📄️ Get Started With Blueprints
Digital.ai offers blueprints to help you create declarative YAML files that simplify the infrastructure provisioning and application deployment process. You can use blueprints to get started with the cloud by following examples that show best practices for provisioning a cloud-based infrastructure and deploying your applications to it.
📄️ Deploy/Release Public Blueprints
A blueprint guides you through a process that automatically generates YAML files for your applications and infrastructure. The blueprint asks a short series of questions about your application and the type of environment it requires, and the Digital.ai Command Line Interface (XL CLI) uses your answers to generate YAML files that define configuration items and releases, plus special files that manage sensitive data such as passwords.
📄️ Blueprint YAML Format
This topic provides a reference for the DevOps as Code YAML file structure for a blueprint. You can review the publicly-available blueprint files alongside the content in this topic to get a better understanding of how fields, values and options are specified.
📄️ Manage Blueprint Repositories
A blueprint repository is a remote repository that contains templates and source code for blueprint functionality. Each time you run the XL CLI xl blueprint command, it fetches files from the blueprint repository.
📄️ Deploy an App to AWS Using a Blueprint
Transitioning a microservice application to the Amazon Web Services (AWS) cloud infrastructure can be a daunting and complex task for a development team new to AWS. The Deploy/Release Blueprints for AWS can streamline the process of creating the AWS infrastructure, orchestrating the pipeline using Release, and deploying applications using Deploy.
📄️ Deploy to Azure With Using the ARM Template Blueprint
The Azure Resource Manager (ARM) allows users to deploy applications to Azure using declarative JSON templates. In the DevOps as Code CLI, you can use the Basic ARM Template to run blueprints on the platforms hosted on Azure, by creating ARM templates. This can greatly simplify the process of provisioning resources from Deploy and Release in an Azure environment.