How to confirm the concurrency of users on Fabric SKU's. Is there any benchmark available.

[Samsfabric]

Is there any Benchmark available to confirm the concurrency of USers supported for each Fabric SKU i.e. F64, F128...F1024. Please suggest.

[v-hashadapu]

Hi @Samsfabric , Hope you're doing fine. Can you confirm if the problem is solved or still persists? Sharing your details will help others in the community.

[v-hashadapu]

Hi @Samsfabric , Hope you're doing okay! May we know if it worked for you, or are you still experiencing difficulties? Let us know — your feedback can really help others in the same situation.

[v-hashadapu]

Hi @Samsfabric , hope you are doing great. May we know if your issue is solved or if you are still experiencing difficulties. Please share the details as it will help the community, especially others with similar issues.

[AntoineW]

Hi @Samsfabric,

There is no official published benchmark on how many users each Fabric SKU can support concurrently. However, user concurrency in Microsoft Fabric is governed by compute resource availability, primarily through Capacity Units (CUs) and Spark session management.

Concurrency depends on:

• ⚙️ Session size (Small, Medium, Large, XLarge)

• 🔢 Number of available Capacity Units (CUs) in your Fabric SKU

• ⚡ Starter pool configuration (to reduce job startup latency)

🧮 How concurrency works in Fabric

Fabric uses CUs to run Spark jobs. Each session consumes a fixed amount of CUs:

Session Size CU Usage Example

Small	2 CUs	Basic data exploration
Medium	4 CUs	Most pipelines & notebooks
Large	8 CUs	Large joins, transformations
XLarge	16 CUs	Memory-intensive workloads

💡 So on an F64 capacity (64 CUs):

• You could run 16 Medium sessions (4 CU) concurrently

• Or 8 Large sessions, etc.

👉 Beyond this limit, jobs are queued automatically
📌 Ref: Spark job concurrency and queueing

 

⚡ Tip: Improve startup performance with Starter Pools

By default, each Spark session needs a few seconds to initialize — which may feel like a bottleneck when multiple users start at once.

You can pre-warm compute nodes using the Starter Pool feature, which allows Fabric to keep a fixed number of Spark sessions ready to go.

📌 Ref: Configure starter pools

✅ Benefits:

• Lower cold start latency for users

• Better concurrency experience during high-usage periods

📈 Monitoring real concurrency

You can monitor:

• Current Spark job queue

• CU consumption per job/session

• Session size distribution

👉 Using the Capacity Metrics App

Hope this helps!

Best regards,
Antoine

[v-hashadapu · Accepted solution]

Hi @Samsfabric , Thank you for reaching out to the Microsoft Community Forum.

As of July 2025, Microsoft does not provide any official benchmarks that define how many concurrent users each Fabric SKU can support. Concurrency isn’t capped by a fixed number of users per SKU, it’s determined by available CPU, memory and throughput, which are dynamically shared across workloads.

Instead of setting hard limits, Microsoft recommends monitoring capacity in real time using the Fabric Capacity Metrics App. This tool helps you track compute usage metrics like CPU load and query queue length to understand how your SKU is performing. If you're seeing high resource usage or frequent queuing, it's a sign you're approaching the concurrency limits of your current capacity.

You can manage and fine-tune workload performance through Fabric Capacity Settings and optimize usage to reduce pressure on resources. When capacity is exhausted, Fabric applies throttling to maintain stability rather than dropping requests.

For Power BI-specific scenarios, tools like the Load Assessment Planning Tool and Realistic Load Testing Tool let you simulate user loads and observe how your capacity handles concurrent report usage.

So, while Microsoft doesn’t define a specific user cap per SKU, you have the tools to monitor, test, and scale based on your actual usage patterns.

Manage your Fabric capacity - Microsoft Fabric | Microsoft Learn

What is the Microsoft Fabric Capacity Metrics app? - Microsoft Fabric | Microsoft Learn

Understand the metrics app compute page - Microsoft Fabric | Microsoft Learn

Evaluate and optimize your Microsoft Fabric capacity - Microsoft Fabric | Microsoft Learn

Understand your Fabric capacity throttling - Microsoft Fabric | Microsoft Learn

Workload Management - Microsoft Fabric | Microsoft Learn

Power BI embedded analytics assess load - Power BI | Microsoft Learn

PowerBI-Tools-For-Capacities/RealisticLoadTestTool/Readme.md at master · microsoft/PowerBI-Tools-For...

[ibarrau]

Hi. I don't think I have read something like that at the docs. I do remember a table for Embedding screnarios with peak renders. But that's if you develop a web to embed a report, I don't think that would be the same for Fabric or Power Bi Service reading reports.

Just as a reference the table was like this:

That a reference of my memory. The embedding licenses mapped with Fabric SKU as a reference. I would say that F4 and F2 it's half and half of users.

I hope that helps, as a baseline