{"data":[{"active":true,"blog_title":null,"blog_url":null,"feature_description":"Fabric feature store is a centralized system that manages the data inputs, called features, that power machine learning models. It bridges raw data and ML models, giving teams one place to define, store, serve, and discover features instead of each team building its own pipelines.","feature_name":"Feature Store","last_modified":"2026-08-11","product_id":"0522b590-dcd6-ee11-9079-000d3a310f67","product_name":"Data Science","release_date":"Q4 2026","release_item_id":"75004e12-2158-f111-bec7-6045bd00f798","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"Quickly identify when and where throttling is occurring across your Eventhouse system. This feature highlights recent throttling events, helping you diagnose performance bottlenecks and take corrective action before they impact users.","feature_name":"show Throttling events of eventhouse at Eventhouse WS monitoring","last_modified":"2026-08-05","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q4 2026","release_item_id":"2d60a7e8-b555-f011-877a-00224804ca88","release_status":"Planned","release_type":"Public preview"},{"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":"This feature enables customers to develop or reuse their own Kafka connectors, or open-source Kafka connectors, when no pre-built streaming connector is available.With this capability, you can:- Customize your own connector at your own pace.- Run with no infrastructure to manage.- Reuse open-source connectors directly.","feature_name":"Eventstream supports customers to upload own connector","last_modified":"2026-08-05","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q3 2026","release_item_id":"60246c0e-762f-f011-8c4d-000d3a34671f","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"Branch workspace admin profile (aka. admin delegation) lets developers use the branch-out experience without needing create-workspace or assign-capacity permissions. Workspace admins keep full control through pre-configured guardrails while unblocking developer workflows. Capabilities:  - Developers without create-workspace or assign-capacity permissions can perform branch-out seamlessly  - Admins pre-configure profile to ensure guardrails for branch workspaces: developer role, capacity assignment and admin list.","feature_name":"Git Integration - Branch workspace admin profile","last_modified":"2026-08-03","product_id":"c6da6b3b-ded6-ee11-9079-000d3a310f67","product_name":"Fabric Developer Experiences","release_date":"Q3 2026","release_item_id":"79538350-662c-f111-88b4-6045bd0a886d","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"List slicer with drop down mode and advanced search options.","feature_name":"List slicer with dropdown mode","last_modified":"2026-07-31","product_id":"642a8375-05fc-ee11-a1ff-000d3a341a60","product_name":"Power BI","release_date":"Q4 2026","release_item_id":"ba851f2d-d21f-f111-8341-6045bd0a8ec1","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":"Announcing Data Clustering in Fabric Data Warehouse (Preview)","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/announcing-data-clustering-in-fabric-data-warehouse-preview","feature_description":"Data Clustering enables faster read performance by allowing users to specify columns for co-locating data on ingestion and perform file skipping on read.","feature_name":"Data Clustering","last_modified":"2026-07-30","product_id":"fa3a73cd-dcd6-ee11-9079-000d3a310f67","product_name":"Data Warehouse","release_date":"Q4 2026","release_item_id":"5cd4b9a0-1322-f011-998a-0022480939f0","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":"Mastering Declarative Data Transformations with Materialized Lake Views","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/mastering-declarative-data-transformations-with-materialized-lake-views","feature_description":"Fabric data engineers today write 80-100+ lines of boilerplate PySpark to ingest CSV and Parquet files into Delta tables - handling file discovery, schema inference, incremental refresh, schema drift, and error recovery manually. This feature introduces a simple Spark SQL DDL surface (CREATE MATERIALIZED LAKE VIEW ... FROM OneLake_Files OPTIONS (...)) that declaratively handles all of this. It includes automatic schema evolution (or strict fixed-schema mode), three refresh modes (append_only, mirror, full), built-in error handling, structured user telemetry on files and lakehouse-level DAG lineage.","feature_name":"Declarative file data ingestion experience in Fabric Materialized Lake Views","last_modified":"2026-07-30","product_id":"a731518f-36ca-ee11-9079-000d3a341a60","product_name":"Data Engineering","release_date":"Q3 2026","release_item_id":"14254506-0f3f-f111-88b5-6045bd00f798","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Time-Travelling through data: The Magic of Table clones","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/time-travelling-through-data-the-magic-of-table-clones","feature_description":"Ability to clone warehouse across workspaces","feature_name":"Warehouse Clones","last_modified":"2026-07-29","product_id":"fa3a73cd-dcd6-ee11-9079-000d3a310f67","product_name":"Data Warehouse","release_date":"Q1 2027","release_item_id":"e240d768-fc21-f011-998a-0022480939f0","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Introducing the New Deployment Pipelines design: A leap forward in deployment Efficiency","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/introducing-the-new-deployment-pipelines-design-a-leap-forward-in-deployment-efficiency","feature_description":"**Release:** Public Preview  |  **Product area:** Fabric CI/CD**Deployment plan** is a new first-class Fabric workspace item that lets you **define, order, and automate** how your content is deployed across environments.Instead of relying on system-inferred lineage order, you author a plan on a **visual canvas** (with **YAML as the source of truth**) to:- **Declare the exact sequence** in which items deploy- **Add pre and post deployment steps** -- for example, running a Notebook to hydrate a Lakehouse, or a Data Pipeline before dependent items go liveDeployment plans **attach to the deployment operations available in Fabric**, including **Git** (branch-out, initial sync, update from Git), **Deployment Pipelines**, **Bulk Import**, and the **CI/CD library**, and are **honored at deploy time**.The result: every promotion follows your intended orchestration and produces a **working, reproducible solution**, not just a set of deployed definitions.","feature_name":"Deployment Plan","last_modified":"2026-07-29","product_id":"c6da6b3b-ded6-ee11-9079-000d3a310f67","product_name":"Fabric Developer Experiences","release_date":"Q4 2026","release_item_id":"fbee65ff-2b8b-f111-ab0f-6045bd03ee11","release_status":"Planned","release_type":"Public preview"},{"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 the data warehouse retention between 1 to 120 days;","feature_name":"Configurable Retention between 1-120 days","last_modified":"2026-07-29","product_id":"fa3a73cd-dcd6-ee11-9079-000d3a310f67","product_name":"Data Warehouse","release_date":"Q4 2026","release_item_id":"dfb17dba-0d22-f011-998a-0022480939f0","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":"Data Warehouse Utilization Reporting in Fabric Capacity Metrics App","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/data-warehouse-utilization-reporting-in-fabric-capacity-metrics-app","feature_description":"Shortcuts in Fabric DW allow users to directly access and query data that is present in internal and external data sources, without loading them into Fabric DW. Users will have the capability to create Table Shortcuts via TSQL & UX","feature_name":"Shortcuts in Fabric Data Warehouse (Public Preview)","last_modified":"2026-07-29","product_id":"fa3a73cd-dcd6-ee11-9079-000d3a310f67","product_name":"Data Warehouse","release_date":"Q4 2026","release_item_id":"ce7f2f21-9421-f011-9989-000d3a302e4a","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Resolving Write Conflicts in Microsoft Fabric Data Warehouse","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/concurrency-control-and-conflict-resolution-in-microsoft-fabric-data-warehouse","feature_description":"This feature is part of the concurrency control strategy for Fabric DW. File-level write-write conflict detection is a mechanism designed to prevent two concurrent transactions from modifying the same physical file in a data warehouse at the same time. More precise than table-level detection (which blocks any concurrent changes to the same table).What It Does?Scope: Operates at the file level (e.g., Parquet files in Fabric DW), rather than at the table or row level.Goal: Detect overlapping changes (updates, deletes) to the same file during concurrent transactions.Trigger: When a transaction tries to commit changes, the system checks if any newer manifests indicate modifications to the same file since the transaction started.Lays groundwork for even finer-grained detection (row-level) in later releases.","feature_name":"File-Level write-write conflict detection (Generally Available)","last_modified":"2026-07-29","product_id":"fa3a73cd-dcd6-ee11-9079-000d3a310f67","product_name":"Data Warehouse","release_date":"Q4 2026","release_item_id":"b7e155c6-94bf-f011-bbd3-000d3a5b0efa","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":"Large string and binary values in Fabric Data Warehouse and SQL analytics endpoint for mirrored items (Generally Available)","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/large-string-and-binary-values-in-fabric-data-warehouse-and-sql-analytics-endpoint-for-mirrored-items-general-availability","feature_description":"SQL analytics endpoints of Lakehouses will support large string and binary data using VARCHAR(MAX) and VARBINARY(MAX) types up to 16 MB.","feature_name":"VARCHAR(MAX) support in SQL analytics endpoint of Lakehouses","last_modified":"2026-07-29","product_id":"fa3a73cd-dcd6-ee11-9079-000d3a310f67","product_name":"Data Warehouse","release_date":"Q3 2026","release_item_id":"f4c0ce02-2e61-f011-bec2-000d3a302e4a","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 allows customers to connect to their SQL DBs via a private endpoint from the customer's virtual network. Workspace level private links will give customers the flexibility to use private link connection to specific workspace(s) which have high security requirements and contain sensitive data while their other workspace can be open to public.","feature_name":"Workspace level Private Link for SQL database","last_modified":"2026-07-29","product_id":"347da228-ea54-ef11-a317-0022480a694f","product_name":"SQL database","release_date":"Q3 2026","release_item_id":"744ac485-321d-f011-9989-000d3a302e4a","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"The OpenAI Assistants API that powers the orchestration layer for the Microsoft Fabric data agent is currently scheduled to be shut down by OpenAI on August 26, 2026. After that date, direct calls to the Assistants API will stop working. We are migrating the Data Agent UX and Programmatic experiences to the Responses API","feature_name":"Data Agent Migration to Responses API","last_modified":"2026-07-27","product_id":"951b64e0-a663-f111-a826-6045bd00f798","product_name":"Conversational Analytics","release_date":"Q3 2026","release_item_id":"e9e7c616-d289-f111-ab0f-6045bd03e6d8","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"This feature delivers a comprehensive Notebook Run Lineage experience for Spark applications, enabling data engineers to monitor and analyze complex notebook workflows with ease. It provides an at-a-glance view of all notebook run statuses, helps quickly identify root-cause failures across nested executions, and highlights performance bottlenecks. Users can filter and explore large execution graphs, access detailed error and run-level information, and view aggregated summaries of execution health and resource usage--all in one place.","feature_name":"Track and Manage Notebook Run Dependencies & Linage View","last_modified":"2026-07-27","product_id":"a731518f-36ca-ee11-9079-000d3a341a60","product_name":"Data Engineering","release_date":"Q3 2026","release_item_id":"71469140-3550-f111-bec7-6045bd00fc61","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Fabric Runtime Release Channels","blog_url":"https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Fabric-Runtime-Release-Channels/ba-p/5240330","feature_description":"This feature enables multiple runtime channels for customers. The default channel will remain the current standard runtime, while an EarlyAccess channel will provide the latest updates - such as library upgrades and security vulnerability fix..Using Spark configuration, customers can test and validate these changes early, before they become part of the default runtime channel.","feature_name":"Synapse Release Channel - Public Preview","last_modified":"2026-07-27","product_id":"a731518f-36ca-ee11-9079-000d3a341a60","product_name":"Data Engineering","release_date":"Q3 2026","release_item_id":"3665d185-5b43-f111-88b5-6045bd0a886d","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":"Eventstream now provides a Salesforce change data capture source connector, streaming record changes from Salesforce into Microsoft Fabric. Teams can react to business changes as they happen.With this capability, you can:- Stream Salesforce record changes into Eventstream in real time.- Build dashboards and alerts on customer and sales activity.- Route Salesforce changes to Fabric destinations without custom code.","feature_name":"Salesforce change data capture source connector","last_modified":"2026-07-23","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q1 2027","release_item_id":"f661c4f7-8d3f-f111-88b5-6045bd00f798","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"New Eventstream sources: MQTT, Solace PubSub+, Azure Data Explorer, Weather & Azure Event Grid","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/new-eventstream-sources-mqtt-solace-pubsub-azure-data-explorer-weather-event-grid","feature_description":"The Azure Data Explorer source connector for Eventstream extends ingestion limits and adds streaming from a custom query, so you can bring Azure Data Explorer data into Microsoft Fabric for further real-time processing.With this capability, you can:- Stream data from Azure Data Explorer into Eventstream.- Use a custom query to select the data you ingest.- Route results to Fabric destinations for downstream analytics.","feature_name":"Azure Data Explorer source connector for Eventstream","last_modified":"2026-07-23","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q1 2027","release_item_id":"34fee3ee-8e3f-f111-88b5-6045bd00f798","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":"Mirroring for Google BigQuery in Microsoft Fabric (Preview)","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/announcing-public-preview-mirroring-for-google-bigquery-in-microsoft-fabric","feature_description":"Mirroring for Google BigQuery enables customers to continuously replicate BigQuery data into Fabric OneLake, making it easier to use BigQuery data with Power BI, data engineering, data science, and AI experiences in Fabric. Customers can bring data from Google BigQuery into the Fabric analytics estate without maintaining separate ETL pipelines for common replication scenarios.","feature_name":"Mirroring - Google BigQuery","last_modified":"2026-07-23","product_id":"a821f83f-dbd6-ee11-9079-000d3a310f67","product_name":"Data Factory","release_date":"Q3 2026","release_item_id":"e64919b9-5163-f111-a826-000d3a36696c","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"Build Agent with AI mode is expanding support for Semantic Models in Data Agent, helping users generate semantic-model specific instructions and example queries more easily. The feature can explore Semantic Model tables, measures, columns, and recent query patterns to produce more relevant configurations while preserving transparency through visible run steps and explored queries. Users remain in control by reviewing, refining, and committing generated configurations before they update their Data Agent setup.","feature_name":"Build Agent with AI Mode: Support Semantic Models","last_modified":"2026-07-22","product_id":"951b64e0-a663-f111-a826-6045bd00f798","product_name":"Conversational Analytics","release_date":"Q3 2026","release_item_id":"df9398eb-fb68-f111-a826-6045bd0066ad","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"Data agents now have advanced DAX generation that more accurately generates queries from your natural-language questions. This update introduces instance value indexing and delivers higher response accuracy and consistency.","feature_name":"Advanced DAX Generation for Semantic Models in Data Agents","last_modified":"2026-07-22","product_id":"951b64e0-a663-f111-a826-6045bd00f798","product_name":"Conversational Analytics","release_date":"Q3 2026","release_item_id":"681eef41-b566-f111-a826-6045bd0066ad","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"Build Agent with AI Mode file support lets users upload existing text-based business context such as documentation, glossaries, process guides, and data dictionaries, so Creator Agent can use it to generate more complete and accurate Data Agent configurations. This reduces repetitive setup work by allowing users to reuse knowledge that already exists in files, rather than manually recreating that context through long chat interactions.","feature_name":"Build Agent with AI Mode Supports Files as Context","last_modified":"2026-07-22","product_id":"951b64e0-a663-f111-a826-6045bd00f798","product_name":"Conversational Analytics","release_date":"Q3 2026","release_item_id":"54678565-fb68-f111-a826-6045bd0066ad","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Creator Improvements in the Data Agent","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/creator-improvements-in-the-data-agent","feature_description":"The Build Agent with AI mode is a specialized AI assistant designed to help data agent creators configure, improve, and optimize their data agents by generating and refining Agent Instructions, Data Source Instructions, and Few-Shot Examples. It addresses common customer pain points such as confusion about where to put instructions, uncertainty about the effectiveness of few shots, and difficulty diagnosing why an agent produces poor results. The agent works in a collaborative, chat-based 'setup' mode, where it analyzes existing configurations, explores database schemas and query patterns, and recommends improvements that users can explicitly accept or reject. It is designed to detect ambiguity and contradictions across configurations and suggest clearer, more consistent alternatives. Initially focused on SQL data sources, the Build Agent with AI mode is intended to expand to additional data sources (e.g., KQL, semantic models) over time. Overall, it enables a faster, more scalable, and more understandable way to build high-quality data agents without requiring deep knowledge of the underlying system.","feature_name":"Build Agent with AI Mode in Data Agent","last_modified":"2026-07-22","product_id":"951b64e0-a663-f111-a826-6045bd00f798","product_name":"Conversational Analytics","release_date":"Q2 2026","release_item_id":"db90d1e4-cbf0-f011-8407-002248096d54","release_status":"Planned","release_type":"Public preview"},{"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":"2026-07-21","product_id":"fa3a73cd-dcd6-ee11-9079-000d3a310f67","product_name":"Data Warehouse","release_date":"Q4 2026","release_item_id":"edb33b5b-7f5d-f011-bec2-0022480939f0","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":"Announcing the Availability of REST APIs for Connections and Gateways in Microsoft Fabric","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/announcing-the-availability-of-rest-apis-for-connections-and-gateways-in-microsoft-fabric","feature_description":"New tenant admin REST APIs for end-to-end visibility and lifecycle management of all cloud connections in Microsoft Fabric -- list, get, delete, manage permissions/ take over.","feature_name":"Connections - Tenant Admin APIs for connections","last_modified":"2026-07-21","product_id":"a821f83f-dbd6-ee11-9079-000d3a310f67","product_name":"Data Factory","release_date":"Q3 2026","release_item_id":"79c8ba5e-fd3c-f111-88b5-6045bd00f798","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Supercharge your real-time data ingestion: What's new in Fabric Eventstream connectors","blog_url":"https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Supercharge-your-real-time-data-ingestion-What-s-new-in-Fabric/ba-p/5260314","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":"2026-07-17","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":"Acquiring Real-Time Data from New Sources with Enhanced Eventstream","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/acquiring-real-time-data-from-new-sources-with-enhanced-eventstream","feature_description":"**Eventstream as a Business Events Publisher from Real-Time Hub****Overview**Enable Eventstream to act as a native publisher of Business Events directly from Real-Time hub--simplifying event creation and allowing users to emit business signals from streaming data with minimal setup.**Key Capabilities*** Native Eventstream Publishing from Real-Time Hub: Create and configure Eventstream publishers directly from the Business Events experience in Real-Time hub.* Seamless Stream-to-Event Mapping: Map incoming data streams to Business Event schemas using built-in mappers to transform raw signals into meaningful business events.* Low-Code Publisher Configuration: Configure publishing logic through UI-driven experiences without requiring custom code or complex infrastructure.* Real-time Event Emission: Continuously publish Business Events from live data streams, enabling downstream consumers to react instantly.* Integrated Publisher Lifecycle: Manage, update, and monitor Eventstream publishers alongside other Business Event producers in a unified experience.","feature_name":"Eventstream as a Business Events Publisher from Real-Time Hub","last_modified":"2026-07-17","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q3 2026","release_item_id":"c8df0463-d93d-f111-88b5-6045bd0a8ec1","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":"Expanding Real-Time Intelligence data sources with Cribl source (Preview)","blog_url":"https://blog.fabric.microsoft.com/en-US/blog/expanding-real-time-intelligence-data-sources-with-cribl-source-preview","feature_description":"The Cribl source for Eventstream allows you to stream data from Cribl Stream into Fabric Eventstream. You can add Cribl as a source to your eventstream to capture, transform, and route real-time events to various destinations in Fabric.","feature_name":"Eventstream connector: Cribl","last_modified":"2026-07-17","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q3 2026","release_item_id":"4ec67f5b-2c82-f111-ab0f-002248085b3f","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":"Introducing Enhanced Capabilities in Eventstream: Derived Streams, Edit modes, and Smart Routing","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/introducing-enhanced-capabilities-in-eventstream-derived-streams-edit-modes-and-smart-routing","feature_description":"**Eventstream as a Business Events Consumer from Real-Time Hub****Overview**Enable Eventstream to natively consume Business Events from Real-Time hub--unlocking real-time processing, transformation, and routing of business signals across Fabric.**Key Capabilities*** Native Eventstream Consumption: Create Eventstream consumers directly from Business Events in Real-Time hub to start processing events in real time.* Real-time Event Processing Pipelines: Build pipelines to ingest, process, and route Business Events with low latency as they are published.* Flexible Transformations & Enrichment: Apply transformations, filtering, and enrichment to Business Events before routing them to downstream systems.* Seamless Routing to Destinations: Deliver processed events to multiple Fabric destinations (e.g., storage, analytics engines, downstream services) for further action.* Integration with Analytics & Actions: Enable scenarios such as real-time insights, anomaly detection, alerts, and automated workflows powered by event data.","feature_name":"Eventstream as a Business Events Consumer from Real-Time Hub","last_modified":"2026-07-17","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q3 2026","release_item_id":"452a8734-da3d-f111-88b5-6045bd0a8ec1","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":"Acquiring Real-Time Data from New Sources with Enhanced Eventstream","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/acquiring-real-time-data-from-new-sources-with-enhanced-eventstream","feature_description":"**Business Events as a Source in Eventstream****Overview**Enable Business Events in Real-Time hub to be used as a native source in Eventstream--allowing users to easily ingest business signals into streaming pipelines for real-time processing and analytics.**Key Capabilities*** Native Business Events Source Integration: Select Business Events directly from Real-Time hub as an input source when creating Eventstream pipelines.* Seamless Event Subscription: Subscribe to relevant Business Events and stream them into Eventstream without requiring custom connectors or ingestion logic.* Unified Streaming Pipeline Creation: Combine Business Events with other data streams in a single Eventstream pipeline for richer, context-aware processing.* Real-time Event Ingestion: Continuously ingest Business Events as they are published, enabling low-latency processing and downstream actions.* Flexible Processing & Routing: Apply transformations, filtering, and routing logic within Eventstream to drive analytics, storage, or automated workflows.","feature_name":"Business Events as a Source in Eventstream","last_modified":"2026-07-17","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q3 2026","release_item_id":"0ba4b543-d83d-f111-88b5-6045bd0a8ec1","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Fabric Eventhouse now supports Eventstream Derived Streams in Direct Ingestion mode (Preview)","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/fabric-eventhouse-now-supports-eventstream-derived-streams-in-direct-ingestion-mode-preview","feature_description":"You can now shortcut an existing Azure Event Hub as a fully featured Eventstream, bringing your own hub into Fabric without rebuilding pipelines. The shortcut stream behaves like a native Eventstream, including processing and routing.With this capability, you can:- Connect an existing Event Hub to Fabric as an Eventstream.- Process shortcut hub data with Eventstream operators.- Route events to Fabric destinations without recreating sources.","feature_name":"Bring your own Eventhub to Fabric Eventstream","last_modified":"2026-07-16","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q1 2027","release_item_id":"ee5af75d-3f4a-f111-bec7-002248085b3f","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"New Eventstream sources: MQTT, Solace PubSub+, Azure Data Explorer, Weather & Azure Event Grid","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/new-eventstream-sources-mqtt-solace-pubsub-azure-data-explorer-weather-event-grid","feature_description":"Eventstream now supports a Java Message Service source connector, extending coverage to another widely used message broker type. Teams running JMS brokers can stream those messages into Microsoft Fabric for real-time analytics.With this capability, you can:- Connect Eventstream to Java Message Service brokers.- Stream JMS messages into Fabric destinations.- Process broker data with no-code operators or SQL operators.","feature_name":"JMS Eventstream connector","last_modified":"2026-07-16","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q1 2027","release_item_id":"eb22e174-8e3f-f111-88b5-6045bd00f798","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Continuous Ingestion from Azure Storage to Eventhouse (Preview)","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/continuous-ingestion-from-azure-storage-to-eventhouse-preview","feature_description":"Eventstream can now continuously ingest file content from Azure Blob Storage into Eventhouse, streaming new and updated files as they arrive. Teams can analyze file data in near real time.With this capability, you can:- Ingest files from Azure Blob Storage automatically as they land.- Stream file content through Eventstream into Eventhouse.","feature_name":"Continuous ingestion from Azure Blob Storage files","last_modified":"2026-07-16","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q1 2027","release_item_id":"c300a8cf-863f-f111-88b5-6045bd00f798","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Unlocking Real-Time Operational Intelligence: Azure Monitor Logs Integration in Fabric via Eventstream","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/unlocking-real-time-operational-intelligence-azure-monitor-logs-integration-in-fabric-via-eventstream","feature_description":"This integration simplifies the discovery of Azure resource diagnostic logs in Fabric RTI, and automatic creation of Eventstream operators, allowing users to focus more on analysis and less on setup. 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Developers and analysts can work with change data as if it were regular tables, without interpreting complex CDC semantics. 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This lets you stream data from third-party providers that require token-based access, using a secure, standard authentication flow.With this capability, you can:- Authenticate to external APIs with OAuth tokens.- Stream data securely from providers that require token-based access.- Refresh tokens automatically for continuous ingestion.","feature_name":"OAuth support for the Eventstream HTTP connector","last_modified":"2026-07-16","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q1 2027","release_item_id":"714d2deb-263e-f111-88b5-6045bd0066ad","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"Eventstream can now use CopyJob sources, with discovery through Real-Time Hub, broadening a set of sources you can stream into Fabric. 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No more jumping between different wizards or piecing together workflows. With one streamlined flow, you can connect a source, preview your data, map your schema, and land it directly into any RTI destination -- all in a few guided steps.Key capabilities:- One consistent ingestion experience across every RTI workload- Built-in data preview to validate events before ingestion- Schema inference and table mapping- Native integration with Eventstream, Eventhouse, Activator, Lakehouse, and Notebook","feature_name":"Unified GetEvents for Fabric RTI","last_modified":"2026-07-16","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q1 2027","release_item_id":"5087315d-e93e-f111-88b5-6045bd00f798","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"What\u2019s new in Fabric Eventstream: July\u2013December 2025 updates","blog_url":"https://blog.fabric.microsoft.com/en-US/blog/whats-new-in-fabric-eventstream-july-december-2025-updates","feature_description":"### Large Message Support in Fabric Eventstreams  #### Overview  Large Message Support enables Fabric Eventstreams to ingest, process, and deliver event payloads up to **20 MB** per message. This removes the need for customers to split, chunk, or pre-process large events before streaming them through Eventstreams.  #### Problem  Today, Eventstreams enforces a default message size limit of 1 MB. Customers with larger payloads -- such as batched IoT telemetry, enriched event schemas, media metadata, or complex domain events -- must implement workarounds to stay within this constraint. These workarounds add pipeline complexity, increase failure surface, and break downstream schema consistency.  #### What's changing  With this feature, customers can opt in to a configurable message size ceiling (up to 20 MB) on their Eventstreams. Key aspects:  - **Opt-in by design** -- existing Eventstreams are unaffected unless the customer explicitly enables a higher limit. - **Configurable ceiling** -- customers choose the maximum message size aligned to their workload, rather than a one-size-fits-all default. - **No pipeline redesign required** -- sources, transformations, and destinations continue to work as expected. Larger messages flow through the same Eventstream canvas.","feature_name":"Large message support ( 20 MB) for Fabric Event streams","last_modified":"2026-07-16","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q1 2027","release_item_id":"4dc5810b-2040-f111-88b5-6045bd0066ad","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Bridging Fabric Lakehouses: Delta Change Data Feed for Seamless ETL","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/bridging-fabric-lakehouses-delta-change-data-feed-for-seamless-etl","feature_description":"Eventstream now reads change records directly from change-enabled Delta tables in a Lakehouse and streams them in real time. 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As a result, creating event-driven and AI-powered applications--like dashboards, alerts, and compliance solutions--no longer requires manual data movement or complex integrations.","feature_name":"Unify batch & streaming data platforms with CopyJob & Real-Time Intelligence","last_modified":"2026-07-16","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q1 2027","release_item_id":"403b7b13-0ca4-f011-bbd3-000d3a5b0efa","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"New Eventstream sources: MQTT, Solace PubSub+, Azure Data Explorer, Weather & Azure Event Grid","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/new-eventstream-sources-mqtt-solace-pubsub-azure-data-explorer-weather-event-grid","feature_description":"Eventstream now provides a Salesforce platform events source connector, bringing real-time business events from Salesforce into Microsoft Fabric. 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