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sun-sboyanapall's avatar
sun-sboyanapall
Icon for Advocate I rankAdvocate I
1 year ago
Solved

Fabric Capacity Estimation

We are planning on migrating from DOMO to Fabric F64 SKU, we have around 100 - 200 datasets ranging from 1k rows to 1mil rows at max one of the sample dataset is consuming around 1000CUs each time...
capacities
  • nilendraFabric's avatar
    nilendraFabric
    1 year ago

    Hello sun-sboyanapall 

     

    FabianSchut  shared a great guidance. 
    let me put my 2 cents here as well

     

    Workload Estimation
    Your workload involves:
    • ETLs: 50 ETLs with varying frequencies:
    • 50% (25 ETLs) run hourly.
    • 30% (15 ETLs) run daily.
    • 20% (10 ETLs) run weekly.
    • CU Consumption per ETL: Each ETL consumes approximately 1000 CUs per run.
    From the calculations:
    • Hourly CU Consumption: CUs.
    • Daily CU Consumption: CUs.
    • Weekly CU Consumption: CUs. Averaged per day: CUs.
    The total daily CU consumption:

    25000*24 +360000+ 240000=1,200,000 cu

     

    Monthly consumption:

    12000000 * 30 =360,000,000 cU/month

     

    F64 Capacity
    The F64 SKU provides:
    • Capacity Units (CUs):

    64*60*60*24=5,529,600 cu

     

    Monthly capacity 

    5529600* 30 =165,888,000 cu

     

    Your estimated workload (36M CUs/month) is well within the F64 capacity (165.9M CUs/month). This leaves significant headroom for additional workloads or unexpected spikes.

    User Load and BI Reports
    With around 100 users accessing BI reports:
    • The F64 SKU supports up to 50 concurrent DirectQuery connections and a maximum of 30 live connections per second, which should be sufficient for your user base.
    • The maximum memory per query is 10 GB, and the total memory for semantic models is 25 GB, which aligns with typical BI workloads.


    Cost Optimization: Reserved pricing for F64 is recommended if the capacity will be utilized consistently.
    • Feature Requirements: F64 supports advanced features like AI Skills and Copilot, which may be beneficial depending on your use case.

     

     

    Thanks

     

     

     

     

     

     

     

v-karpurapud's avatar
v-karpurapud
Icon for Community Support rankCommunity Support
1 year ago

Hi sun-sboyanapall 


Thank you for reaching out to the Microsoft Fabric Community Forum.


I appreciate the insights shared by both FabianSchut  and nilendraFabric . In addition to that , here are few points to optimize your workload and capacity.

 

Optimizing ETL Execution:

 

  • If all ETLs are scheduled to run at fixed intervals, try staggering the schedules to distribute CU consumption more evenly over time. Running multiple ETLs simultaneously can cause peak load congestion.
  • Identify ETLs that can be batched or refreshed incrementally instead of performing full dataset refreshes, which will help reduce CU consumption.
  • While the average CU consumption is well within the F64 capacity, ensure that peak loads (e.g., multiple ETLs running at the same time) do not exceed the capacity.

 

Additionally, refer to the documents below for guidance on effectively planning, optimizing, and managing your Microsoft Fabric capacity and ETL processes.

 

By following these steps, you can confidently proceed with the F64 SKU while ensuring scalability and cost efficiency.

 

If my response has resolved your query, please mark it as the Accepted Solution to help others. Additionally, I would appreciate a 'Kudos' if you found my response helpful.

Thank you!