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daniele_tiles
Advocate II
Advocate II

Evaluations for migrating models from P3 to P1

Hi to all,

one of our client has got a P3, and it's thinking to buy an additional P1 to move some "less important semantic models" to that P1.

I wanted to understand if it's a correct and possible way to think:

 

  1. A P1 is the same of an F64, so it has 64*3.600*14 = 3.225.600 CU seconds available in 14 days.
  2. From the Fabric Capacity Metrics App I can get the last 14 days of usage of model in CU seconds. So I can think to move models which have a consumption less then 3.225.600 CU seconds (I'd go even for the 60% of 3.225.600, so to be under the 80% limit, but to stress a bit this capacity and try to free most of the "less used/useful" semantic models).

Clearly, it should also be evaluated by how big are the models and so on, but still this would be a starting point for a list to evaluate and a possible threshold to not go over.

Any thought will be appreciated 🙂

 

Daniele

1 ACCEPTED SOLUTION
Anonymous
Not applicable

Hi @daniele_tiles ,

I think the approach of evaluating the migration of the semantic model from P3 to P1 based on CU second consumption is fundamentally sound. Not only does this strategy help ensure that P1 is not overstressed, but it also leaves room for unexpected spikes in usage or future growth.


Larger, more complex models may consume more resources and have different performance characteristics on P1 compared to P3. P1 capacity may handle fewer concurrent queries than P3, so I think you can read this document for more information: What is the Microsoft Fabric Capacity Metrics app? - Microsoft Fabric | Microsoft Learn

 

 

 

Best Regards

Yilong Zhou

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

View solution in original post

2 REPLIES 2
Anonymous
Not applicable

Hi @daniele_tiles ,

I think the approach of evaluating the migration of the semantic model from P3 to P1 based on CU second consumption is fundamentally sound. Not only does this strategy help ensure that P1 is not overstressed, but it also leaves room for unexpected spikes in usage or future growth.


Larger, more complex models may consume more resources and have different performance characteristics on P1 compared to P3. P1 capacity may handle fewer concurrent queries than P3, so I think you can read this document for more information: What is the Microsoft Fabric Capacity Metrics app? - Microsoft Fabric | Microsoft Learn

 

 

 

Best Regards

Yilong Zhou

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

SaiTejaTalasila
Super User
Super User

Hi,

 

  • I don't think there is any standard procedure for this:
    You can keep unimportant workspaces or less utilized workspaces on P1 and keep important and high-demand workspaces (with a larger number of users and more activity) on P3 capacity. Monitor both capacities on the Fabric Capacity Metrics app for 1 or 2 weeks, and you can shuffle the workspaces between the capacities if required.
  • User activity details you can get  from audit logs.

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