Creating a Custom MarkLogic AMI with Packer
22 September 2021 02:17 PM


Packer from HashiCorp is a provisioning tool, allowing for the automated creation of machine images, extending the ability to manage infrastructure to machine images. Packer supports a number of different image types including AWS, Azure, Docker, VirtualBox and VMWare.

Packer can be used to create a customized MarkLogic Amazon Machine Image (AMI) which can then be deployed to AWS and used in a Cluster. We recommend using the official MarkLogic AMIs whenever possible, and making the necessary customizations to the official images. This ensures that MarkLogic Support is able to quickly diagnose any issues that may occur, as well as reducing the risk of running MarkLogic in a way that is not fully supported.

The KB article, Customizing MarkLogic with Packer and Terraform, covers the process of customizing the official MarkLogic AMI using Packer.

Setting Up Packer

For the purpose of this example, I will assume that you have already installed the AWS CLI, with the correct credentials, and you have installed Packer.

Packer Templates

A Packer template is a JSON configuration file that is used to define the image that we want to build. Templates have a number of keys available for defining the machine image, but the most commonly used ones are builders, provisioners and post-processors.

  • builders are responsible for creating the images for various platforms.
  • provisioners is the section used to install and configure software running on machines before turning them into images.
  • post-processors are actions applied to the images after they are created.

Creating a Template

For our example, we are going to take build from the official Amazon Linux 2 AMI, where we will install the required prerequisite packages, install MarkLogic, and apply some customizations before creating a new image.

Defining Variables

Variables help make the build more flexible, so we will utilize a separate variables file, marklogic_vars.json, to define parts of our build.

  "vpc_region": "us-east-1",
  "vpc_id": "vpc-06d3506111cea30d0",
  "vpc_public_sn_id": "subnet-03343e69ae5bed127",
  "vpc_public_sg_id": "sg-07693eb077acb8635",
  "instance_type": "t3.large",
  "ssh_username": "ec2-user",
  "ami_filter": "amzn2-ami-hvm-2.*-ebs",
  "ami_owner": "amazon",
  "binary_source": "./",
  "binary_dest": "/tmp/",
  "marklogic_binary": "MarkLogic-10.0-4.2.x86_64.rpm"

Here we've identified the instance details so our image can be launched, as well as the filter values, ami_filter and ami_owner, that will help us retrieve the correct base image for our AMI. We are also identifying the name of the MarkLogic binary, along with some path details on where to find it locally, and where to place it on the remote host.

Creating Our Template

Now that we have some of the specific build details defined, we can create our template, marklogic_ami.json. In this case we are going to use the build and provisioners keys in our build.

    "builders": [
        "type": "amazon-ebs",
        "region": "{{user `vpc_region`}}",
        "vpc_id": "{{user `vpc_id`}}",
        "subnet_id": "{{user `vpc_public_sn_id`}}",
        "associate_public_ip_address": true,
        "security_group_id": "{{user `vpc_public_sg_id`}}",
        "source_ami_filter": {
          "filters": {
          "virtualization-type": "hvm",
          "name": "{{user `ami_filter`}}",
          "root-device-type": "ebs"
          "owners": ["{{user `ami_owner`}}"],
          "most_recent": true
        "instance_type": "{{user `instance_type`}}",
        "ssh_username": "{{user `ssh_username`}}",
        "ami_name": "ml-{{isotime \"2006-01-02-1504\"}}",
        "tags": {
          "Name": "ml-packer"
    "provisioners": [
        "type": "shell",
        "script": "./"
        "destination": "{{user `binary_dest`}}",
        "source": "{{user `binary_source`}}{{user `marklogic_binary`}}",
        "type": "file"
        "type": "shell",
        "inline": [ "sudo yum -y install /tmp/{{user `marklogic_binary`}}" ]

In the build section we have defined the network and security group configurations and the source AMI details. We have also defined the naming convention (ml-YYYY-MM-DD-TTTT) for the our new AMI with ami_name and added a tag, ml-packer. Both of those will make it easier to find our AMI when it comes time to deploy it.


In our example, we are using the shell provisioner to execute a script against the machine, the file provisioner to copy the MarkLogic binary file to the machine, and the shell provisioner to install the MarkLogic binary, all of which will be run prior to creating the image. There are also provisioners available for Ansible, Salt, Puppet, Chef, and PowerShell, among others.

Provisioning Script

For our custom image, we've determined that we need install Git, to create a symbolic link MarkLogic needs on Amazon Linux 2, and to setup /etc/marklogic.conf to disable the MarkLogic Managed Cluster feature, all of which we will do inside a script. We've named the script, and it is stored in the same directory as our Packer template.

#!/bin/bash -x
echo "**** Starting ****"
echo "**** Creating LSB symbolic link ****"
sudo ln -s /etc/system-lsb /etc/redhat-lsb
echo "**** Installing Git ****"
sudo yum install -y git
echo "**** Setting Up /etc/marklogic.conf ****"
echo "export MARKLOGIC_MANAGED_NODE=0" >> /tmp/marklogic.conf
sudo cp /tmp/marklogic.conf /etc/
echo "**** Finishing ****"

Executing Our Build

Now that we've completed setting up our build, it's time to use Packer to create the image.

packer build -debug -var-file=marklogic_vars.json marklogic_ami.json

Here you can see that we are telling Packer to do a build using marklogic_ami.json and referencing our variables file with the -var-file flag. We've also added the -debug flag which will disable parallelism and enable debug mode. In debug mode, Packer will stop after each step and prompt you to hit Enter to go to the next step.

The last part of the build output will print out the details of our new image:

Wrapping Up

We have now created a customized MarkLogic AMI using Packer, which can be used to deploy a self managed cluster.

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