Forum Discussion

BalajiL's avatar
BalajiL
Resolver I
10 months ago

Capacity Derive

I’m reaching out for a quick assist in validating the appropriate Microsoft Fabric SKU for a customer currently in the proposal stage. The customer is looking for ROI insights compared to their exist...
data engineering
v-karpurapud's avatar
v-karpurapud
Community Support
10 months ago

Hi BalajiL 

We have not received a response from you regarding the query and were following up to check if you had the opportunity to review the information provided. Please feel free to contact us if you have any further questions.

 

Thank You.

BalajiL's avatar
BalajiL
Resolver I
10 months ago

Hi v-karpurapud 

Looks the SKU calculator requires lot of improvement to derive the capacity for the customer ask. Many projects are running in Databricks, Synapse etc. There should be a way to map the existing load parameters exists and to derive capacity.  The SKU calculator provides varies SKU with the same parameter input in multiple iteration sometimes it shows F256 or F512 without any modification on the parameter.  Could you please help how to use batch cycle in the sku calculator with various tables and batches - it is not straight forward approach. I would request this should be considered and enhanced further. 

 

  • v-karpurapud's avatar
    v-karpurapud
    Community Support
    10 months ago

    Hi BalajiL 
    Thank you for providing such comprehensive feedback.
     
    You have highlighted an important consideration regarding the SKU calculator's interpretation of workload parameters like batch cycles, table counts, and data volume. Currently, the calculator views the “number of batch cycles” as a measure of concurrent workload intensity, rather than the total number of runs over a day. This approach may lead to overestimating capacity needs, especially when multiple smaller or regional batches are run sequentially instead of concurrently.

    The fluctuations in estimated SKUs (such as switching between F256 and F512 without clear parameter changes) may be attributed to the tool’s internal rounding or recalculation logic. For more precise results, it is recommended to enter peak concurrency values the highest number of jobs or pipelines running in parallel and the data volume processed concurrently, rather than total daily or regional batch runs.
     

    For further improvements and enhancements, it is recommended to share this feedback through theCommunity Feedback - Microsoft Fabric Community.  Submitting detailed input there will help the product team better understand real-world use cases and prioritize enhancements such as clearer parameter definitions, improved handling of sequential versus concurrent workloads, and stronger alignment with Databricks or Synapse metrics for more accurate capacity sizing.

    Regards,

    Microsoft Fabric Community Support Team.

    • BalajiL's avatar
      BalajiL
      Resolver I
      10 months ago

      Thanks v-karpurapud , I will share the details in the feedback forum, so that these information reach out to product team and they can work on enhancing calculator. 

      • v-karpurapud's avatar
        v-karpurapud
        Community Support
        10 months ago

        Hi,

        Thank you for the update. Hope you issue resolves soon.