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Microsoft Fabric: Overcoming Capacity and Performance Challenges

Optimize your Microsoft Fabric environment with insights on capacity management, performance bottlenecks, and cost control strategies to ensure seamless transitions from Power BI Premium.
Chris Sutcliffe
Microsoft Fabric: Overcoming Capacity and Performance Challenges

Microsoft Fabric has emerged as a powerful, unified analytics platform, offering an exciting evolution for organizations leveraging Power BI Premium. While Fabric promises enhanced capabilities and streamlined data operations, the transition isn’t always without its challenges.

Many organizations, especially those accustomed to Power BI Premium, are finding themselves grappling with unexpected capacity issues, performance bottlenecks, and a lack of clear visibility into their Fabric environments.

Understanding Microsoft Fabric Capacity Issues

The shift from Power BI Premium to Fabric introduces new challenges for capacity management. While Fabric offers a unified capacity model across various workloads, understanding how these workloads consume resources and impact overall performance can be a steep learning curve. Organizations often encounter:

  • Unexplained Slowdowns: Reports and dashboards that once performed flawlessly in Power BI Premium may experience significant delays.
  • Capacity Exhaustion: Despite choosing an equivalent capacity to Power BI Premium e.g. P1 = F64, users encounter errors indicating resource limitations.
  • Cost Increases: Due to these persistent capacity issues, most customers are forced to scale up their Fabric capacity, significantly increasing their operational costs.

     

Gaining Visibility and Observability

To truly master your Microsoft Fabric environment, you need a clear and comprehensive view of its inner workings. Microsoft Fabric provides a robust set of out-of-the-box reports and monitoring apps, such as the Fabric Capacity Metrics app and the Monitoring Hub, which offer valuable insights into your capacity usage, activity, and performance. Although these tools are a great starting point, providing a foundational understanding of your Fabric footprint.

However, tracking the usage patterns of a large organization can be complex, so we go a step further adding additional custom reports and monitoring to supplement Microsoft’s offerings, providing even deeper insights.

Identifying Root Causes in Microsoft Fabric

When issues arise, pinpointing the precise root cause is essential:

  • Microsoft Fabric Capacity Metrics app: We leverage this app extensively to start our diagnosis, pinpointing areas that require deeper investigation.

  • User Activity Analysis: Using the Power BI Activity Events API, we dive deep into user-level behaviors to identify which reports and queries cause the greatest strain.

  • Semantic Model & Pipeline Performance: Our specialists analyze semantic model designs and pipeline structures to highlight inefficiencies or bottlenecks.

Optimizing your Capacity Strategy

Our approach includes:

  • User Education: Training sessions tailored to your teams to promote best practices and reduce unnecessary resource consumption.
  • Scaling and Reserved Capacity: Strategic advice on scaling your environment efficiently and leveraging reserved capacity to control costs.
  • Cost Efficiency through Pause/Resume: Implementing pause/resume strategies for non-critical workloads, significantly reducing your expenditure.
  • Effective Workload Separation: Structuring workloads strategically to prevent capacity overload and maintain optimal performance.

Read more about Microsoft Fabric

How Fabric unites your organization's data?

Exploring the deployment capabilities of Microsoft Fabric

Norrin recognized as a Microsoft Featured Partner

 

Could we help you with your Microsoft Fabric solutions? Contact us!


 

Chris Sutcliffe

With 20+ years in data and analytics and as Director at Norrin Thailand, I specialize in building and operating modern, cloud-based data platforms while developing cross-border delivery models that balance quality, cost efficiency, and scalability.

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