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To learn more about ml-gradle, choose from one of the links below, or browse the index of Wiki pages on the right:

Getting an error with ml-gradle? Please see the Debugging guide.
Getting started - this walks you through the basics of setting up a new project and extending it
Project layout - see examples of what a typical ml-gradle project looks like
Example projects - working examples of some of the features of ml-gradle
Property reference - list of all properties supported by ml-gradle
Resource reference - list of all resources supported by ml-gradle
Task reference - list of all tasks supported by ml-gradle

Looking to migrate a Roxy project to ml-gradle? Please see the migration guide.

ml-gradle Configuration

"Configuration" can refer to several aspects of ml-gradle; the following links describe the different ways that ml-gradle can be configured:

Configuring ml-gradle describes how the ml-gradle plugin can be configured via Gradle properties and scripting in the Gradle build file.
Configuring resources describes how to create files that define the different MarkLogic resources for an application, such as databases, app servers, scheduled tasks, etc.
Configuring security describes the different MarkLogic users that can be used for each of the jobs performed by ml-gradle during a deployment

ml-gradle provides a number of features for loading modules, and there are a number of things to be aware of as well, as described by these pages:

ml-gradle easily integrates with other Java-based MarkLogic tools, as described by the following pages:

A common way to extend ml-gradle is by creating your own Gradle tasks, but it can be extended and overridden at lower levels as well:

Writing your own task describes the support ml-gradle provides for custom tasks for your project
Writing your own command describes how to extend and customize the behavior of mlDeploy and mlUndeploy
Writing a task that talks to a different port describes how to write tasks that talk to a variety of ports in MarkLogic