Earlier last week I had deployed the latest version of vRealize Network Insight (vRNI) 3.2 in my home lab to learn more about the product and its capabilities. The vRNI setup involves involves deploying two Virtual Machines, the first being the main vRNI Platform OVA. Once the vRNI Platform VM has been deployed, you will need to activate it with a license key and then generate a shared secret which is then used to deploy the vRNI Proxy OVA. Using the share secret, the vRNI Platform VM will be able to automatically detect when the vRNI Proxy VM is on the network and associate it with the deployment.
The workflow is pretty straight forward but as many of you know me, if I need to manually do something once, it means I should probably automate it for the future 🙂 I had looked around the documentation and did not see any published APIs for the initial setup and configuration. Although a CLI exists, it was only available post-deployment and it required SSH which I did not want to have to rely upon. I ended up reverse engineering the UI to replicate the workflow from an automation standpoint. I created a small PowerCLI script called vRNI-Deploy.ps1 and below are the instructions on using the script.
Step 0 - Obtain a vRNI License Key, which is required to setup vRNI. You may need to work with your VMware Account team or contact VMware Sales to get an evaluation license key.
Step 1 - Download both the vRNI 3.2 Platform and Proxy OVA from here.
Step 2 - Download the vRNI-Deploy.ps1 script to a system that has the latest release of PowerCLI 6.5 R1 installed.
Step 3 - Edit the following sections of the script which you can find more details below:
The full path to both the vRNI Platform and Proxy OVAs:
The vRNI License Key:
The configuration of the vRNI Platform VM:
The configuration of the vRNI Proxy VM:
General deployment configuration for both VMs:
Note: The medium (smallest) deployment requires at least 42GB of memory (32GB reserved for Platform VM and 10GB reserved for the Proxy VM). Please ensure you have sufficient resources before deploying into your environment.