27 docs tagged with "deploy"

Custom or community plugins that want to support the transform of artifacts using Stitch rules, must call the Stitch Engine transformer.

* When you install Digital.ai Deploy, the Central Configuration feature is implemented by default on the application server (Master) as an embedded service.

As we move towards Kubernetes-based containerized Deploy solution, the Digital.ai Deploy shared configuration files are moved to a centralized location from where they are managed by the Central Configuration Management server. The idea of Central Configuration is to have one central place—in this case, the Digital.ai Deploy's Master server—where you can store, distribute, and manage configuration data for master/worker pods in your cluster. Digitial.ai Central Configuration is the process of maintaining and managing the configuration from a centralized location in the file system. With a centralized management, you can configure workers and masters easily and more efficiently. For example, if you have a Master-Master and Master-Worker setup with two masters and two workers, before Central Configuration you had to individually modify the configuration on all four instances. With the Central Configuration, the configurations are automatically reflected in all the instances.

From Deploy 22.0, the Deploy Task Engine is used to install workers on Kubernetes clusters. This section describes how to configure Kubernetes Operator to use the Deploy Task Engine setup.

Implementing custom input/output formats

Stitch is a collection of tools available out-of-the-box with Deploy. Stitch extends Deploy’s capability and enables the field experts in your organization to define and build scaled customizations and variants of reusable deployment patterns that your cloud-native teams can effortlessly consume for their cloud and container deployments.

Application Deployment

This section describes how to install the Deploy application on various Kubernetes platforms.

This section provides an introduction to Kubernetes Operator as a custom installer to deploy Digital.ai Deploy.

Stitch is a new capability of digital.ai Deploy that provides a declarative way to customize configuration files for deployments of bespoke applications and commercial of the shelf components (COTS). It is designed for the world of cloud and containers, and builds on top of Deploy concepts of UDM model, types, rules engine and plugins.

Keycloak is the the default authentication manager for Deploy. This topic describes the steps involved in configuring Keycloak before and after the Deploy installation.

This tutorial will teach you how to use Stitch capability of Digital.ai Deploy, when deploying to a Kubernetes cluster. For more information about Stitch, please see Introduction to Stitch.

The Lock plugin is a Deploy plugin that adds capabilities for preventing simultaneous deployments.

In order for Deploy to apply any Stitch transformation, the plugin needs to have a support for Stitch since it controls the content in it.

When user wants to generate additional documents based on the content of the deployment plugin uses preprocessing or postprocessing stitch transformation. Preprocessing should be used if generated documents should go through regular stitch transformations and postprocessing should be used when no additional transformation is expected.

Stitch sources are created under the Configuration tab of the CI Explorer. Using configuration or folder permissions, you can show/hide Stitch sources. As a Stitch source is also a CI, it has the same logic for permissions as all other CI’s.

This article provides information on how to create an Artemis cluster (JMS 2.0) and integrate it with Deploy.

This topic outlines the procedure to setup Active Messaging Queue (MQ) Artemis in highly available configuration with UDP protocol. It also describes how Digital.ai Deploy can be connected to Artemis nodes.

Stitch macros are reusable building blocks which group the common processors used inside of Stitch rules.

Some of the Stitch features, like preview or dry run, can be run through either Jython or XL CLI.

When you use the Preview option of the deployment plan, you can also see the Stitch preview for it, by using the toggle button to switch between two views. After clicking on the Stitch preview toggle, you can also browse and view Stitch invocation details.

A Stitch processor is a part of a Stitch rule that is responsible for modifying the application's resource configuration files during the deployment planning phase. Processors are defined in a Stitch YAML file in the processor array.

The Stitch Workbench is a part of Deploy's web-based user interface that provides an overview of all customizations known to Stitch.

This section describes how to troubleshoot some of the common issues you may face when installing the Deploy application using Operator-based installer.

You may want to uninstall the Deploy Operator to troubleshoot an issue where the Deploy installation is not working properly, or you no longer want to use the Operator. This section describes the steps to uninstall the Digital.ai Deploy Operator.

This section describes how to upgrade to the latest Kubernetes Operator-based Deploy solution on various Kubernetes platforms. Deploy 22.1 supports the following upgrades on the supported Kubernetes platforms:

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