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IBM IBM DB2 10.1 Fundamentals

A e-book to the IBM DB2 9 Fundamentals certification examination | killexams.com existent Questions and Pass4sure dumps

here excerpt from DB2 9 Fundamentals: Certification examine guide, written by using Roger E. Sanders, is reprinted with authorization from MC Press. read the comprehensive Chapter 1, A e book to the IBM DB2 9 certification examination if you believe taking a DB2 9 Fundamentals certification exam might possibly exist your next profession stream.

The IBM DB2 9 certification process

an in depth examination of the IBM certification roles available promptly displays that, as a route to obtain a particular DB2 9 certification, you should assume and flux one or greater exams that abide been designed chiefly for that certification role. (each and every examination is a utility-primarily based exam that is neither platform -- nor product-particular.) for this reason, after you abide chosen the certification function you want to pursue and familiarized yourself with the necessities for that selected function, the next step is to set together for and assume the acceptable certification exams.

preparing for the IBM DB2 9 certification checks

when you abide event the consume of DB2 9 within the context of the certification role you abide got chosen, you may additionally already possess the handicap and competencies obligatory to pass the examination(s) required for that role. youngsters, in case your event with DB2 9 is limited (and in spite of the fact that it is not), that you may prepare for any of the certification exams available by taking expertise of here components:

  • Formal education
  • IBM gaining scholarship of capabilities offers classes that are designed to assist you set together for DB2 9 certification. a catalogue of the classes that are advised for each and every certification examination can besides exist discovered the consume of the Certification Navigator appliance offered on IBM's "expert Certification software from IBM " net web site. advised courses can besides exist discovered at IBM's "DB2 records management" internet site. For greater tips on direction schedules, locations, and pricing, contact IBM getting to know services or hunt counsel from their internet web page.

  • online tutorials
  • IBM presents a train of seven interactive online tutorials designed to prepare you for the DB2 9 Fundamentals exam (exam 730). IBM additionally presents a train 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 software evolution examination (examination 733).

  • Publications
  • the entire tips you requisite to pass any of the purchasable certification assessments can besides exist present in the documentation that is equipped with DB2 9. an entire set of manuals comes with the product and are accessible throughout the assistance core after you abide installed the DB2 9 utility. DB2 9 documentation can even exist downloaded from IBM's web site in both HTML and PDF codecs. @39202

    Self-analyze books (corresponding to this one) that hub of attention on one or more DB2 9 certification checks/roles are besides purchasable. every one of these books can besides exist discovered at your local bookstall or ordered from many on-line ebook retailers. (a catalogue of viable reference materials for every certification examination will besides exist discovered using the Certification Navigator device offered on IBM's "knowledgeable Certification application from IBM" web site.)

    apart from the DB2 9 product documentation, IBM often produces manuals, known as "RedBooks," that cowl superior DB2 9 topics (as well as different matter matters). These manuals can exist institute as downloadable PDF information on IBM's RedBook net site. Or, in case you favor to abide a bound complicated replica, which you can obtain one for a modest payment through following the applicable hyperlinks on the RedBook net web site. (There is not any can saturate for the downloadable PDF info.)

  • examination aims
  • pursuits that give an overview of the simple topics that are covered on a particular certification exam may besides exist discovered using the Certification Navigator device provided on IBM's "professional Certification application from IBM" web site. exam goals for the DB2 9 family unit Fundamentals exam (exam 730) can besides exist institute in Appendix A of this publication.

  • sample questions/exams
  • pattern questions and pattern checks permit you to rotate into universal with the format and wording used on the exact certification assessments. they could assist you gain to a decision whether you possess the skills obligatory to stride a selected examination. pattern questions, along with descriptive answers, are supplied at the conclusion of each chapter in this ebook and in Appendix B. pattern assessments for each DB2 9 certification position obtainable may besides exist institute the consume of the Certification exam appliance supplied on IBM's "knowledgeable Certification application from IBM" net site. there is a $10 saturate for every examination taken.

    it is Important to note that the certification exams are designed to exist rigorous. Very unavoidable solutions are anticipated for most examination questions. because of this, and since the scope of material covered on a certification examination is always broader than the expertise ground of many DB2 9 gurus, exist positive to assume capabilities of the examination guidance resources obtainable in case you want to guarantee your success in acquiring the certification(s) you want.

  • The ease of this chapter particulars everyone attainable DB2 9 certifications and contains lists of suggested objects to grasp before taking the examination. It besides describes the structure of the checks and what to anticipate on examination day. study the finished Chapter 1: A e book to the IBM DB2 9 certification exam to exist taught greater.


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    No result discovered, are trying modern key phrase!Fundamentals of IBM can exist reviewed in perquisite here matter matters under ... lately, on June 19, I trimmed Boeing (NYSE:BA) from 10.1% of the portfolio to 9.6%. it exist a much business, but you ought to exist di...

    Mainframe facts Is Your stealthy Sauce: A Recipe for records insurance policy | killexams.com existent Questions and Pass4sure dumps

    Mainframe records Is Your stealthy Sauce: A Recipe for information insurance policy July 31, 2017  |  by Kathryn Zeidenstein A chef drizzling sauce on a plate of food.

    Bigstock

    Share Mainframe information Is Your stealthy Sauce: A Recipe for statistics protection on Twitter share Mainframe statistics Is Your stealthy Sauce: A Recipe for data insurance policy on facebook share Mainframe data Is Your stealthy Sauce: A Recipe for statistics coverage on LinkedIn

    We within the security container want to consume metaphors to help illustrate the significance of statistics within the enterprise. I’m a much fan of cooking, so I’ll consume the metaphor of a stealthy sauce. suppose about it: each transaction basically reflects your corporation’s wonderful relationship with a consumer, service provider or companion. by means of sheer quantity alone, mainframe transactions provide an incredible number of materials that your corporation uses to create its stealthy sauce — improving consumer relationships, tuning give chain operations, soar modern lines of company and extra.

    extremely captious statistics flows through and into mainframe data retailers. in reality, ninety two of the exact 100 banks confidence on the mainframe because of its velocity, scale and safety. additionally, greater than 29 billion ATM transactions are processed per 12 months, and 87 % of everyone bank card transactions are processed throughout the mainframe.

    Safeguarding Your stealthy Sauce

    the buzz has been stalwart for the recent IBM z14 announcement, which contains pervasive encryption, tamper-responding key management and even encrypted utility program interfaces (APIs). The velocity and scale of the pervasive encryption solution is breathtaking.

    Encryption is a fundamental expertise to protect your stealthy sauce, and the brand modern effortless-to-use crypto capabilities within the z14 will create encryption a no brainer.

    With the entire exhilaration around pervasive encryption, although, it’s essential not to fail to notice another fragment that’s Important for facts security: statistics endeavor monitoring. imagine everyone of the purposes, functions and administrators as cooks in a kitchen. How can you create unavoidable that americans are correctly following the recipe? How enact you exist positive that they aren’t running off along with your stealthy sauce and developing competitive recipes or promoting it on the black market?

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

    facts coverage and exercise Monitoring

    data undertaking monitoring offers insights into entry deportment — that's, the who, what, where and when of access for DB2, the assistance management device (IMS) and the file equipment. as an example, through the consume of data recreation monitoring, you could exist able to inform even if the top chef (i.e., the database or device administrator) is working from a special zone or working irregular hours.

    in addition, statistics undertaking monitoring raises the visibility of unusual mistake circumstances. If an application starts throwing a few bizarre database error, it may exist an illustration that an SQL injection assault is underway. Or maybe the application is only poorly written or maintained — in everyone probability tables had been dropped or utility privileges abide changed. This visibility can champion organizations in the reduction of database overhead and risk via bringing these issues to gentle.

    Then there’s compliance, everyone and sundry’s favorite subject. You deserve to exist capable of reveal to auditors that compliance mandates are being adopted, even if that comprises monitoring privileged clients, now not enabling unauthorized database alterations or tracking everyone entry to cost card industry (PCI) information. With the eu’s universal facts insurance policy legislation (GDPR) set to assume sequel in may besides 2018, the stakes are even bigger.

    Automating abide faith, Compliance and protection

    As a fragment of a comprehensive information coverage system for the mainframe, IBM protection Guardium for z/OS gives certain, granular, precise-time recreation monitoring capabilities as well as real-time alerting, out-of-the-box compliance reporting and a all lot greater. The most recent liberate, 10.1.3, provides information insurance policy improvements as well as performance advancements to assist preserve your costs and overhead down.

    Your mainframe statistics is valuable — it's your stealthy sauce. As such, it will exist stored under lock and key, and monitored continuously.

    To learn more about monitoring and conserving information in mainframe environments, watch their on-demand webinar, “Your Mainframe atmosphere Is a Treasure Trove: Is Your elegant data covered?”

    Tags: Compliance | records coverage | Encryption | Mainframe | Mainframe security | price Card industry (PCI) Kathryn Zeidenstein

    expertise Evangelist and neighborhood recommend, IBM safety Guardium

    Kathryn Zeidenstein is a technology evangelist and community intimate for IBM protection Guardium statistics insurance policy... 13 Posts What’s new
  • PodcastExamining the state of Retail Cybersecurity forward of the 2018 crash Season
  • EventWebinar: The Resilient finish of 12 months evaluation — The appropriate Cyber safety traits in 2018 and Predictions for the yr ahead
  • ArticleA enjoyable and educational respond to the security attention problem: The security collect away Room
  • protection Intelligence Podcast Share this article: Share Mainframe information Is Your stealthy Sauce: A Recipe for information insurance policy on Twitter share Mainframe statistics Is Your stealthy Sauce: A Recipe for records coverage on facebook share Mainframe data Is Your stealthy Sauce: A Recipe for statistics protection on LinkedIn greater on data insurance plan A meeting  scope in a modern office: data discovery PodcastForrester Analyst Heidi Shey Dives deep Into information Discovery and Classification Illustration of a malicious advertisement on a laptop screen: malvertising ArticleHow to guard towards Malvertising force-through attacks A woman using a smartphone to  create an online purchase: security hygiene ArticleRetail safety Hygiene: The Case for Seasonal Checkups Man checking his phone for a second-factor authentication key: password management ArticleWe should contend NIST’s Dropped Password management strategies

    C2090-610 DB2 10.1 Fundamentals

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    C2090-610 exam Dumps Source : DB2 10.1 Fundamentals

    Test Code : C2090-610
    Test title : DB2 10.1 Fundamentals
    Vendor title : IBM
    : 138 existent Questions

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    Altova Introduces Version 2014 of Its Developer Tools and Server Software | killexams.com existent 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 include integration with the lightning hastily validation and processing capabilities of RaptorXML®, champion for Schema 1.1, XPath/XSLT/XQuery 3.0, champion for modern databases and much more. modern features in Altova server products include caching options in FlowForce® Server and increased performance powered by RaptorXML across the server product line.

    "We are so excited to exist able to extend the hyper-performance delivered by the unparalleled RaptorXML Server to developers working in their desktop tools. This functionality, along with robust champion 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 sunder handicap when structure and deploying applications."

    A few of the modern 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 workable 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 hastily 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 champion the very latest of everyone apposite 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 Important champion for XML Schema 1.1 validation and editing. The latest version of the XML Schema standard, 1.1 adds modern features aimed at making schemas more flexible and adaptable to trade 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 facile to understand and implement these modern features.

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

    Coinciding with XML Schema 1.1 support, Altova has besides 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 include the latest version of the XPath Recommendation. XPath 3.0 is a superset of the XPath 2.0 recommendation and adds powerful modern functionality such as: dynamic function cells, inline function expressions, and champion for union types to title just a few. Full champion for modern 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 still a working draft that continues to evolve. XSLT 3.0 champion conforms to the W3C XSLT 3.0 Working Draft of July 10, 2012 and the XPath 3.0 Candidate Recommendation. However, champion in XMLSpy now gives developers the ability to start working with this modern version immediately.

    XSLT 3.0 takes handicap of the modern features added in XPath 3.0. In addition, a major feature enabled by the modern version is the modern xsl:try / xsl:catch construct, which can exist used to trap and regain from dynamic errors. Other enhancements in XSLT 3.0 include champion for higher order functions and partial functions.

    Story Continues

    As with XSLT and XPath, XMLSpy champion for XQuery now besides includes a subset of version 3.0. Developers will now abide 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 modern functions and operators added in XPath 3.0, such as a modern string concatenation operator, map operator, math functions, sequence processing, and more -- everyone 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 include complete champion for newer versions of previously supported databases, as well as champion for modern 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 modern 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 trade processes, while MapForce Server and StyleVision Server proffer high-speed automation for projects designed using chummy 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 create its own Web service data requests. FlowForce Server administrators can now schedule execution of a time-consuming job and cache the results to obviate these delays. The cached data can then exist 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 exist a safe 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 modern features, supported standards, and affliction 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 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 exist the trademarks of their respective owners.


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

    Current evolution cycles countenance many challenges such as an evolving landscape of application architecture (Monolithic to Microservices), the requisite to frequently deploy features, and modern IaaS and PaaS environments. This causes many issues throughout the organization, from the evolution teams everyone the route to operations and management.

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

    MongoDB is the next-generation database that is built for rapid and iterative application development. Its flexible 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 help 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 besides exist 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 savor 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 result this example, you will requisite to meet a number of requirements. You will requisite 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 besides 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 besides 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 besides seeks to unravel other major unsolved IT challenges.

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

    In order to install Ansible using yum you will requisite 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 ground RHEL packages.

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

    Vagrant is not included in any touchstone repository, so they will requisite to install it. You can install Vagrant by enabling the SCLO repository or you can collect it directly from the Vagrant website. They will consume 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 consume VirtualBox for the virtualization software.

    VirtualBox is best done using a repository to ensure you can collect updates. To enact this you will requisite to result 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 correct 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 correct domain:

  • Open VirtualBox, this should exist 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 exist a vboxnet0 as the network, click on it and click on the edit icon (looks fancy 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 Run the same route on every platform. However, modern microservice deployments typically consume a scheduler such as Kubernetes to Run 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 facile to Run involved deployments resembling production. This means involved applications can exist developed using production grade tools from the very start, signification developers are unlikely to savor 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 finish of this blog post you will know how to Run an application on top of OpenShift and will exist chummy with the core features of the CDK and OpenShift. Let’s collect started…

    Installing the CDK

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

    Start by going to Red Hat Product Downloads (note that you will requisite a Red Hat subscription to access this). Select ‘Red Hat Container evolution Kit’ under Product Variant, and the appropriate 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 help 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 exist used to register the modern 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 title 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 consume the Vagrantfile that comes shipped with the CDK and has champion for OpenShift.

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

    In order to consume the landrush plugin to configure the DNS they requisite 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 requisite to exist 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 exist reachable only by IP address from within the VM.

    Save the changes and start the virtual machine :

    $ vagrant up

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

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

    Now that they abide 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 exist 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 exist openshift-dev/devel. You can besides consume your Red Hat credentials to login. In the console, they create a modern project:

    Next, they create a modern application using one of the built-in ‘Instant Apps’. Instant Apps are predefined application templates that pull specific images. These are an facile route to quickly collect 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 consume the source code from the OpenShift GitHub repository located here. If you want to result along with the webhook steps later, you’ll requisite 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 Important to us – GITHUB_WEBHOOK_SECRET and APPLICATION_DOMAIN:

  • GITHUB_WEBHOOK_SECRET: this territory allows us to create a stealthy to consume with the GitHub webhook for automatic builds. You don’t requisite to specify this, but you’ll requisite to recollect the value later if you do.
  • APPLICATION_DOMAIN: this territory will determine where they can access their application. This value must include 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 consume it later on.

    OpenShift will then pull the code from GitHub, find the appropriate Docker image in the Red Hat repository, and besides 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 examine fancy this:

    In order to consume the Landrush plugin, there is additional steps that are required to configure dnsmasq. To enact that you will requisite to enact 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 requisite 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 requisite a route of routing from the public internet to the Vagrant machine running on your host. An facile route to achieve this is to consume a third party forwarding service such as ultrahook or ngrok. They requisite 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 stealthy (if you specified one when setting up the OpenShift project). If your webhook is configured correctly you should notice something fancy this:

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

    Any facile route to enact this is to edit the views/index.html file, e.g: (Note that you can besides enact this through the GitHub web interface if you’re feeling lazy). commit and shove this change to the GitHub repo, and they can notice a modern build is triggered automatically within the web console. Once the build completes, if they again open their application they should notice the updated front page.

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

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

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

    Replication Controllers

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

    In this post, they abide shown how to consume the Red Hat CDK to achieve both of these goals within a short-time frame and now abide a Node.js and MongoDB application running in containers, deployed using the OpenShift PaaS. This is a much route to quickly collect 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 exist required to set up the replica set. They will not walk through everyone of the steps of setting up Red Hat as this is prerequisite knowledge.

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

    We will besides exist 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 modern 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 enact a yum update on the guest RHEL install.

    The final step will exist to generate modern ssh keys for the root user and transfer the keys to the guest machine. To enact that tickle enact the following steps:

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

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

    To enact so on each of the guests enact 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 exist 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 cease firewalld # systemctl disable firewalld
  • Edit the hostname using the appropriate values from the table above.  # hostnamectl set-hostname "mongo-db1" --static
  • Edit the hosts file adding the following to etc/hosts, you should besides enact 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 exist leveraged throughout the development, test, and production lifecycle, with captious functionality ranging from cluster performance monitoring data, alerting, no-downtime upgrades, advanced configuration and scaling, as well as backup and restore. Ops Manager can exist used to manage up to thousands of sunder MongoDB clusters in a tenants-per-cluster mode — isolating cluster users to specific clusters.

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

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

    To consume Ops Manager with Ansible and OpenShift:

  • Install and consume 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 requisite to exist able to gain into the managed VMs directly over the network).
  • Spawn servers (VMs) running Red Hat Enterprise Linux, able to gain 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). consume 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 exist facile enough to login and Run the commands as seen in the Ops Manager agent installation information. However they abide created an ansible playbook that you will requisite 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 ground 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 requisite to customize it with the information you gathered from the Ops Manager.

    You will requisite 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 Run 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 Run the playbook you requisite 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 appropriate access rights:

  • Verify that everyone of the Ops Manager agents abide 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 examine at how a team can assume handicap of the advanced features of OpenShift in order to automatically stride modern 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 Run a completely sunder cluster for each environment (e.g. dev, staging, production) and others may consume a lone cluster for several environments. If you Run a sunder OpenShift PaaS for each environment, they will each abide their own dedicated and isolated resources, which is costly but ensures isolation (a problem with the evolution cluster cannot strike production). However, multiple environments can safely Run on one OpenShift cluster through the platform’s champion for resource isolation, which allows nodes to exist dedicated to specific environments. This means you will abide one OpenShift cluster with common masters for everyone environments, but dedicated nodes assigned to specific environments. This allows for scenarios such as only allowing production projects to Run on the more powerful / expensive nodes.

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

    To stride code between environments, they can assume handicap 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 notice this in the diagram above — when the developer is ready for their changes to exist picked up by the next environment in line, they simply tag the image appropriately, which will generate an image stream notification that will exist picked up by the staging environment. The staging environment will then automatically rebuild and redeploy any containers using this image (or images who abide the changed image as a ground layer). This can exist fully automated by the consume of Jenkins or a similar CI tool; on a check-in to the source control repository, it can Run a test-suite and automatically tag the image if it passes.

    To stride between staging and production they can enact exactly the same thing — Jenkins or a similar appliance could Run 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 modern versions. This would exist proper 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 still a manual “ok” required before changes hit production. In OpenShift this can exist easily done by requiring the images in staging to exist tagged manually before they are deployed to production.

    Deployment of an OpenShift Application

    Now that we’ve reviewed the workflow, let’s examine at a existent case of pushing an application from evolution to production. They will consume 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 same OpenShift cluster, but it can exist easily adapted to allow promotion to another OpenShift instance by using a common registry.

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

    $ oc login -u openshift-dev

    Now we’ll create two modern 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 exist their evolution environment (mlbparks):

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

    After you Run this command you should exist 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 vacuous selector and an endpoint. In some cases you can abide 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 requisite to create one external service for each node. In their case they abide three nodes so for illustrative purposes they abide 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 requisite to Run 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 abide the endpoints for the external replica set created they can now create the MLB parks using a template. They will consume 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). everyone of the environment variables are in the mlbparks-template.json, so they will first create a template then create their modern app:

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

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

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

    We can collect the title of the image created by the build with the help of the characterize command:

    $ oc characterize 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 pull 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 consume 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 exist tied to this particular version. If they hadn’t done this, production would automatically track changes to latest, which would include untested code.

    To allow the production project to pull the image from the evolution repository, they requisite to award pull rights to the service account associated with production environment. Note that mlbparks-production is the title of the production project:

    $ oc policy add-role-to-group system:image-puller \ system:serviceaccounts:mlbparks-production \ --namespace=mlbparks To verify that the modern policy is in place, they can check the rolebindings: $ oc collect 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 abide an image that can exist 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 consume 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 fragment we’ll exist 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 exist deployed in deployment config "mlbparks" * Port 8080/tcp will exist load balanced by service "mlbparks" --> Creating resources with label app=mlbparks ... DeploymentConfig "mlbparks" created Service "mlbparks" created --> Success Run '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 stride modern items to production, but they will besides reveal how they can update an application without having to update the MongoDB schema. They abide 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 modern 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 modern ingredient to in their application to exist persisted to the database, they would requisite to create the changes in the code as well as abide 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 = modern BasicDBObject(); updateQuery.append("$set", modern BasicDBObject() .append("division", "East")); BasicDBObject searchQuery = modern BasicDBObject(); searchQuery.append("league", "American League"); parkListCollection.updateMulti(searchQuery, updateQuery);

    Once the build finishes running, a deployment chore will start that will replace the running container. Once the modern version is deployed, you should exist able to notice East under Toronto for example.

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

    OK, we’re gratified with the change, let’s tag it ready for production. Again, Run oc to collect 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 modern image to the production environment.

    Rolling back can exist done in different ways. For this example, they will roll back the production environment by tagging production with the ragged 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 Important 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 exist automatically pushed from evolution through to production combined with the power and capabilities of MongoDB as the backend of choice for applications.


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    XML-Master [3 Certification Exam(s) ]
    Zend [6 Certification Exam(s) ]





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