139 docs tagged with "release"

In Release, the phases in a template or release represent blocks of work that happen in succession.

You can now add Stage Owners to Deliveries.

This topic provides information about tasks in Release, which are the core components of activities within a template or release, logically grouped into phases.

Learn how to manage application images in air-gapped environments. Following are the five different options you can use to ensure your application images are available in air-gapped environments.

Steps to perform an automatic in-place PostgreSQL major version upgrade with the CloudNativePG operator, and when to fall back to the manual upgrade process.

This topic provides information about how to automatically handle failures in Release tasks.

This document provides procedures for backing up the Digital.ai Release installation on a Kubernetes (K8s) cluster. Follow these steps to ensure your data and configuration are protected before performing upgrades or maintenance.

This topic provides an overview of the Calendar view in Digital.ai Release, including how to navigate different calendar views, filter releases, mark special days, and export the calendar.

This topic explains how to change the type of a task in Release, including the necessary permissions for modifying tasks in templates, planned releases, and active releases.

Step-by-step guides for cloud-native deployment scenarios with Digital.ai Release, including AWS EKS, Argo CD, and deployment strategies.

This topic explains how Digital.ai Release can define a release from a Groovy-based DSL script, that describes all the phases, tasks, and task-groups in the release. This enables you to store release definitions as code in version control and gives you programmatic control over a release when creating it.

This topic illustrates how to configure the settings required to install Release with HTTP2 backend enabled on a Kubernetes cluster.

This topic illustrates how to configure SSL/TLS with Digital.ai Release. A self-signed certificate is used for illustrative purposes in this procedure. However, you may want to replace it with your own trusted certificate for production environments, which you can do by creating a new Secret object in Kubernetes that contains your certificate and then configuring the ingress controller to use it.

This guide explains how to configure the DNS Time-to-Live (TTL) settings for the Release Java Virtual Machine (JVM) in a Kubernetes environment. Proper TTL configuration is crucial for managing how long DNS resolutions are cached, which can affect system performance and network behavior.

The Digital.ai Release Confluence plugin integrates your Confluence workspace with Release, making it easy to manage documentation as part of your release pipeline. It enables you to automate page creation, updates, and related actions so your Confluence content stays aligned with your delivery workflow.

Digital.ai Release is a release orchestration platform. It lets teams plan, track, and execute releases from a single location, giving every stakeholder — developers, QA engineers, release managers, and operations teams — a consistent view of release status.

Configure a Git trigger and an External Script task so that a release starts automatically whenever changes are pushed to a Git repository.

Release triggers are an automated way to create and run a release. When you create a trigger for a release template and enable it, Release will execute the script associated with the trigger at a specified interval. When the trigger starts, it will create and start a new release from the template. A good example of a trigger is one that polls a source code management system like GitHub for a change and starts a release as a result.

A Create Delivery task is an automatic task that creates a new delivery from a delivery pattern.

In Digital.ai Release, release variables are scope-specific configuration elements that help manage dynamic values within release templates and instances. Unlike global variables, release variables are confined to the template or release where they are created.

This guide explains how custom resource keys are migrated during the Digital.ai Release operator upgrade process. Understanding this process is crucial for maintaining your configuration when upgrading to newer versions of the operator.

Introduction

This topic explains how to use dashboard templates in Digital.ai Release to quickly build a dashboard that provides information on your deployments and releases.

Delivery Patterns in Release allow you to create pipelines where each team can work at its own timelines and tools, and converge at synchronized points.

Overview of delivery tasks in Digital.ai Release for creating, finding, and managing deliveries and tracked items.

When running Digital.ai Release with HTTPS enabled in Kubernetes, you may need to disable the Server Name Indication (SNI) check in certain scenarios. This guide explains how to safely disable the SNI check using Kubernetes commands.

Add the following entries to the xl-release.conf file to enable caching in Release.

This topic explains how to enable file logging in the Kubernetes cluster for Release application.

A Find Delivery task is an automatic task that searches for an existing delivery by tracked item or by name.

A Find Or Create Delivery task is an automatic task that searches for an existing delivery or creates a new one from a delivery pattern.

Teams are used to group one or more users in Release. Folder, template, or release-level permissions can be assigned to one or more teams.

Definitions of the key terms you will encounter when working with Digital.ai Release.

This guide explains how to manage file system operations in Digital.ai Release when using Operator-based installation. By default, containers run with read-only file systems for enhanced security. Learn how to configure various storage options including temporary storage, persistent volumes, and custom mounts to meet your application's needs while maintaining security best practices.

To use the Release REST API, you need to know the unique identifiers for templates, releases, phases and tasks. This topic explains where you can find them.

This topic explains how to use templates to model the ideal process of a release flow.

You can install Release in an air-gapped environment disconnected from the public internet. This topic provides information about installing and upgrading Release in such environments using a Minikube cluster and a custom image registry. For other Kubernetes platforms, steps are similar to the ones listed here for Minikube as long as the custom image registry contains all the required images.

Here is a basic setup for the AWS EKS cluster, use it as a guideline to create K8s cluster to have minimal K8s environment for Digital.ai Release installation.

Here is a basic setup for the Azure K8S cluster, use it as a guideline to create K8s cluster to have minimal K8s environment for Digital.ai Release installation.

Here is a basic setup for the GKE cluster, use it as a guideline to create K8s cluster to have minimal K8s environment for Digital.ai Release installation.

Here is a basic setup for the AWS Openshift cluster, use it as a guideline to create K8s cluster to have minimal K8s environment for Digital.ai Release installation.

Use these instructions to install Digital.ai Release on a minikube multi-node cluster for testing or illustration purposes. Do not use these instructions to set up a production environment.

* Here's a list of questions that you would have to answer to install Digital.ai Release Runner using the xl kube install command.

Reference for the questions and options presented during Digital.ai Release installation with xl kube install.

How to install Digital.ai Release on Red Hat OpenShift using the OpenShift Certified Operator.

The Delivery Patterns feature in Release allows you to use deliveries and tracked items to synchronize multiple releases together. This allows you to design delivery patterns that conform to the release standards being used by your organization, such as SAFe.

This guide explains how to manage Digital.ai Release plugins in offline mode when working with a Release cluster created using the Operator-based installer. You'll learn multiple approaches to manage plugins when the Release UI is unavailable or not functioning properly.

This tutorial is intended to help you get started with DevOps as Code in Release. It describes how to generate a DevOps as Code YAML file from an existing Release template and manage it in source control.

The Releases page provides a centralized view for managing and tracking releases.

This document explains what folders are in Digital.ai Release, how to organize them, manage permissions, configure notifications, and set up GitOps-based version control. You'll learn how to structure folders to match your organization and use them effectively to manage templates, releases, and configurations across teams.

Delivery stage transitions force all the tracked items in a stage to wait together until the transition conditions are met, or the transition is manually completed. This allows you to synchronize the releases together based on criteria such as business approval, scheduling, or the status of tracked items.

This topic describes how to create, run, and manage workflows.

This topic describes how to create and manage delivery patterns. A delivery pattern allows you to design a flow of stages that the tracked items in a delivery must go through. You can reuse these patterns in multiple deliveries.

This guide covers the manual steps required to upgrade PostgreSQL across a major version when using the CloudNativePG (CNPG) operator-based PostgreSQL installation, specifically when PostgreSQL is managed through the experimental postgresql-operator and postgresql-cluster rather than through the Release CR's built-in spec.postgresql keys. Use this manual process only if the automatic upgrade fails or your cluster doesn't meet its prerequisites.

PostgreSQL cannot be automatically upgraded during an operator-to-operator or Helm-to-operator upgrade due to incompatible data formats between different PostgreSQL server versions. In such cases, a manual upgrade is necessary. The process involves first backing up the PostgreSQL data, then upgrading to the new PostgreSQL version, and finally restoring the data in the upgraded version.

Learn how to capture task output properties in Digital.ai Release, map them to variables, and reuse those variables in subsequent tasks for efficient pipeline management.

A Mark Tracked Items task is an automatic task that completes or skips one or more tracked items on a running delivery.

This guide covers the manual steps required to migrate from the Bitnami chart-managed PostgreSQL installation (the default up to and including operator 25.1 releases) to the CloudNativePG (CNPG) operator-managed equivalent introduced in operator 25.3 releases.

This topic illustrates how to set up the persistent volumes on the Release containers.

Learn how to organize your Digital.ai Release environment with folders, GitOps versioning, users, roles, and connections.

The release dashboard tiles topic provides you with an overview of your planning information with the help of graphical representations. The release dashboard can be customized as per your requirement by adding, configuring, moving, and removing tiles to show the planning information and details about the release status.

This topic provides an overview of Digital.ai Release reports, including types of dashboards, report permissions, and report caching. Digital.ai Release reports display graphs and statistics based on historical release data stored in the archive database, and are available to users with the appropriate permissions.

This topic describes how release reports display graphs and statistics based on historical release data.

Here is the list of the main parameters for the Digital.ai Release Custom Resource (CR). The following table lists the parameters available in the Digital.ai Release's dairelease_cr.yaml file and their default values.

Prerequisites and planning information for installing or upgrading Digital.ai Release on Kubernetes.

From 23.3 plugin management is possible with XL CLI utility. For more information, see Plugin Manager CLI.

This how-to guide explains how to configure and manage your user profile settings in Release. You can update personal details, change your password, adjust regional preferences, select your default landing page, and manage product analytics and guidance options.

This topic describes how to add one or more tracked items to a delivery. If you want to track a new feature as part of your end to end delivery of a release, you can add the feature as a tracked item in the delivery.

A Register Tracked Items task is an automatic task that registers one or more tracked items to a running delivery.

This topic covers the audit report in Digital.ai Release, which provides full traceability and auditability for auditors. You can generate an audit report for releases that are in progress, completed, or archived.

Core concepts for understanding releases in Digital.ai Release, including the release lifecycle, views, history, and risk awareness.

The release dashboard displays planning information and release status through configurable tiles. You can add, move, resize, and remove tiles to build a view that fits your team's needs.

The Flow Editor shows the phases and tasks in a release or a template. You can use this view to add, move, edit, and delete phases and tasks.

The Release History provides a complete audit trail of all activities performed in a release, capturing user actions along with dates and times. This helps track progress, monitor changes, and troubleshoot issues with greater visibility.

This topic explains the different stages and states a release goes through during its lifecycle in Digital.ai Release.

Overview of the Release MCP Server, its features, available tools, and use cases for Digital.ai Release.

Example prompts and scenarios for automating release management with the Release MCP Server.

The Release MCP Tools Plugin provides the Model Context Protocol tools that AI agents use to work with Digital.ai Release.

The Release planner view provides an interactive Gantt chart to view and edit the duration of the phases and tasks in a release or template. The Gantt chart is a combined timeline of the template or release, its phases, and the tasks within.

This topic covers Release properties, which are configurable attributes that influence the behavior and execution of a release.

The Release table view provides an alternative view of a template or release that is optimized for working with tasks.

In Release, templates are like blueprints for releases. You can use templates to model the ideal process of a release flow. A template can describe a procedure that is used to deliver different applications, or it can describe a procedure that is used to release a particular application and that will be reused for different versions of the application.

This topic provides information on the Release value stream report, which evaluates the quality of completed and aborted releases. The report draws data from the Release archive database, so it does not include releases that are completed or aborted but not yet archived. For more information, see completed and aborted and archive database.

Monitor and manage your releases using calendar, table, planner, code, and relationships views in Digital.ai Release.

This topic provides key information on flagged releases and highlights those with the highest level of automation.

In an active release, you can abort the current phase and restart the execution from any past phase. This can be required if some parts of the release procedure must be repeated. For example, QA rejects a version of the application for release and the test phase must be repeated with an updated version.

Release calculates a risk level for each release based on different factors such as flags, failed or failing states, or due dates. You can see the releases with a high risk level and take the appropriate actions.

This topic illustrates how to use the diagnostic mode in Release.

This guide explains how to set up and run Release Runner using Docker.

In Release, you can schedule your releases by setting start dates and times, end dates and times, and durations on templates, releases, phases, and tasks. When you set dates and durations on phases and tasks, Release automatically adjusts other phases and calculates the release duration and end date.

Kubernetes provides flexible mechanisms to control pod scheduling across your cluster nodes. This guide explores three powerful options for scheduling pods to specific nodes: node selectors, node affinity, and tolerations. Each approach offers different levels of control and complexity to help you optimize your workload placement.

Configuring OIDC is one of the steps in installing or upgrading Digital.ai Release using the Operator-based installer.

This topic illustrates on how to set up the custom context root on the Release.

This article explains how to set up a custom image registry for installing or upgrading Release. A custom image registry can be either public (not password-protected) or private (password-protected).

This topic illustrates on how to set up JVM arguments for Relase containers.

This topic illustrates on how to set up a truststore to store trusted certificates that are used to verify the identities of parties in a secure communication.

Starting with Digital.ai Release version 24.3.0, there are two types of images available for Kubernetes-based setups with an external database or internal message queue: slim and non-slim.

Learn how to manage and configure Kubernetes resource allocations (CPU & Memory) for Digital.ai Release installation through xl-cli

This topic describes how to create a release from a template using various methods and the steps required before starting the release.

This topic explains how to start a new release from an archived release by using the original template and variable values

This topic describes how to configure Digital.ai Release on Kubernetes to store reports and task logs on Amazon S3. This setup eliminates the need for persistent volumes, making storage management easier for Kubernetes-based release instances.

Automate and extend tasks in Digital.ai Release using scripts and scheduled polling.

Overview of task types in Digital.ai Release, including manual, automated, and custom tasks, and how to extend them.

Triggers are automation tools that initiate release tasks based on specific conditions or events. They help streamline your release process by automating repetitive tasks and responding to external events.

If you need to do some customization in the CR file or in the operator deployment, check the following sections.

You must use the custom resource definition file (CR file) in case you want to change the Digital.ai Release's license on sites installed using the Operator-based installer.

Reference for the questions and options presented when upgrading Digital.ai Release with xl kube upgrade.

* Here's a list of questions that you would have to answer to upgrade Digital.ai Release Runner using the xl kube upgrade command.

Patch upgrades from 23.3

If you plan to use an existing database—one that is not created by default by the Operator-based installer—you must configure the relevant database parameters in the dairelease_cr.yaml file.

This topic illustrates how to use an external database instead of the one that is provided with the operator itself.

This topic describes how to create and manage deliveries.

Dependent properties within the XML type-definitions enables dynamic user inputs that adapt based on user selections. This functionality is essential for tasks requiring context-specific input, ensuring that only relevant fields and options are presented, thereby enhancing the user experience.

You can use DevOps as Code to add and generate Software Delivery items, including delivery patterns and all delivery tasks.

This topic illustrates how to replace the CR values that are in clear-text format in the CR with the secret references.

The Release support accelerator gathers data that helps the Digital.ai Support Team to troubleshoot issues.

Digital.ai Release uses variables to make your release templates more flexible and reusable. Variables allow you to parameterize your release processes, making it easier to manage dynamic content and configuration across different environments and scenarios.

A Wait For Stage task is an automatic task that makes the running release wait for a stage to be completed on a running delivery before proceeding.

A Wait For Tracked Items task is an automatic task that waits for items to exist or be completed in a stage on a running delivery.

In Release, phases in a template or release represent blocks of activities that occur in succession. Activities in a template or release are modeled as tasks, which are logically grouped in phases. You can use the release flow editor to manage phases and tasks.

Workflows are bundled within the Release application itself, and are categorized into multiple types based on its use-cases. Additionally, you can also create new workflows and assign it to a specific category.

Before You Begin

The objective is to illustrate how to use the AWS Lambda create function using S3 zip file workflow in Digital.ai Release to create an AWS Lambda function using S3 zip file.

The objective is to illustrate how to use the AWS SecretsManager create secret workflow in Digital.ai Release to create secrets in AWS Secrets Manager, which can again be looked up and substituted across Digital.ai Release templates and workflows.

The objective is to illustrate how to use the Azure KeyVault create secret workflow in Digital.ai Release to create secrets in Azure KeyVault, which can again be looked up and substituted across Digital.ai Release templates and workflows.

The objective is to illustrate how to use the ArgoCD delete application workflow in Digital.ai Release to delete an application in Argo CD that runs in a Kubernetes cluster.

The objective is to illustrate how to use the AWS SecretsManager delete secret workflow in Digital.ai Release to delete secrets in AWS Secrets Manager.

The objective is to illustrate how to use the Azure KeyVault delete secret workflow in Digital.ai Release to delete secrets in Azure KeyVault.

Before You Begin

The objective is to illustrate how to use the Helm install and uninstall application workflow in Digital.ai Release to install and uninstall the application using Helm.

Before You Begin

Before You Begin

The objective is to illustrate how to use the List Azure Container Registry Images workflow in Digital.ai Release to list container images from the Azure container registry.

Before You Begin

This topic illustrates how to use the CheckmarxOne scan Git repository workflow to initiate a CheckmarxOne scan on your git repository, review scan results, and verify compliance directly from within the Digital.ai Release.

The objective is to illustrate how to use the ArgoCD update application workflow in Digital.ai Release to update an application in Argo CD that runs in a Kubernetes cluster.

The objective is to illustrate how to use the AWS SecretsManager update secret workflow in Digital.ai Release to update secrets in AWS Secrets Manager, which can again be looked up and substituted across Digital.ai Release templates and workflows.

The objective is to illustrate how to use the Azure KeyVault update secret workflow in Digital.ai Release to update secrets in Azure KeyVault, which can again be looked up and substituted across Digital.ai Release templates and workflows.

Note: Workflows are bundled with the Release application by default. However, you must have the relevant plugins installed to view these workflows in the Workflows folder. For example, you must have the Deploy plugin installed in Release to view the workflows in the Workflows > Digital.ai Deploy folder.

With Digital.ai Release 23.3, new self-service workflows have been introduced to help Developers onboard their applications more easily with minimal knowledge of tools. These workflows guide users through step-by-step execution of tasks, reducing complexity in setting up environments. They leverage cloud benefits such as scalability, availability, and optimization of applications for the cloud for improved performance and reliability. This also helps ensure adherence to cloud security and compliance best practices.