{"id":190616,"date":"2024-10-25T06:30:00","date_gmt":"2024-10-25T05:30:00","guid":{"rendered":"https:\/\/datascientest.com\/en\/?p=190616"},"modified":"2024-10-23T17:17:57","modified_gmt":"2024-10-23T16:17:57","slug":"azure-data-factory-devops-pipelines","status":"publish","type":"post","link":"https:\/\/datascientest.com\/en\/azure-data-factory-devops-pipelines","title":{"rendered":"Azure Data Factory &amp; DevOps Pipelines: CI\/CD Guide"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"190616\" class=\"elementor elementor-190616\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-a4c69fe e-flex e-con-boxed e-con\" data-id=\"a4c69fe\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-0787be3 elementor-widget elementor-widget-text-editor\" data-id=\"0787be3\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p><strong>Azure DevOps pipelines facilitate CI\/CD (Continuous Integration and Continuous Delivery) for Azure Data Factories. Explore how to transition updates from a development setting to testing and production environments!<\/strong><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0f3e49c elementor-widget elementor-widget-text-editor\" data-id=\"0f3e49c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\"><a href=\"https:\/\/datascientest.com\/en\/data-engineer-role-skills-salary\">Data Engineers<\/a> craft and establish pipelines within a Development setting before migrating them to a Testing environment. Post-testing, the pipelines are ready for Production deployment. The primary aim of this approach is to <\/span><b>identify bugs, data quality issues, or missing data<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">This distinct separation of environments ensures a <\/span><b>division of responsibilities<\/b><span style=\"font-weight: 400;\"> and minimizes the influence of alterations made through other epics. It mitigates risks and outages while enabling the confinement of security and permissions specific to each environment, thus averting human errors and protecting data integrity.<\/span><\/p><p><span style=\"font-weight: 400;\">This distinction emphasizes the necessity of having separate development, testing, and production environments. Implementing <\/span><b>CI\/CD (Continuous Integration and Continuous Delivery)<\/b><span style=\"font-weight: 400;\"> further aids by automating administrative tasks and reducing technical risks.<\/span><\/p><p><span style=\"font-weight: 400;\">Integrating automation in testing and deployment guarantees the consistency of actions every time. CI\/CD pipelines incorporated into the development workflow permit systematic and automated <\/span><b>testing and deployment of data pipelines<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">This article guides you on how to <\/span><b>set up an Azure DevOps repository<\/b><span style=\"font-weight: 400;\"> for your Data Factory and <\/span><b>utilize Azure DevOps pipelines<\/b><span style=\"font-weight: 400;\"> to propagate updates across different environments.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-20f5c2d e-flex e-con-boxed e-con\" data-id=\"20f5c2d\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-299fc92 elementor-widget elementor-widget-heading\" data-id=\"299fc92\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h3 class=\"elementor-heading-title elementor-size-default\">Why Implement CI\/CD for Azure Data Factory?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c7a5ce2 elementor-widget elementor-widget-text-editor\" data-id=\"c7a5ce2\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Per Microsoft&#8217;s definition, continuous integration is the automated and early-stage testing of every codebase change. Continuous delivery follows this testing phase in the continuous integration process and oversees the transition of updates to a <\/span><b>staging or production environment<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">Within <a href=\"https:\/\/datascientest.com\/en\/azure-data-factory-what-is-it-and-what-is-it-for\">Azure Data Factory<\/a>, continuous integration and delivery (CI\/CD) means the migration of Data Factory pipelines from one phase (development, test, production) to another.<\/span><\/p><p><span style=\"font-weight: 400;\">The objective is to rigorously test developments within Data Factory, employing <\/span><b>varied separate environments for simplified transitions between these stages<\/b><span style=\"font-weight: 400;\"> to create a reliable and maintainable Data Engineering platform.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-02db112 elementor-widget elementor-widget-image\" data-id=\"02db112\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"869\" height=\"529\" src=\"https:\/\/datascientest.com\/en\/files\/2024\/10\/pipeline-ci-cd-1.webp\" class=\"attachment-full size-full wp-image-190619\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2024\/10\/pipeline-ci-cd-1.webp 869w, https:\/\/datascientest.com\/en\/files\/2024\/10\/pipeline-ci-cd-1-300x183.webp 300w, https:\/\/datascientest.com\/en\/files\/2024\/10\/pipeline-ci-cd-1-768x468.webp 768w\" sizes=\"(max-width: 869px) 100vw, 869px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-02496f6 e-flex e-con-boxed e-con\" data-id=\"02496f6\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-0c6c1d3 elementor-widget elementor-widget-heading\" data-id=\"0c6c1d3\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">What Are the Prerequisites?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cf4450c elementor-widget elementor-widget-text-editor\" data-id=\"cf4450c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Several elements serve as prerequisites for this workflow. An <\/span><b>Azure cloud subscription<\/b><span style=\"font-weight: 400;\"> is vital, with provisions to create resource groups and resources under the &#8220;Owner&#8221; role designation.<\/span><\/p><p><span style=\"font-weight: 400;\">Without the corresponding role privileges, establishing a <\/span><b>service principal,<\/b><span style=\"font-weight: 400;\"> to secure <\/span><b>access to Data Factories<\/b><span style=\"font-weight: 400;\"> within the resource group, is impossible.<\/span><\/p><p><span style=\"font-weight: 400;\">Along with building the Azure Data Factory and configuring DevOps pipelines. For demonstration purposes, we\u2019ll prepare all necessary resources for <\/span><b>three environments<\/b><span style=\"font-weight: 400;\">: <\/span><b>DEV<\/b><span style=\"font-weight: 400;\">, <\/span><b>UAT<\/b><span style=\"font-weight: 400;\">, and <\/span><b>PROD<\/b><span style=\"font-weight: 400;\">.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-05cbeeb e-flex e-con-boxed e-con\" data-id=\"05cbeeb\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-db0da9c elementor-widget elementor-widget-heading\" data-id=\"db0da9c\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Configuring the Azure Environment<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-35dfd7e elementor-widget elementor-widget-text-editor\" data-id=\"35dfd7e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">We\u2019ll start by creating three resource groups and Data Factories using the Azure Portal. Each <\/span><b>resource group<\/b><span style=\"font-weight: 400;\"> name needs to be a unique identifier within the subscription, and these Data Factories should have distinctive identities within the Azure cloud.<\/span><\/p><p><span style=\"font-weight: 400;\">This tutorial adheres to this naming pattern: &#8220;<\/span><b>initials-project-environment-resource&#8221;<\/b><span style=\"font-weight: 400;\">. For further insight on naming conventions, Microsoft&#8217;s official documentation is available.<\/span><\/p><p><span style=\"font-weight: 400;\">Create three Resource Groups named: &lt;Initials&gt;-warehouse-dev-rg &lt;Initials&gt;-warehouse-uat-rg &lt;Initials&gt;-warehouse-prod-rg<\/span><\/p><p><span style=\"font-weight: 400;\">In the Azure portal, select &#8220;create a resource&#8221; at the top of the homepage. Use the search bar to find &#8220;Resource Group&#8221; and select it from the results.<\/span><\/p><p><span style=\"font-weight: 400;\">Navigate to the &#8220;Resource Group&#8221; page and click &#8220;Create.&#8221; Populate three fields on the &#8220;Create a resource group&#8221; page:<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Subscription<\/b><span style=\"font-weight: 400;\">: Choose your subscription from the menu<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Resource Group<\/b><span style=\"font-weight: 400;\">: &#8220;&lt;Initials&gt;-warehouse-dev-rg&#8221;<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Region<\/b><span style=\"font-weight: 400;\">: Select the geographically closest region<\/span><\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1871cf9 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"1871cf9\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-md\" href=\"https:\/\/datascientest.com\/en\/data-courses\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Discover our  courses<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5db2f3c elementor-widget elementor-widget-text-editor\" data-id=\"5db2f3c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Finalize by clicking &#8220;Create&#8221; at the bottom of the screen. Repeat this procedure to establish the <\/span><b>UAT and PROD Resource Groups<\/b><span style=\"font-weight: 400;\"> by changing only the group name on the creation pages. You\u2019ll now find these three Resource Groups in your Azure portal.<\/span><\/p><p><span style=\"font-weight: 400;\">Next, we\u2019ll set up <\/span><b>Data Factories for each Resource Group<\/b><span style=\"font-weight: 400;\">, following this structure: &lt;Initials&gt;-warehouse-dev-df &lt;Initials&gt;-warehouse-uat-df &lt;Initials&gt;-warehouse-prod-df<\/span><\/p><p><span style=\"font-weight: 400;\">Remember, Data Factory names must be unique across the Azure cloud. It might be necessary to add a random numeral at the end for differentiation.<\/span><\/p><p><span style=\"font-weight: 400;\">For the DEV Data Factory, select &#8220;Create a Resource&#8221; from the top of the Azure home page. Search for &#8220;Data Factory&#8221; and select it from the results.<\/span><\/p><p><span style=\"font-weight: 400;\">Click &#8220;Create&#8221; on the &#8220;Data Factory&#8221; page. Populate five fields:<\/span><\/p><ul><li><b>Subscription<\/b><span>: Choose your subscription from the drop-list<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Resource Group<\/b><span style=\"font-weight: 400;\">: Select &#8220;&lt;Initials&gt;-warehouse-dev-rg&#8221;<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Region<\/b><span style=\"font-weight: 400;\">: Pick the nearest Region<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Name<\/b><span style=\"font-weight: 400;\">: &#8220;&lt;Initials&gt;-warehouse-dev-df&#8221;<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Version<\/b><span style=\"font-weight: 400;\">: V2<\/span><\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e57686c elementor-widget elementor-widget-text-editor\" data-id=\"e57686c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Select <\/span><b>&#8220;Next: Git configuration&#8221;<\/b><span style=\"font-weight: 400;\"> at the bottom of the page. Opt for <\/span><b>&#8220;Configure Git later&#8221;<\/b><span style=\"font-weight: 400;\">, then click &#8220;Create&#8221; to finalize.<\/span><\/p><p><span style=\"font-weight: 400;\">The same creation process applies for the UAT and PROD Data Factories by updating the name and relevant Resource Group.<\/span><\/p><p><span style=\"font-weight: 400;\">Upon completion, each Resource Group will accommodate a Data Factory. The Data Factory environment should correspond with the Resource Group.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ab4fb6f elementor-widget elementor-widget-image\" data-id=\"ab4fb6f\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"675\" height=\"404\" src=\"https:\/\/datascientest.com\/en\/files\/2024\/10\/devops-environnement.webp\" class=\"attachment-full size-full wp-image-190620\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2024\/10\/devops-environnement.webp 675w, https:\/\/datascientest.com\/en\/files\/2024\/10\/devops-environnement-300x180.webp 300w\" sizes=\"(max-width: 675px) 100vw, 675px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-2783940 e-flex e-con-boxed e-con\" data-id=\"2783940\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-eb96054 elementor-widget elementor-widget-heading\" data-id=\"eb96054\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Establishing the DevOps Environment<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2a3bb28 elementor-widget elementor-widget-text-editor\" data-id=\"2a3bb28\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">The following step involves setting up a repository with the Azure Data Factory code and pipelines. Access the Azure DevOps website and click <\/span><b>&#8220;sign up for Azure DevOps&#8221;<\/b><span style=\"font-weight: 400;\"> below the <\/span><b>&#8220;Get started for free&#8221;<\/b><span style=\"font-weight: 400;\"> button.<\/span><\/p><p><span style=\"font-weight: 400;\">Log in using your Azure credentials. At the directory confirmation stage, refrain from hitting &#8220;Continue&#8221; just yet. The approach varies based on your account type.<\/span><\/p><p><span style=\"font-weight: 400;\">For a personal Azure and DevOps account, switch directories while logging in to <\/span><b>link Azure Services to DevOps<\/b><span style=\"font-weight: 400;\">. After signing in, select <\/span><b>&#8220;change directory&#8221;<\/b><span style=\"font-weight: 400;\"> beside the email and opt for &#8220;default directory,&#8221; then proceed by clicking &#8220;Continue.&#8221;<\/span><\/p><p><span style=\"font-weight: 400;\">If a corporate account is in use, it\u2019s already linked to a directory; thus, you can directly click &#8220;Continue.&#8221; On the &#8220;Create a project to start&#8221; screen, the system generates an organization name automatically in the top left corner.<\/span><\/p><p><span style=\"font-weight: 400;\">Before project creation, ensure the DevOps organization connects correctly to Azure Active Directory via the <\/span><b>&#8220;Organization settings&#8221;<\/b><span style=\"font-weight: 400;\"> found at the top left. In the sidebar, access <\/span><b>&#8220;Azure Active Directory&#8221;<\/b><span style=\"font-weight: 400;\"> to confirm the used account for Azure Services.<\/span><\/p><p><span style=\"font-weight: 400;\">You may now generate the project, naming it <\/span><b>&#8220;Azure Data Factory&#8221;<\/b><span style=\"font-weight: 400;\"> while keeping visibility private, selecting &#8220;Git&#8221; for version control and &#8220;Basic&#8221; for <\/span><b>&#8220;work item process&#8221;<\/b><span style=\"font-weight: 400;\">. Click &#8220;Create project.&#8221;<\/span><\/p><p><span style=\"font-weight: 400;\">Following this step, you\u2019ve formed a DevOps organization and a project harboring the Azure Data Factory code repository. Now, on the project home page, the next task is linking the <\/span><b>DEV Data Factory to the DevOps repository<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">Only the DEV Data Factory is added to the repository, serving as the DevOps release pipeline for code transitions to UAT and PROD.<\/span><\/p><p><span style=\"font-weight: 400;\">In the Azure portal, navigate to the DEV Resource Group and select <\/span><b>DEV Data Factory<\/b><span style=\"font-weight: 400;\">. Initiate &#8220;configure a code repository&#8221; from the homepage.<\/span><\/p><p><span style=\"font-weight: 400;\">On the &#8220;repository configuration&#8221; panel, complete these fields:<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Repository type<\/b><span style=\"font-weight: 400;\">: Azure DevOps Git<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Azure Active Directory<\/b><span style=\"font-weight: 400;\">: Choose your Azure Active Directory<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Azure DevOps Account<\/b><span style=\"font-weight: 400;\">: Select the organization created earlier<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Project Name<\/b><span style=\"font-weight: 400;\">: Azure Data Factory<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Repository Name<\/b><span style=\"font-weight: 400;\">: Opt for &#8220;use an existing repository,&#8221; choose &#8220;Azure Data Factory&#8221; from the menu<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Collaboration branch<\/b><span style=\"font-weight: 400;\">: master<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Publish branch<\/b><span style=\"font-weight: 400;\">: adf_publish<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Root folder<\/b><span style=\"font-weight: 400;\">: Retain default root &#8220;\/ &#8220;<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Import existing resource<\/b><span style=\"font-weight: 400;\">: Leave unchecked, as this Data Factory is fresh with no content.<\/span><\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-41a36f6 elementor-widget elementor-widget-text-editor\" data-id=\"41a36f6\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Confirm the setup and ascertain connectivity between your Data Factory and the repository. On the left sidebar, click &#8220;Author.&#8221; When selecting a working branch, choose &#8220;Use an existing branch&#8221; and &#8220;master,&#8221; then save.<\/span><\/p><p><span style=\"font-weight: 400;\">Under &#8220;Factory Resources,&#8221; click &#8220;+&#8221; and opt for &#8220;new pipeline.&#8221; Term it <\/span><b>&#8220;wait pipeline 1&#8221;<\/b><span style=\"font-weight: 400;\"> and insert a &#8220;Wait&#8221; activity onto the pipeline canvas. Hit &#8220;Save All&#8221; atop the screen followed by &#8220;Publish&#8221; and &#8220;OK.&#8221;<\/span><\/p><p><span style=\"font-weight: 400;\">Navigate to the Azure Data Factory project in DevOps and select &#8220;Repos.&#8221; You should see the pipeline created therein.<\/span><\/p><p><span style=\"font-weight: 400;\">The repository holds two branches. The master branch, originating with the repository, encapsulates all Data Factory elements, including datasets, <\/span><b>integration runtimes<\/b><span style=\"font-weight: 400;\">, <\/span><b>linked services<\/b><span style=\"font-weight: 400;\">, <\/span><b>pipelines<\/b><span style=\"font-weight: 400;\">, and <\/span><b>triggers<\/b><span style=\"font-weight: 400;\">, each tied to a .json file detailing its properties.<\/span><\/p><p><span style=\"font-weight: 400;\">The automatically generated <\/span><b>adf_publish branch<\/b><span style=\"font-weight: 400;\"> on publishing &#8220;wait pipeline 1&#8221; hosts two crucial files enabling the transition of the DEV Data Factory code to UAT and PROD.<\/span><\/p><p><span style=\"font-weight: 400;\">The <\/span><b>ARMTemplateForFactory.json file<\/b><span style=\"font-weight: 400;\"> documents all assets and properties within the Data Factory, while the ARMTemplateParametersForFactory.json file specifies all used parameters within the DEV Data Factory.<\/span><\/p><p><span style=\"font-weight: 400;\">Now, having established the resources and connections, you can proceed to create the pipeline. It facilitates releasing the adf_publish branch content to UAT and PROD.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6cb6a1e elementor-widget elementor-widget-image\" data-id=\"6cb6a1e\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"640\" height=\"365\" src=\"https:\/\/datascientest.com\/en\/files\/2024\/10\/coding-g15fbd119e_640.webp\" class=\"attachment-full size-full wp-image-190627\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2024\/10\/coding-g15fbd119e_640.webp 640w, https:\/\/datascientest.com\/en\/files\/2024\/10\/coding-g15fbd119e_640-300x171.webp 300w\" sizes=\"(max-width: 640px) 100vw, 640px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-0b0b03d e-flex e-con-boxed e-con\" data-id=\"0b0b03d\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-e7ad632 elementor-widget elementor-widget-heading\" data-id=\"e7ad632\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Creating an Azure DevOps Pipeline<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-be6a37c elementor-widget elementor-widget-text-editor\" data-id=\"be6a37c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">The pipeline\u2019s central function is capturing the <\/span><b>adf_publish branch<\/b><span style=\"font-weight: 400;\">. This branch maintains the latest DEV Data Factory version, subsequently deployable across UAT and PROD Data Factories.<\/span><\/p><p><span style=\"font-weight: 400;\">Every release mandates executing the <\/span><b>&#8220;pre and post-deployment&#8221;<\/b><span style=\"font-weight: 400;\"> PowerShell scripts. Without these scripts, any DEV Data Factory pipeline deletions won&#8217;t register during UAT and PROD deployments.<\/span><\/p><p><span style=\"font-weight: 400;\">Access this script in the Azure Data Factory documentation\u2019s footer. Save it as a PowerShell file using your preferred code editor.<\/span><\/p><p><span style=\"font-weight: 400;\">In Azure DevOps, click <\/span><b>&#8220;Repos&#8221;<\/b><span style=\"font-weight: 400;\"> in the left panel. In the adf_publish branch, hover over the DEV Data Factory folder, click <\/span><b>&#8220;ellipses&#8221;<\/b><span style=\"font-weight: 400;\">, then &#8220;Download files,&#8221; and ascertain the desired file location for download. Validate the process. You should now find a <\/span><b>&#8220;.ps1&#8221;<\/b><span style=\"font-weight: 400;\"> file extension in the adf_publish branch.<\/span><\/p><p><span style=\"font-weight: 400;\">Next, build the <\/span><b>CI\/CD Azure Pipeline<\/b><span style=\"font-weight: 400;\">. On the DevOps page\u2019s left side, go to &#8220;Pipelines&#8221; and select <\/span><b>&#8220;Create Pipeline&#8221;<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">The following page offers an option to &#8220;Use the classic editor,&#8221; providing a visual overview of the ongoing process steps. Once finalized, you can examine the YAML code produced.<\/span><\/p><p><span style=\"font-weight: 400;\">This pipeline ties to the adf_publish branch, wherein the <\/span><b>ARMTemplateForFactory and ARMTemplateParametersForFactory .json files<\/b><span style=\"font-weight: 400;\"> are housed.<\/span><\/p><p><span style=\"font-weight: 400;\">At the source selection interface, pick Azure Data Factory as the team project and repository, with adf_publish as the default branch, then &#8220;Continue.&#8221;<\/span><\/p><p><span style=\"font-weight: 400;\">We will now transfer the DEV Data Factory folder contents under the adf_publish branch located in &#8220;Repos&#8221; &gt; &#8220;Files.&#8221; Adjacent to &#8220;Agent job 1,&#8221; click the &#8220;+&#8221; symbol. Search &#8220;Publish artifacts&#8221; and add it to the task list.<\/span><\/p><p><span style=\"font-weight: 400;\">Under &#8220;Agent job 1,&#8221; selecting &#8220;Publish Artifact: drop&#8221; provides extra options on the page\u2019s right side. Modify the &#8220;Publish path&#8221;: click the ellipsis and select &#8220;&lt;Initials&gt;-warehouse-dev-df&#8221; from the folder menu. Press &#8220;OK.&#8221;<\/span><\/p><p><span style=\"font-weight: 400;\">Above the pipeline, choose &#8220;Triggers&#8221; and ensure &#8220;Enable continuous integration&#8221; is checked, with &#8220;Branch specification&#8221; set to &#8220;adf_publish.&#8221;<\/span><\/p><p><span style=\"font-weight: 400;\">Enabling this setting for the pipeline facilitates automated capturing and applying the latest <\/span><b>DEV Data Factory<\/b><span style=\"font-weight: 400;\"> state upon user publishing of new components. Hit &#8220;Save and Queue,&#8221; then &#8220;Save and run.&#8221;<\/span><\/p><p><span style=\"font-weight: 400;\">Upon choosing <\/span><b>&#8220;Agent job 1&#8221;<\/b><span style=\"font-weight: 400;\">, you gain insight into the underlying processes. Once the job concludes successfully, go to &#8220;Pipelines&#8221; on the left. You\u2019ll spot the newly made pipeline, along with its status and recent modifications.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-fbf53da elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"fbf53da\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-md\" href=\"https:\/\/datascientest.com\/en\/data-courses\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">More about our  courses<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-c39396d e-flex e-con-boxed e-con\" data-id=\"c39396d\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-9821c67 elementor-widget elementor-widget-heading\" data-id=\"9821c67\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Establishing a DevOps Release Pipeline for CI\/CD<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1b3fbe0 elementor-widget elementor-widget-text-editor\" data-id=\"1b3fbe0\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">The release pipeline leverages the preceding pipeline&#8217;s output for UAT and PROD Data Factory transfers.<\/span><\/p><p><span style=\"font-weight: 400;\">On the DevOps site, under &#8220;Pipelines&#8221; click &#8220;Releases,&#8221; then select <\/span><b>&#8220;New Pipeline&#8221;<\/b><span style=\"font-weight: 400;\"> and rename the stage to <\/span><b>&#8220;UAT&#8221;<\/b><span style=\"font-weight: 400;\">. Hit <\/span><b>&#8220;Save&#8221;<\/b><span style=\"font-weight: 400;\"> in the upper-right, and confirm.<\/span><\/p><p><span style=\"font-weight: 400;\">Upon UAT stage creation, include the artifact: the previously made pipeline ensconcing transferable configurations between stages.<\/span><\/p><p><span style=\"font-weight: 400;\">Within the release pipeline, click &#8220;Add an artifact.&#8221; In the <\/span><b>&#8220;Add an artifact&#8221;<\/b><span style=\"font-weight: 400;\"> panel, simply click &#8220;Add.&#8221;<\/span><\/p><p><span style=\"font-weight: 400;\">Proceed by adding tasks to the UAT stage within the &#8220;new release pipeline.&#8221; At the pinnacle of the pipeline, switch to <\/span><b>&#8220;Variables&#8221;<\/b><span style=\"font-weight: 400;\">. Set <\/span><b>variables ResourceGroup, DataFactory, and Location<\/b><span style=\"font-weight: 400;\"> for automatic task parameterization during transitions.<\/span><\/p><p><span style=\"font-weight: 400;\">Click &#8220;Add&#8221; to create the three pipeline variables, ensuring the location matches that of the Resource Groups and Data Factories.<\/span><\/p><p><span style=\"font-weight: 400;\">Save changes and enter pipeline view. Click &#8220;1 job, 0 task&#8221; on the UAT box, then the &#8220;+&#8221; button next to &#8220;Agent job.&#8221; Search &#8220;Azure PowerShell&#8221; and add it from the list, titled <\/span><b>&#8220;Azure PowerShell script: pre-deployment&#8221;<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">Select your Azure Subscription and create a Service Principal within the UAT Resource Group, later adding it to the <\/span><b>PROD Resource Group<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">Carefully select your Azure subscription from the list during &#8220;Service Principal Authentication.&#8221; Avoid directly selecting &#8220;Authorize,&#8221; choosing &#8220;advanced options&#8221; instead.<\/span><\/p><p><span style=\"font-weight: 400;\">Ensure &#8220;UAT Resource Group&#8221; is picked for the &#8220;Resource Group&#8221; in the pop-up, and hit &#8220;OK.&#8221;<\/span><\/p><p><span style=\"font-weight: 400;\">Leave &#8220;Script file path&#8221; unchanged while selecting &#8220;Script Type.&#8221; Click the ellipsis next to &#8220;Script Path&#8221; to pick the saved PowerShell script. Confirm by clicking &#8220;OK.&#8221;<\/span><\/p><p><span style=\"font-weight: 400;\">We will employ the &#8220;Script Arguments&#8221; presented in Azure Data Factory documentation. For pre-deployment, the arguments are <\/span><b>&#8220;-armTemplate \\&#8221; $(System.DefaultWorkingDirectory)\/&lt;your-arm-template-location&gt;\\&#8221; -ResourceGroupName &lt;your-resource-group-name&gt; -DataFactoryName &lt;your-data-factory-name&gt; -predeployment $true -deleteDeployment $false&#8221;<\/b><span style=\"font-weight: 400;\">. Ensure correct location within artifact drop, pick UAT Resource Group for the environment, set Data Factory name as UAT\u2019s, selecting <\/span><b>&#8220;Latest installed version&#8221;<\/b><span style=\"font-weight: 400;\"> for Azure PowerShell version. Save.<\/span><\/p><p><span style=\"font-weight: 400;\">Include another task; click &#8220;+,&#8221; search &#8220;ARM Template,&#8221; and add &#8220;ARM Template Deployment.&#8221; Modify to &#8220;ARM Template Deployment: Data Factory,&#8221; linking it to the previous Service Principal.<\/span><\/p><p><span style=\"font-weight: 400;\">Complete remaining fields:<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Subscription<\/b><span style=\"font-weight: 400;\">: Select your subscription<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Action<\/b><span style=\"font-weight: 400;\">: create or update a Resource Group<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Resource Group<\/b><span style=\"font-weight: 400;\">: Employ the Resource Group variable formatted previously<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Location<\/b><span style=\"font-weight: 400;\">: Use the Location variable<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Template location<\/b><span style=\"font-weight: 400;\">: Referenced Artifact<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Template Parameters<\/b><span style=\"font-weight: 400;\">: Utilize the ARMTemplateForFactory.json file<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Template parameter overrides<\/b><span style=\"font-weight: 400;\">: Replace &#8220;factory name&#8221; with the Data Factory variable<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Deployment mode<\/b><span style=\"font-weight: 400;\">: Incremental<\/span><\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-11366a0 elementor-widget elementor-widget-image\" data-id=\"11366a0\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"666\" height=\"372\" src=\"https:\/\/datascientest.com\/en\/files\/2024\/10\/Capture-decran-2022-12-26-184056.webp\" class=\"attachment-full size-full wp-image-190634\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2024\/10\/Capture-decran-2022-12-26-184056.webp 666w, https:\/\/datascientest.com\/en\/files\/2024\/10\/Capture-decran-2022-12-26-184056-300x168.webp 300w\" sizes=\"(max-width: 666px) 100vw, 666px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e9c920f elementor-widget elementor-widget-text-editor\" data-id=\"e9c920f\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Then add an Azure PowerShell task named &#8220;Azure PowerShell Script: Post-Deployment.&#8221; Compared to the pre-deployment arguments, only replace<\/span><b> &#8220;-predeployment $true&#8221; with &#8220;-predeployment $false&#8221; and &#8220;-deleteDeployment $false&#8221; with &#8220;-deleteDeployment $true.&#8221;<\/b><span style=\"font-weight: 400;\">\u00a0\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Now, grant the Service Principal access to the PROD Resource Group before starting to create the PROD stage of the release pipeline. Go to the Azure portal, navigate to the UAT Resource Group, and select<\/span><b> &#8220;Access Control (IAM).&#8221;<\/b><span style=\"font-weight: 400;\"> Under the &#8220;Contributor&#8221; role, copy the name of the DevOps organization and the project name.\u00a0\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Navigate to the PROD Resource Group and go to &#8220;Access Control (IAM).&#8221; In the access view tab, click the &#8220;+ Add&#8221; button and select <\/span><b>&#8220;Add role assignment.&#8221;<\/b><span style=\"font-weight: 400;\"> Choose the Contributor role from the dropdown menu and leave &#8220;Assign access to&#8221; as &#8220;User, group, or service principal.&#8221; Paste the previously copied name into the search bar and select the service principal. Save.\u00a0\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Now we can complete the PROD stage of the release pipeline. Go back to the<\/span><b> &#8220;New release pipeline&#8221;<\/b><span style=\"font-weight: 400;\"> and hover over the UAT stage. Click on <\/span><b>&#8220;Clone.&#8221;<\/b><span style=\"font-weight: 400;\">\u00a0\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Rename &#8220;Copy of UAT&#8221; to &#8220;PROD.&#8221; The ResourceGroup and DataFactory variables are duplicated, but under the Prod scope. Change their values by replacing &#8220;UAT&#8221; with &#8220;PROD.&#8221; Save.\u00a0\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">While the <\/span><b>Azure Data Factory-CI<\/b><span style=\"font-weight: 400;\"> pipeline is configured to run with every change in adf_publish, now the Release Pipeline needs to be adjusted so that a new release occurs with every change in adf_publish. The change must then automatically apply to the UAT Data Factory. For the PROD Data Factory, a pre-deployment approval is required before applying the DEV and UAT changes.\u00a0\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">In the &#8220;new release pipeline,&#8221; click the <\/span><b>&#8220;continuous deployment trigger&#8221; <\/b><span style=\"font-weight: 400;\">button to enable it. To adjust the UAT stage conditions for automatic execution, click the <\/span><b>&#8220;pre-deployment conditions&#8221; <\/b><span style=\"font-weight: 400;\">button on the UAT stage. Make sure to select the &#8220;after release&#8221; option.\u00a0\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Click on the &#8220;pre-deployment conditions&#8221; for the PROD stage and configure the trigger to &#8220;after stage&#8221; with the stage set to UAT. Also enable <\/span><b>&#8220;pre-deployment approvals&#8221;<\/b><span style=\"font-weight: 400;\"> and enter your email. Save.\u00a0\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">To test the release pipeline, manually initiate the Azure Data Factory-CI pipeline to activate it. Go to Pipelines and select Azure Data Factory &#8211; CI. Click on &#8220;run pipeline&#8221; at the top, then click &#8220;run&#8221; again. Go to &#8220;Releases,&#8221; and you should now see the first release. You will also see that the UAT stage of the Release Pipeline is running.\u00a0\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Once the UAT stage is successfully completed, the PROD stage is ready for approval. Go to your UAT Data Factory and verify if the &#8220;Wait Pipeline 1&#8221; is present.\u00a0\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Go to your &#8220;New release pipeline&#8221; and click on the PROD stage. Approve. You can see the progress of the PROD stage and the presence of the &#8220;Wait Pipeline 1.&#8221;\u00a0\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Finally, you can make changes in the DEV Data Factory to observe the entire process from start to finish. Go to the DEV Data Factory, create a pipeline called <\/span><b>&#8220;Wait Pipeline 2,&#8221;<\/b><span style=\"font-weight: 400;\"> and insert a &#8220;Wait 2&#8221; activity. Delete the &#8220;Wait Pipeline 1.&#8221;\u00a0\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Click on &#8220;save all&#8221; and &#8220;publish&#8221; all changes. In &#8220;Pipelines&#8221; on Azure DevOps, you can see that the Azure Data Factory-CI pipeline has already been triggered since adf_publish has changed. Similarly, in &#8220;Releases,&#8221; &#8220;Release-2&#8221; has been created, and the UAT stage is being deployed.\u00a0\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">The Data Factory PROD is currently on<\/span><b> &#8220;Release-1.&#8221;<\/b><span style=\"font-weight: 400;\"> Approve the PROD stage. It is evident that the changes made in the Data Factory DEV are also applied to the UAT and PROD Data Factories!\u00a0\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">This confirms that all resources are correctly connected and that the pipelines are functioning properly. Any future deployments in the DEV Data Factory can be replicated across UAT and PROD.\u00a0\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Thus, you will avoid minor differences between environments and save time troubleshooting issues. Feel free<\/span><b> to review the generated YAML<\/b><span style=\"font-weight: 400;\"> code throughout the steps of this guide to understand its structure and content.\u00a0\u00a0<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-230555e e-flex e-con-boxed e-con\" data-id=\"230555e\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-7d04477 elementor-widget elementor-widget-heading\" data-id=\"7d04477\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">How to master Azure DevOps?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-eba7336 elementor-widget elementor-widget-text-editor\" data-id=\"eba7336\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Azure DevOps is widely <\/span><b>used by DevOps teams<\/b><span style=\"font-weight: 400;\">. To learn to master this cloud service and its various elements like Data Factories, <\/span><b>you can choose DataScientest<\/b><span style=\"font-weight: 400;\">.\u00a0\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Our distance learning courses teach you how to master the best cloud and DevOps tools, as well as the best practices and working methods. By the end of the program, you will have <\/span><b>all the skills of a DevOps engineer<\/b><span style=\"font-weight: 400;\">.\u00a0\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Similarly, our <a href=\"https:\/\/datascientest.com\/en\/data-engineer-course\">Data Engineer training<\/a> covers all aspects of data engineering. You will learn <a href=\"https:\/\/datascientest.com\/en\/python-programming-for-dummies-episode-1\">programming in Python<\/a>, <a href=\"https:\/\/datascientest.com\/en\/all-about-ci-cd\">CI\/CD<\/a>, <a href=\"https:\/\/datascientest.com\/en\/database-types-how-to-make-the-right-choice\">databases<\/a>, <a href=\"https:\/\/datascientest.com\/en\/big-data-methods-unleashing-the-power-of-data-at-scale\">Big Data<\/a>, as well as <\/span><b>automation and deployment techniques<\/b><span style=\"font-weight: 400;\">.\u00a0\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">All our programs are <\/span><b>available as Continuing Education or in BootCamp mode<\/b><span style=\"font-weight: 400;\"> and offer hands-on learning through a capstone project. You can also obtain <\/span><b>top cloud and DevOps certifications<\/b><span style=\"font-weight: 400;\">.\u00a0\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Our organization, the leading French-speaking provider of Data Science training, is recognized by the State and eligible for Personal Training Account funding. Don\u2019t wait any longer and <\/span><b>discover DataScientest! <\/b><span style=\"font-weight: 400;\">\u00a0<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-be99433 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"be99433\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-md\" href=\"https:\/\/datascientest.com\/en\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Discover DataScientest training courses<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-61af6bb elementor-widget elementor-widget-text-editor\" data-id=\"61af6bb\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">You now know everything about Azure DevOps Pipelines and Data Factory. For more information on the same topic, check out <a href=\"https:\/\/datascientest.com\/en\/devops-principle-benefits-training\"><span style=\"font-weight: 400;\">our comprehensive DevOps guide<\/span><\/a> and <a href=\"https:\/\/datascientest.com\/en\/microsoft-azure-empower-yourself-with-knowledge\">our guide on Microsoft Azure cloud<\/a>.\u00a0\u00a0<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-eb6eb76 e-flex e-con-boxed e-con\" data-id=\"eb6eb76\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-7d2275a elementor-widget elementor-widget-html\" data-id=\"7d2275a\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<script type=\"application\/ld+json\">\r\n{\r\n  \"@context\": \"https:\/\/schema.org\",\r\n  \"@type\": \"FAQPage\",\r\n  \"mainEntity\": [{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"Why use CI\/CD for Azure Data Factory?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"According to Microsoft's definition, continuous integration is the practice of automatically testing every change made to the codebase as early as possible. 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The primary [&hellip;]<\/p>\n","protected":false},"author":45,"featured_media":190618,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2412],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.7 (Yoast SEO v21.7) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Azure Data Factory &amp; DevOps Pipelines: CI\/CD Guide<\/title>\n<meta name=\"description\" content=\"Azure DevOps pipelines enable CI\/CD (Continuous Integration\/Continuous Deployment) on Azure Data Factories. 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