OpenLM Agent licensing is based on network token that is fully explained in the following article link.

This article is discussing the best method to determine the number of tokens we need to purchase in order to assure availability. The article refers to two possible scenarios:

  • Estimation is done after OpenLM system monitors the license activity
  • Estimation is based on licensing data without a license activity data.

The problem we are trying to solve

OpenLM active agent functionality is based on tokens and we need a method that will help us to determine the number of tokens in order to support the organization.

OpenLM active agent functionality includes the following:

  • Save & Close
  • Suspend & Resume
  • Agent Procedures
  • Actual usage

This functionality is configured for a specific process and OpenLM Tokens are pulled for these features only when the process is started and released back to the OpenLM License Pool when the process is closed. 

Another important fact we need to take into consideration is that we are talking about concurrent tokens that can be used by multiple features. As features are typically not in use all the time, there is a balancing effect that is more significant as we have more users and locations in different timezones.

Decision based on OpenLM data

When we have usage data from OpenLM the decision is easier and based on real data. We basically need to base our decision on the number of concurrent sessions of the software we would like to support. 

Let’s take a simple example. Company with one license manager and one timezone. The license usage chart looks like this:

Checking the license usage chart for the last 90 days shows that if we have tokens to cover 9 concurrent users, we will provide most of the demand. If we want to cover 100% of the demand, we will need tokens for 13 concurrent users. 

Since this is Autodesk licenses, we need 400 OpenLM per session. So we need any number of tokens between 9*400=3600 to 13*400=5200 tokens.

It is important to keep the following in mind:

  • Unused tokens can be utilized by another monitored process. The more processes are monitored, the token usage balancing effect is bigger.
  • Users in other timezones can use the same tokens, on another time.

Estimation based on licensing data 

Let’s review the same example from the previous section, assuming that we don’t actually have the license usage data from OpenLM. 

What we know is the number of Autodesk seats – 14. 

Purchasing OpenLM tokens that allows 100% coverage requires us to purchase 14*400=5200 OpenLM Tokens.

We can reduce the number OpenLM token we purchase based on the following assumptions:

  1. We don’t really utilize all our Autodesk seats.
  2. We will get benefits, even if some of the Autodesk sessions are not managed by OpenLM.
  3. We have multiple processes we would like to manage and there will be a balancing effect.
  4. We have users in multiple time zones.

Summary

OpenLM Active Agent functionality is licensed using concurrent reusable tokens and helps organizations to maintain high efficiency in license usage. 

This article suggests a method that helps organizations to estimate the number of OpenLM Tokens they need to purchase in order to support their users. Basing this decision on OpenLM license usage information can yield a better result but a decision based on licensing information only can be used.

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