{"data":[{"active":true,"blog_title":"Configurable Data Retention in Microsoft Fabric Warehouse (Preview)","blog_url":"https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Configurable-Data-Retention-in-Microsoft-Fabric-Warehouse/ba-p/5181211","feature_description":"Ability to configure retention between 1 to 30 days","feature_name":"Configurable Retention between 1-120 days","last_modified":"2026-06-16","product_id":"fa3a73cd-dcd6-ee11-9079-000d3a310f67","product_name":"Data Warehouse","release_date":"Q2 2027","release_item_id":"c13c3e13-0d22-f011-998a-0022480939f0","release_status":"Shipped","release_type":"Public preview"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"Data engineers encounter challenges when constructing metadata-driven workflows due to the need to establish multiple connections for diverse data source endpoints. Currently, existing connections lack the capability for dynamic referencing. To address this, we are introducing connections as a workspace item that will consolidate the connections Role Based Access Contro l(RBAC) with workspace. This feature will facilitate dynamic referencing in connections, thereby enhancing flexibility and efficiency in metadata-driven workflows.","feature_name":"Connections - Enabling customers to parameterize their connections","last_modified":"2026-06-16","product_id":"a821f83f-dbd6-ee11-9079-000d3a310f67","product_name":"Data Factory","release_date":"Q4 2026","release_item_id":"cdc7d144-f9d6-ee11-9079-000d3a310f67","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"OneLake security (Preview)","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/onelake-security-is-now-available-in-public-preview","feature_description":"OneLake malware protection helps secure your data by automatically scanning files for malicious content when they're uploaded. It surfaces alerts and scan results for further action, providing built-in protection for enterprise data without requiring additional infrastructure.","feature_name":"OneLake malware scanning","last_modified":"2026-06-16","product_id":"338c69fe-dcd6-ee11-9079-000d3a310f67","product_name":"OneLake","release_date":"Q4 2026","release_item_id":"b99f2796-064f-f111-bec7-000d3a36696c","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Unlock Real-Time Intelligence with the Eventhouse Endpoint for Lakehouse","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/unlock-real-time-intelligence-with-the-eventhouse-endpoint-for-lakehouse","feature_description":"Lakehouse Streaming Tables bring real-time data processing and analytics to the Fabric Real Time hub, making it easier for data engineers and data scientists to discover, explore, and act on streaming data - all in one central location. With seamless integration to Spark and AI Skills, users can filter, open, and endorse streaming tables, and launch advanced analytics experiences. This feature is designed to boost engagement and productivity by providing instant access to continuously updated data, supporting rapid insights and decision-making for modern data teams.","feature_name":"Lakehouse Streaming Tables in the Real Time hub","last_modified":"2026-06-16","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q4 2026","release_item_id":"a9abe16a-7faf-f011-bbd3-000d3a3740cc","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"New Solace PubSub+ Connector: seamlessly connect Fabric Eventstream with Solace PubSub+ (Preview)","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/new-solace-pubsub-connector-seamlessly-connect-fabric-eventstream-with-solace-pubsub-preview","feature_description":"Eventstream streaming connector source: Solace PubSub+","feature_name":"Eventstream streaming connector source: Solace PubSub+ GA","last_modified":"2026-06-16","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q4 2026","release_item_id":"953fb7bc-2ca6-f011-bbd3-000d3a5b0efa","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"Set a Time-to-Live (TTL) on your mirrored Azure Cosmos DB data in OneLake, independent of the TTL on your source container. Retain analytics history in OneLake longer than the source, or expire mirrored data sooner to control storage and meet retention policies. This brings retention parity with Azure Synapse Link, making it easier to migrate analytics workloads from Synapse Link to Fabric Mirroring.","feature_name":"Mirroring TTL","last_modified":"2026-06-16","product_id":"0e17459c-141b-f011-998a-00224804b6c3","product_name":"Cosmos DB","release_date":"Q4 2026","release_item_id":"854b6b48-174b-f111-bec7-6045bd00f506","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Cosmos DB in Microsoft Fabric and Cosmos DB Mirroring (Generally Available)","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/announcing-ga-of-cosmos-db-in-microsoft-fabric-and-cosmos-db-mirroring","feature_description":"Bring your Azure Cosmos DB for MongoDB data into Microsoft Fabric with Mirroring. Replicate your operational MongoDB data into OneLake in near real time and run analytics across it without ETL pipelines or impact to your transactional workload.","feature_name":"Cosmos DB Mirroring for MongoDB","last_modified":"2026-06-16","product_id":"0e17459c-141b-f011-998a-00224804b6c3","product_name":"Cosmos DB","release_date":"Q4 2026","release_item_id":"794b6b48-174b-f111-bec7-6045bd00f506","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Discover Fabric items across workspaces with the OneLake Catalog Search API, MCP and CLI tools (Preview)","blog_url":"https://blog.fabric.microsoft.com/en-US/blog/discover-fabric-items-across-workspaces-with-the-onelake-catalog-search-api-mcp-and-cli-tools-preview","feature_description":"As part of Skills for Fabric, AI coding assistants like GitHub Copilot can discover Fabric items and tables. Developers can find existing, governed data before writing code, enabling a "find before you build" workflow that bridges AI tools and Fabric's enterprise data platform.","feature_name":"Find Fabric items and tables from Copilot CLI with OneLake Catalog","last_modified":"2026-06-16","product_id":"796a0af7-2dc7-ee11-9079-000d3a3419a8","product_name":"Administration, Governance and Security","release_date":"Q4 2026","release_item_id":"6754378c-e14a-f111-bec7-6045bd0a8ec1","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"Take the formatting on an individual visual and add it to the custom report theme for re-use on other visuals in the same report or a new report.","feature_name":"Add to preset for Power BI visuals","last_modified":"2026-06-16","product_id":"642a8375-05fc-ee11-a1ff-000d3a341a60","product_name":"Power BI","release_date":"Q4 2026","release_item_id":"e326538e-d31f-f111-8341-6045bd0a8ec1","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"Organizational themes (preview) allow Power BI administrators to centrally manage and distribute custom report themes across the organization. Maintaining a consistent visual identity across Power BI reports is now simpler and more scalable, thanks to organizational themes. Whether reports are built manually or generated with Copilot, this feature ensures that styling and branding stay aligned with your organization's identity and design standards.","feature_name":"Organizational themes for Power BI reports","last_modified":"2026-06-16","product_id":"642a8375-05fc-ee11-a1ff-000d3a341a60","product_name":"Power BI","release_date":"Q4 2026","release_item_id":"6cda5cd3-d31f-f111-8341-6045bd0a8ec1","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":"How Spark Supports OneLake Security with Row and Column Level Policies","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/how-spark-supports-onelake-security-with-row-and-column-level-security-policies","feature_description":"OneLake Security supports Dynamic Row-Level Security (RLS), so each user sees only the rows that match their identity. This work brings Spark on Fabric into parity with that capability: Spark queries against tables protected by a Dynamic RLS role correctly return only the rows the calling user is allowed to see.With this release, Security Admins can define a single set of Dynamic RLS roles in OneLake Security and have those policies enforced uniformly across Spark, T-SQL, and Power BI. Existing Dynamic RLS roles defined in OneLake Security start working for Spark notebooks and jobs without any policy or query changes. Customers no longer have to choose between Dynamic RLS and Spark access for the same dataset.","feature_name":"Dynamic RLS support in Spark","last_modified":"2026-06-16","product_id":"a731518f-36ca-ee11-9079-000d3a341a60","product_name":"Data Engineering","release_date":"Q3 2026","release_item_id":"ff6d38a5-4a4d-f111-bec6-6045bd00f798","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Enhanced Monitoring for Spark High Concurrency Workloads in Microsoft Fabric","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/enhanced-monitoring-for-spark-high-concurrency-workloads-in-microsoft-fabric","feature_description":"This feature is designed to visualize real-time metrics for Spark applications through a dashboard that allows users to monitor CPU and memory utilization at the application level for both executors and drivers, across running and completed applications. It aligns with the Fabric SaaS offering and extends Spark vCore allocation and utilization analysis. Additional details about user scenarios are available in the discussion.","feature_name":"[Monitoring] Integrate and Expose Spark Application CPU/Memory Usage","last_modified":"2026-06-16","product_id":"a731518f-36ca-ee11-9079-000d3a341a60","product_name":"Data Engineering","release_date":"Q3 2026","release_item_id":"fe489766-3350-f111-bec7-6045bd00fc61","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"Currently the largest message size Eventstream can support is 1MB. This new feature will push this limit to bigger size to meet broader requirements.","feature_name":"Eventstream supports large message size","last_modified":"2026-06-16","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q3 2026","release_item_id":"fc3ce8fd-6e2f-f011-8c4d-000d3a34671f","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Dataflow Gen2: Dataflow Diagnostics Download (Preview)","blog_url":"https://blog.fabric.microsoft.com/en-US/blog/dataflow-gen2-dataflow-diagnostics-download-preview","feature_description":"We plan to make Diagnostics Download in Dataflow Gen2 generally available, providing a production-ready way to capture and share detailed runtime diagnostics for dataflow executions.Moving this feature to GA means it is ready for production usage, with consistent behavior, reliability, and support suitable for business-critical data pipelines.Key benefits and scenarios:* Download run-level diagnostic packages including execution details and runtime metadata* Speed up troubleshooting, root-cause analysis, and performance investigations* Enable easier collaboration between data teams, administrators, and Microsoft support using standardized diagnostic artifactsBy taking Diagnostics Download to GA, we're strengthening observability and supportability for Dataflow Gen2, making it easier to operate, troubleshoot, and trust dataflows at production scale.","feature_name":"Dataflows - Dataflow Diagnostics Download","last_modified":"2026-06-16","product_id":"a821f83f-dbd6-ee11-9079-000d3a310f67","product_name":"Data Factory","release_date":"Q3 2026","release_item_id":"f98cc7d2-5834-f111-88b4-6045bd00f506","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":"From repetition to reuse: accelerate data prep with My queries in Dataflow Gen2","blog_url":"https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/From-repetition-to-reuse-accelerate-data-prep-with-My-queries-in/ba-p/5176763","feature_description":"Shared Queries in Dataflow Gen2 will be available in Preview, enabling users to save commonly used Power Query transformations within a Fabric workspace, share and reuse them across multiple dataflows and collaborators.This preview extends the reuse-first authoring model to teams, making it easy to apply trusted, reusable logic--such as data cleansing steps, business rules, or standard joins--consistently across projects without rebuilding queries from scratch.Key benefits and scenarios:* Share common transformation logic across workspace members to accelerate team-wide development* Promote consistency and standardization of data preparation patterns across dataflows* Reduce duplication and improve maintainability by centralizing reusable query logic* Enable faster onboarding and collaboration when multiple authors work with similar source systemsDuring Preview, Shared Queries is intended for experimentation and early team adoption, helping organizations validate collaborative transformation patterns and provide feedback as we continue evolving the experience.","feature_name":"Dataflows - Shared Queries","last_modified":"2026-06-16","product_id":"a821f83f-dbd6-ee11-9079-000d3a310f67","product_name":"Data Factory","release_date":"Q3 2026","release_item_id":"f8f739d4-b850-f111-bec7-6045bd0a8ec1","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Create Metadata Driven Data Pipelines in Microsoft Fabric","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/create-metadata-driven-data-pipelines-in-microsoft-fabric","feature_description":"A commonly used functionality in ADF is configuring a Pipeline to run when a set of dependencies are met. We are excited to bring this functionality to Data Pipelines in Data Factory in Fabric to continue enriching orchestration capabilities.","feature_name":"Pipelines - Run Pipeline when dependencies are met","last_modified":"2026-06-16","product_id":"a821f83f-dbd6-ee11-9079-000d3a310f67","product_name":"Data Factory","release_date":"Q3 2026","release_item_id":"f8636911-7191-ef11-ac21-002248098a98","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"To enhance security, we aim to prevent the sharing of Microsoft account credentials across collaborators. The new connection-sharing model will encourage each collaborator to sign in with their own Microsoft account.","feature_name":"Connections - Enhanced Connection Collaboration Model","last_modified":"2026-06-16","product_id":"a821f83f-dbd6-ee11-9079-000d3a310f67","product_name":"Data Factory","release_date":"Q3 2026","release_item_id":"f3579085-8c20-f011-998a-0022480939f0","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Announcing preview of Workspace Monitoring","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/announcing-public-preview-of-workspace-monitoring","feature_description":"This feature delivers a comprehensive Spark Workspace Monitoring experience, enabling administrators and data engineers to gain full visibility into workspace-level Spark activity. Users can view and analyze live and historical job executions, filter and drill into specific runs, and compare performance across Fabric items.With direct access to Spark diagnostic logs and metrics via Kusto Query Language (KQL), users can create custom queries, perform advanced aggregations, and build their own dashboards, unlocking powerful, flexible insights for monitoring, troubleshooting, and optimization.","feature_name":"Spark Workspace Monitoring v1","last_modified":"2026-06-16","product_id":"a731518f-36ca-ee11-9079-000d3a341a60","product_name":"Data Engineering","release_date":"Q3 2026","release_item_id":"f0f360ab-3350-f111-bec7-6045bd00fc61","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Running Apache Airflow jobs seamlessly in Microsoft Fabric","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/running-apache-airflow-jobs-seamlessly-in-microsoft-fabric","feature_description":"Fabric Apache Airflow jobs provides a SaaS way to build Python-based Airflow DAGs in your Fabric workspace. With this new feature, you will now be able to easily view your runtime logs from Apache Airflow in the Fabric Workspace Monitoring view to build your own queries, reports, and dashboards.","feature_name":"Airflow - Workspace Monitoring to include Apache Airflow logs from Airflow Job","last_modified":"2026-06-16","product_id":"a821f83f-dbd6-ee11-9079-000d3a310f67","product_name":"Data Factory","release_date":"Q3 2026","release_item_id":"ef14c40e-0a6f-f011-bec2-00224804b6c3","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Boost performance and save costs with Fast Copy in Dataflows Gen2","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/boost-performance-and-save-costs-with-fast-copy-in-dataflows-gen2","feature_description":"The option to disable V-Order (VertiParquet) compression in Dataflow Gen2 will become generally available, giving customers greater control over performance and storage optimization trade-offs for supported workloads and destinations.This capability enables advanced users to reduce processing overhead associated with V-Order compression during writes, helping improve refresh throughput and lower write latency for large-scale or time-sensitive ingestion and transformation scenarios.With this release, organizations can better tune Dataflow Gen2 execution behavior to align with the performance requirements of their Fabric architectures while continuing to benefit from the scalability and flexibility of Microsoft Fabric data transformation workflows.","feature_name":"Dataflows - Performance: Disable V-Order Compression","last_modified":"2026-06-16","product_id":"a821f83f-dbd6-ee11-9079-000d3a310f67","product_name":"Data Factory","release_date":"Q3 2026","release_item_id":"eed6fd49-4461-f111-a826-000d3a376137","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":"Inline Scalar user-defined functions (UDFs) in Microsoft Fabric Warehouse (Preview)","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/inline-scalar-user-defined-functions-udfs-in-microsoft-fabric-warehouse-preview","feature_description":"We're expanding scalar user-defined functions with new capabilities, including INLINE = AUTO, improved error messaging, support for special built-in functions, and CONTINUE/BREAK statements in **computation**-based UDFs.","feature_name":"Scalar User-defined functions (UDFs)","last_modified":"2026-06-16","product_id":"fa3a73cd-dcd6-ee11-9079-000d3a310f67","product_name":"Data Warehouse","release_date":"Q3 2026","release_item_id":"edb33b5b-7f5d-f011-bec2-0022480939f0","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"JMS source connector for another message broker type.","feature_name":"JMS source connector","last_modified":"2026-06-16","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q3 2026","release_item_id":"eb22e174-8e3f-f111-88b5-6045bd00f798","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"How Spark Supports OneLake Security with Row and Column Level Policies","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/how-spark-supports-onelake-security-with-row-and-column-level-security-policies","feature_description":"OneLake is adding support for multi-table Row-Level Security (RLS) to OneLake security. This allows users to define security for one table based on values of columns in another table. This is commonly used for filtering scenarios such as restricting sales data based on assigned stores or regions.This work item adds the necessary functionality to the Spark workload so that multi-table RLS policies can be defined and enforced. For workloads using the RLS bitmaps, the implementation requires testing and validation work to ensure correct enforcement during scan execution.","feature_name":"OneSecurity multi-table RLS support in Spark","last_modified":"2026-06-16","product_id":"a731518f-36ca-ee11-9079-000d3a341a60","product_name":"Data Engineering","release_date":"Q3 2026","release_item_id":"e54fa8e7-494d-f111-bec6-000d3a376c0f","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Announcing Shortcut Transformations: from files to Delta tables. Always in sync, no pipelines required.","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/announcing-shortcut-transformations-from-files-to-delta-tables-always-in-sync-no-pipelines-required","feature_description":"Shortcut Transformations let you transform files to tables. With the instroduction of Content Understanding transform you can make any file a table.","feature_name":"Shortcut Transformations - file to table (content understanding)","last_modified":"2026-06-16","product_id":"338c69fe-dcd6-ee11-9079-000d3a310f67","product_name":"OneLake","release_date":"Q3 2026","release_item_id":"ded7f959-0cc0-f011-bbd3-00224808fcf0","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Announcing the General Availability of Enhanced Eventstream and Connector Sources","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/announcing-the-general-availability-of-enhanced-eventstream-and-connector-sources","feature_description":"**Add Data Source Connector for Business Events in Real-Time Hub****Overview**Enable seamless ingestion of Business Events into Real-Time hub Eventstream--making it easier to onboard event producers and unify event streams across systems.**Key Capabilities*** Native Data Source Connectivity: Connect external systems and Fabric workloads as event producers through a unified Real-Time hub experience.* Simplified Event Ingestion: Stream Business Events directly from connected data sources without requiring custom integration layers.* Schema-Aware Mapping: Map incoming data streams to standardized Business Event schemas to ensure consistency across producers and consumers.* Centralized Event Discovery: Surface all ingested Business Events in Real-Time hub for easy exploration, filtering, and subscription.* Seamless Integration with Downstream Consumers: Enable immediate consumption by Eventstream.","feature_name":"Add Data Source Connector for Business Events in Real-Time Hub","last_modified":"2026-06-16","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q3 2026","release_item_id":"ddd81a72-da3d-f111-88b5-6045bd0a8ec1","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":"Introducing the HTTP and MongoDB CDC Connectors for Eventstream \u2014 Inspired by You","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/introducing-the-http-and-mongodb-cdc-connectors-for-eventstream-inspired-by-you","feature_description":"The MongoDB CDC connector for Eventstream captures database changes from any MongoDB deployment, including MongoDB Atlas and self-managed instances on other cloud providers. These change events are streamed into Eventstream for real-time processing and analysis.","feature_name":"Eventstream connector: MongoDB CDC","last_modified":"2026-06-16","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q3 2026","release_item_id":"ddb75e86-23a6-f011-bbd3-000d3a5b0efa","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":"Capacity Scheduler: Smarter capacity control for Eventhouse (Preview)","blog_url":"https://blog.fabric.microsoft.com/en-US/blog/capacity-scheduler-smarter-capacity-control-for-eventhouse-preview","feature_description":"Capacity Operation Events Public Preview","feature_name":"Capacity Operation Events Public Preview","last_modified":"2026-06-16","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q3 2026","release_item_id":"dc8a0aee-e3c0-f011-bbd3-000d3a5b0efa","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Easily load Fabric OneLake data into Excel \u2014 OneLake catalog and Get Data are integrated into Excel for Windows (Preview)","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/easily-load-fabric-onelake-data-into-excel-onelake-catalog-and-modern-get-data-are-integrated-into-excel-for-windows-preview","feature_description":"The OneLake catalog integration in Excel as part of modern Get Data unlocks seamless connectivity to Fabric data, empowering every business user to discover and analyze organizational content directly from Excel. This powerful capability simplifies data access and accelerates insights, making Excel a true gateway to Fabric's rich data ecosystem.","feature_name":"Fabric OneLake catalog in Excel Get Data","last_modified":"2026-06-16","product_id":"796a0af7-2dc7-ee11-9079-000d3a3419a8","product_name":"Administration, Governance and Security","release_date":"Q3 2026","release_item_id":"d2e07536-32b3-f011-bbd3-00224808fcf0","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"**Publish Business Events Samples from Real-Time Hub****Overview**Enable users to quickly understand and adopt Business Events by publishing ready-to-use sample events directly from Real-Time hub--reducing setup time and accelerating onboarding to event-driven scenarios.**Key Capabilities*** One-click Sample Event Publishing: Publish pre-configured Business Events directly from Real-Time hub without needing custom code or setup.* Guided Sample Experiences: Provide curated examples that demonstrate common scenarios (e.g., anomaly detection, order processing, operational signals).* Integrated Publisher Setup: Seamlessly configure publishers (Eventstream, Notebooks, UDFs) from within Real-Time hub to start emitting events instantly.* Schema-Aligned Samples: Ensure all samples follow standardized Business Event schemas, helping users learn best practices while building.* End-to-End Scenario Validation: Allow users to validate event flows--from publishing to consumption--using sample data before integrating real workloads.","feature_name":"Publish Business Events Samples from Real-Time Hub","last_modified":"2026-06-16","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q3 2026","release_item_id":"d0437aab-da3d-f111-88b5-6045bd0a8ec1","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":"Workspace-Level Private Link in Microsoft Fabric (Generally Available)","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/announcing-general-availability-of-workspace-level-private-link-in-microsoft-fabric","feature_description":"Private Link enables secure, private connectivity between your virtual network and Microsoft Fabric, eliminating exposure to the public internet. With Eventstream's integration with Workspace Private Link, you gain granular access control at the workspace level enhancing data security by minimizing the risk of unauthorized access and potential data breaches.","feature_name":"Workspace Private Link for Eventstream's Select Sources & Destinations","last_modified":"2026-06-16","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q3 2026","release_item_id":"cde82016-24a6-f011-bbd3-000d3a5b0efa","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":"Introducing the HTTP and MongoDB CDC Connectors for Eventstream \u2014 Inspired by You","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/introducing-the-http-and-mongodb-cdc-connectors-for-eventstream-inspired-by-you","feature_description":"With a built-in Dataverse connectors to Eventstream, users  find it easy to discover the Dataverse tables of interest and enable change events on those tables in RTI with the GetEvents UX. It transform the raw events into a easily consumable form - Instead of having to process complex, deeply nested JSON objects, users will find it easy to build applications on change records that reflect the shape/schema of the Dataverse source table.","feature_name":"Route Dataverse data events to Eventstream","last_modified":"2026-06-16","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q3 2026","release_item_id":"cb7b0382-4fb8-ef11-b8e9-002248098a98","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Public APIs \u2013 bulk import and export items definition (Preview)","blog_url":"https://blog.fabric.microsoft.com/en-US/blog/public-apis-bulk-import-and-export-items-definition-preview","feature_description":"Import and export item definitions in bulk through a single API call. 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Query folding indicators that surface which steps are folding back to the source. 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