View source for Configuring an RLM Server/Running RLM in Kubernetes

== Use case ==

The question of how (or why) to run RLM in Kubernetes would most often arise in a cloud application that uses ADE.

The ADE license is priced based on the number of servers that it is installed on. For a Kubernetes workload, this equates to the number of pods using ADE at the same time.  A floating ADE license is one way to manage that, which requires an RLM instance to count how many are current active (and to limit it to the number of seats in the license). 

== Does it make sense? ==

It may make sense to use floating licenses in the above use case to manage the number of ADE instances.  However, the question here is whether it makes sense to install RLM in a pod.  The simple answer is no, not really. 

You should think of a license manager as an organization-wide application. An organization may have multiple clusters. Instead of managing licenses separately inside a cluster, it makes more sense to run RLM on a dedicated computer (in GCP, Azure or AWS, this would be on a VM provisioned for this purpose). Then your ADE instances in each cluster workload would get their license from this one server.  This RLM server lives outside of any Kubernetes cluster.

You can most likely provision the lowest-end Windows server VM as your RLM host. RLM as an application requires very little in terms of all resources (memory, disk, CPU, bandwidth, etc.). 

== How ==

We recommend against installing RLM in a pod (see above). If you absolutely are hellbent on requiring it to run within a pod, here's how.

These instructions focus primarily on how to solve the license activation problem. We assume you know (or have other resources) for the details of creating a docker image).

# [https://analytica.com/users/manual-activation/ Manually activate] your RLM-on-a-VM license using:
#* '''Product:'''ADE
#* '''License type:''' Centrally managed
#* '''Email:''' (your email)
#* '''Activation key:''' (the one provided by Lumina for running RLM on a VM. NOT the ADE activation key!!!)
#* '''Count:''' 1
#* '''Hostid:''' host=rlm-pod
# [https://analytica.com/users/manual-activation/ Manually activate] your ADE license using:
#* '''Product:'''ADE
#* '''License type:''' Centrally managed
#* '''Email:''' (your email)
#* '''Activation key:''' (the one provided by Lumina for ADE)
#* '''Count:''' (The number of seats of your license)
#* '''Hostid:''' host=rlm-pod
# Install the RLM administration bundle on your computer, and then add the files from it to your docker image.
#: Details not covered here, but you should go through [[Configuring an RLM Server]].
#:Requires knowledge of creating docker images, not covered here.
# Get both license files from the manual activation from your email and include them in your Docker image in your RLM license folder.
# Have the docker file start the RLM service.  ** TO DO -- add details here **
# Build your docker image, name it rlm-image
# Push your image to your artifacts registry or GCP (or equiv on AWS or Azure). 
# Create this <code>rlm.yaml</code> file:
 apiVersion: v1
 kind: Pod
  metadata:
    name: rlm-pod
 spec:
    hostname: rlm-pod
    containers:
    - name: rlm-container
      image: us-west1-docker.pkg.dev/my-proj/my-repo/rlm-image:latest
      ports:
     -  containerPort: 5053
      - containerPort: 5054
# Run: <code>kubectl apply -f rlm.yaml</code>

== See also ==
* [[Configuring an RLM Server]]
* [[Installing ADE in a Docker image]]