition), written by some of the developers of MySQL, and published by MySQL Press. Yet this latter book — even though published a month after O'Reilly's — devotes fewer than 50 pages to stored programs, and the material is not in the printed book itself, but in the "MySQL Language Reference" part, on the accompanying CD. That material, in conjunction with the online reference documentation, may live enough for the more simple stored program evolution needs. But for any MySQL developer who wishes to understand in-depth how to manufacture the most of this current functionality in version 5.0, they will likely need a much more substantial treatment — and that's exactly what Harrison and Feuerstein gain created.

    The authors are generous in both the technical information and evolution advice that they offer. The book's material spans 636 pages, organized into 23 chapters, grouped into four parts, followed by an index. The first part, "Stored Programming Fundamentals," provides an introduction and then a tutorial, both taking a broad view of MySQL stored programs. The remaining four chapters cover language fundamentals; blocks, conditional statements, and iterative programming; SQL; and oversight handling. The book's second part, "Stored Program Construction," may live considered the heart of the book, because its five chapters present the details of creating stored programs in general, using transaction management, using MySQL's built-in functions, and creating one's own stored functions, as well as triggers. The third part, "Using MySQL Stored Programs and Applications," explains some of the advantages and disadvantages of stored programs, and then illustrates how to convoke those stored programs from source code written in any one of five different programming languages: PHP, Java, Perl, Python, and Microsoft.NET. In the fourth and final part, "Optimizing Stored Programs," the authors focus on the security and tuning of stored programs, tuning SQL, optimizing the code, and optimizing the evolution process itself.

    This is a substantial book, encompassing a august deal of technical as well as advisory information. Consequently, no review such as this can hope to narrate or critically observation upon every section of every chapter of every part. Yet the overall trait and utility of the manuscript can live discerned simply by choosing just one of the aforesaid Web programming languages, and writing some code in that language to convoke some MySQL stored procedures and functions, to derive results from a test database — and developing complete of this code while relying solely upon the book under review. Creating some simple stored procedures, and calling them from some PHP and Perl scripts, demonstrated to me that MySQL Stored Procedure Programming contains more than enough coverage of the topics to live an invaluable guide in developing the most common functionality that a programmer would need to implement.

    The book appears to gain very few aspects or specific sections in need of improvement. The discussion of variable scoping, in Chapter 4, is too cursory (no database pun intended). In terms of the book's sample code, I institute countless cases of inconsistency of formatting — specifically, operators such as "||" and "=" being jammed up against their adjacent elements, without any whitespace to better readability. These minor flaws could live easily remedied in the next edition. Some programming books manufacture similar mistakes, but throughout their text, which is even worse. Fortunately, most of the code in this book is neatly formatted, and the variable and program names are generally descriptive enough.

    Some of the book's material could gain been left out without august loss — thereby reducing the book's size, weight, and presumably price. The two chapters on basic and advanced SQL tuning contain techniques and recommendations covered with equal skill in other MySQL books, and were not needed in this one. On the other hand, slovenly developers who churn out lamentable code might argue that the terminal chapter, which focuses on best programming practices, could moreover live excised; but those are the very individuals who need those recommendations the most.

    Fortunately, the few weaknesses in the book are completely overwhelmed by its positive qualities, of which there are many. The coverage of the topics is quite extensive, but without the repetition often seen in many other technical books of this size. The explanations are written with clarity, and provide enough detail for any experienced database programmer to understand the general concepts, as well as the specific details. The sample code effectively illustrates the ideas presented in the narration. The font, layout, organization, and fold-flat binding of this book, complete manufacture it a joy to read — as is characteristic of many of O'Reilly's titles.

    Moreover, any programming book that manages to lighten the load of the reader by offering a handle of humor here and there, cannot live complete bad. Steven Feuerstein is the author of several well-regarded books on Oracle, and it was nice to contemplate him poke some fun at the database heavyweight, in his election of sample code to demonstrate the my_replace() function: my_replace( 'We savor the Oracle server', 'Oracle', 'MySQL').

    The prospective reader who would relish to learn more about this book, can consult its Web page on O'Reilly's site. There they will find both short and plenary descriptions, confirmed and unconfirmed errata, a link for writing a reader review, an online table of contents and index, and a sample chapter (number 6, "Error Handling"), in PDF format. In addition, the visitor can download complete of the sample code in the book (562 files) and the sample database, as a mysqldump file.

    Overall, MySQL Stored Procedure Programming is adeptly written, neatly organized, and exhaustive in its coverage of the topics. It is and likely will remain the premier printed resource for Web and database developers who want to learn how to create and optimize stored procedures, functions, and triggers within MySQL.

    Michael J. Ross is a Web programmer, freelance writer, and the editor of PristinePlanet.com's free newsletter. He can live reached at www.ross.ws, hosted by SiteGround.



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    SASInstitute [15 Certification Exam(s) ]
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    SDI [3 Certification Exam(s) ]
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    Symantec [134 Certification Exam(s) ]
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    Tibco [18 Certification Exam(s) ]
    Trainers [3 Certification Exam(s) ]
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    TruSecure [1 Certification Exam(s) ]
    USMLE [1 Certification Exam(s) ]
    VCE [6 Certification Exam(s) ]
    Veeam [2 Certification Exam(s) ]
    Veritas [33 Certification Exam(s) ]
    Vmware [58 Certification Exam(s) ]
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    XML-Master [3 Certification Exam(s) ]
    Zend [6 Certification Exam(s) ]





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