Microsoft Fabric is expanding the reach of Microsoft OneLake with two new mirroring capabilities: Mirrored Azure Monitor and Mirrored AWS Glue catalog. These previews make it easier to bring operational telemetry and tables from external catalogs into Fabric while minimizing data movement and integration complexity.
Bring more of your data estate into OneLake
Organizations manage data across clouds and platforms. As two examples, operational telemetry may live in Azure Monitor, and some lakehouse environments may use AWS Glue Data Catalog to organize Apache Iceberg tables stored in Amazon S3. Bringing these systems together traditionally requires custom ingestion pipelines, duplicate storage, and ongoing infrastructure management.
Fabric mirroring provides a simpler model: it connects to external systems and reflects data or metadata into OneLake and Fabric experiences, helping teams analyze information across platform boundaries.
Mirror your Azure Monitor data into Fabric
Mirrored Azure Monitor brings tables from Log Analytics workspaces into OneLake without duplicating the operational data. It connects OneLake to the Log Analytics storage used by Azure Monitor, allowing teams to combine telemetry with business data already available in OneLake.
This creates opportunities for:
- Operational analytics across application and infrastructure signals.
- Cross-domain reporting that connects service health with business outcomes.
- Real-time intelligence scenarios using KQL.
- AI-powered reasoning across operational and business data.
Because the data remains governed by Azure Monitor and is accessed without replication, teams can avoid building a second ingestion and storage path merely to analyze telemetry in Fabric.
Bring Iceberg tables from AWS Glue into OneLake
Mirrored AWS Glue catalog is designed for organizations that use AWS Glue Data Catalog for their Apache Iceberg tables backed by AWS S3. Users connect OneLake to AWS Glue, select supported Iceberg tables, and have their Iceberg tables automatically show up in OneLake for use in Fabric.
The experience is intended to enable:
- Unified discovery of Glue-cataloged Iceberg data with other OneLake data.
- Faster onboarding of cataloged data into Fabric analytics experiences.
- Cross-cloud analysis using Fabric workloads such as Power BI, Data Warehousing, Data Engineering, and Data Science.
The underlying data remains in its existing storage location, while Fabric uses mirrored metadata and OneLake shortcuts to make supported Iceberg tables available across the platform.
Open by design
These capabilities continue Microsoft’s commitment to open data architectures and cross-platform interoperability. The mirrored catalog feature establishes a metadata-based, zero-copy pattern for bringing external catalog-managed data into OneLake. Mirrored AWS Glue catalog and Mirrored Azure Monitor extends the mirrored catalog approach to additional providers and environments.
Get started
Refer to the following steps to try out mirroring for these new sources today!
Mirrored Azure Monitor
To set up mirroring for your Azure Monitor tables from your Log Analytics workspace:
- Create a new Mirrored Azure Monitor item in Fabric.
- Connect it to a supported Log Analytics workspace.
- Select the tables you want to make available.
- Start exploring and analyzing the mirrored tables using Fabric experiences.
Check out the Mirror Azure Monitor in Microsoft Fabric (preview) documentation for more guidance.
Mirrored AWS Glue catalog
To set up mirroring for Iceberg tables from your AWS Glue catalog:
- Create a new Mirrored AWS Glue catalog item in Fabric.
- Connect to AWS Glue Data Catalog using a supported authentication method.
- Select the Iceberg tables you’d like to mirror into OneLake.
- Start exploring and analyzing the mirrored tables using Fabric experiences.
Check out the Mirrored AWS Glue catalog (preview) documentation for more information.
Mirrored Azure Monitor and Mirrored AWS Glue catalog help bring more of your data estate into OneLake, reducing the complexity of traditional integration projects and making it easier to work across operational, business, and cross-cloud data.
We want your feedback!
Try the previews today! Share your feedback through the Fabric Ideas site and Microsoft Fabric Community!