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Microsoft Fabric Updates Blog

  1. 更新
  2. 7月 2023

Free preview usage of Microsoft Fabric workloads extended to October 1, 2023

On June 1, 2023, we announced the availability of Microsoft Fabric preview capacity for purchase within the Azure portal. At that time, we communicated that Fabric workloads other than Power BI would not accrue against your purchased capacity limits and that you would have visibility in the capacity metrics app to your preview vs. paid usage until August 1.

We are now extending the free preview usage of Fabric workloads (other than Power BI), and these workloads will not count against purchased capacity until October 1, 2023.

Learn more about Fabric capacities in the original June 1 blog post. 

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Free preview usage of Microsoft Fabric workloads extended to October 1, 2023

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Expanding Real-Time Intelligence data sources with Cribl source (Preview)
1月 20, 2026 作者： Xu Jiang

The exchange of real-time data across different data platforms is becoming increasingly popular. The Cribl source (preview) is now available in Real-Time Intelligence, allowing real-time data to flow into Fabric RTI Eventstream through our collaboration with Cribl, enabling you to take full advantage of Fabric Real-Time Intelligence’s robust analytics tools for their real-time needs. Collaborating to broaden … Continue reading “Expanding Real-Time Intelligence data sources with Cribl source (Preview)”

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部落格的精選影像

Simplifying data movement across multiple clouds with Copy job – Enhancements on incremental copy and change data capture
1月 20, 2026 作者： Ye Xu

Copy job is the go-to solution in Microsoft Fabric Data Factory for simplified data movement, whether you’re moving data across clouds, from on-premises systems, or between services. With native support for multiple delivery styles, including bulk copy, incremental copy, and change data capture (CDC) replication, Copy job offers the flexibility to handle a wide range … Continue reading “Simplifying data movement across multiple clouds with Copy job – Enhancements on incremental copy and change data capture”

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