26 docs tagged with "deploy"

Application Onboarding is a modernized control panel for Developers to enable efficient application onboarding in a hybrid or multi-cloud environments. With Digital.ai Release 23.1, we are bringing in new self-service workflows so that Developers can onboard their applications easier with minimum knowledge of tools. Newly introduced workflows guide users through step-by-step execution of tasks, reducing complexity in setting up environments. Application Onboarding leverages cloud benefits such as scalability, availability, and optimizing applications for the cloud for improved performance and reliability. It also helps ensure adherence to cloud security and compliance best practices.

This topic describes how to connect Release to Deploy servers, enabling seamless integration for deployment automation.

From 23.3 version, there are changes how is working answer to the question:

The Deploy container CI plugin allows you to start a deployment of an application on Deploy.

The Deploy container plugin allows you to start a deployment of an application on Deploy.

The Deploy plugin for Release allows you to start a control task or to start a deployment of an application on Deploy. It also provides the functionality to trigger undeployment of an application already deployed on Deploy.

The Deploy task provides integration with Deploy, the Application Release Automation solution as part of the DevOps Platform. It is an automated task that triggers the deployment of an application to an environment in Deploy. Both the application and environment must be configured in Deploy. The task provides live updates of the deployment process and completes automatically when the deployment succeeds.

Note: 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 Deploy or Release installation.

Note: 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 Deploy or Release installation.

Note: 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 Deploy or Release installation.

Note: Here is a basic setup for the AWS Openshift cluster,

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

The Live Deployments feature enables you to track deployments from various sources and embed them in your release process. Previously, only deployments that were started from a task in the release process were known in Release. You can now listen to deployment events from external tools like Digital.ai Deploy and ArgoCD and view live updates in Release. All the deployment activities are on the same page, whether it comes from cloud-native Kubernetes environments or classic middleware. Additionally, you can make the external deployments part of the release flow, even when they are not orchestrated by Release.

The community xlr-xldeploy-plugin and the officially-supported xlr-xld-plugin can both exist within the same Release instance without any conflicts.

This topic introduces the Octopus Deploy Plugin for Release, which facilitates integration with Octopus Deploy for managing deployments within release pipelines.

The Live Deployments Discovery wizard allows you to create connections to ArgoCD or your server's Deploy applications. You can use this wizard to discover and onboard applications with ease.

You use the XL CLI's xl kube command to install or upgrade Digital.ai Deploy or Release, or Release Runner. For more information, see XL Kube Command Reference.

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

Workflows are a combination of tasks that can be executed in an interactive session, with pre-built best practices. Once you have this setup in place, all you would be doing is to select the workflows from the self-service catalog and execute them in step-by-step view to interactively setup applications in Argo CD and Deploy.

In this article, you will learn how to set up a custom image registry to install or upgrade Release. A custom image registry can either be public (not password protected) or private (password protected).

This topics provides information about creating and configuring a truststore, importing certificates, and adjusting Release settings to ensure secure communication with the Deploy server.

Note: Live Status of Deployed Applications is a feature in Tech Preview—released in Digital.ai Release 22.3—enabled by default. You must disable this feature (using the feature flag) if you do not want to use it.

Before You Begin

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 ArgoCD update application workflow in Digital.ai Release to update an application in Argo CD that runs in a Kubernetes cluster.

With Digital.ai Release 23.3, we are bringing in new self-service workflows so that Developers can onboard their applications easier with minimum knowledge of tools. Newly introduced workflows guide users through step-by-step execution of tasks, reducing complexity in setting up environments. It leverages cloud benefits such as scalability, availability, and optimizing applications for the cloud for improved performance and reliability. It also helps ensure adherence to cloud security and compliance best practices.