AI Readiness · 2
Fabric Updates
Sep 2, 2026
3/5 · Tier B
AI ReadinessGovernance
announcement
<p><strong>Fabric Data Agents</strong> are generally available in Copilot Studio as tools through <strong>Fabric IQ Data MCP</strong>, replacing the earlier connected-agent experience. Copilot Studio can invoke the data agent alongside connectors, workflows, SharePoint knowledge, and other tools.</p><p>The Fabric data agent continues executing in Fabric and respects permissions on the underlying data sources. Agents can now be published to <strong>Microsoft Teams</strong> and <strong>Microsoft 365 Copilot</strong>, allowing users to ask questions over governed enterprise data inside their normal work surfaces.</p><p>The integration improves composition and reuse, but answer quality still depends on the data agent’s definitions, source permissions, and orchestration decisions. The extract does not provide specific consumption pricing, quotas, or accuracy benchmarks.</p>
GA integration makes governed Fabric data reusable in Copilot Studio, with permission inheritance and broader publishing options.
Fabric Updates
Sep 1, 2026
3/5 · Tier B
AI ReadinessSemantic Model
announcement
<p><strong>Advanced DAX generation</strong> is available in the Fabric data agent Preview runtime. Instead of translating a question in one pass, the agent can inspect semantic-model metadata, use tools, review intermediate results, refine its query, and execute the final DAX.</p><p>Instance value indexing helps resolve informal user wording to actual column values, improving filters for company names, products, locations, and categories. The feature remains preview-only, and the runtime affects more than DAX generation. Clear names, focused AI schemas, instructions, verified answers, and performant measures remain necessary for reliable results.</p>
Preview agentic DAX generation improves value resolution and iterative reasoning, but accuracy still depends on model preparation.
Capacity · 1
<p><strong>Capacity Operation Events</strong> are available in Real-Time Hub as a preview, adding operation-level telemetry to the broader Capacity Overview Events. Administrators can identify which operations, workspaces, and artifacts are contributing to capacity consumption, throttling, or performance pressure.</p><p>Events include workspace and item details, capacity-unit consumption, operation duration, start time, and smoothing-window attribution. The telemetry can feed Eventhouse, custom dashboards, alerts, and Microsoft Activator workflows for near-real-time notification or remediation.</p><p>The feature complements rather than replaces the Capacity Metrics App: overview events answer what is happening to capacity, while operation events help explain which workloads caused it. Preview schemas and event availability should be validated before production automation depends on them.</p>
Exposes operation-level capacity telemetry for consumption, throttling, workspaces, artifacts, and near-real-time automation.
CI/CD · 1
<p>New guidance connects Fabric REST APIs, Git integration, deployment pipelines, Variable library, Fabric CLI, Terraform, and the <strong>fabric-cicd</strong> library into end-to-end delivery patterns. Tutorials cover Terraform-provisioned environments, local deployment, Azure DevOps approval gates, parameterized environment values, and Git-driven Bulk Import and Export API deployments.</p><p>The dependency guidance is particularly important: some references bind through portable logical IDs, while others retain workspace-specific object IDs and require parameterization. An open-source generic Git sample extends the pattern to GitLab, Bitbucket, GitHub Enterprise Server, Azure DevOps Server, and multi-tenant deployments.</p>
The resources provide concrete Fabric promotion patterns, automation tooling, dependency handling, and multi-provider Git support.
Governance · 3
<p><strong>Workspace Outbound Access Protection (OAP)</strong> applies default-deny outbound policies to Operations Agent and Fabric Maps. Workspace administrators approve destinations through Data Connection Rules, while blocked actions appear in notifications and the Operations Agent Activity Log.</p><p>Fabric Maps validates references during save and load, then validates map tiles, geospatial features, and query requests at runtime. Lakehouses in the same workspace remain allowed; cross-workspace Lakehouses require rules. Approved WMS, WMTS, and WFS endpoints are supported, while cross-workspace Kusto databases and Ontologies remain blocked. Policy failures deny access rather than permitting unvalidated connections.</p>
Preview adds default-deny outbound controls, allow lists, audit visibility, and fail-closed behavior for agents and maps.
<p><strong>Fabric Pipelines and Copy Jobs</strong> can move data to or from Snowflake without exposing the workspace, staging storage, or Snowflake transfer path publicly.</p><p>The topology combines <strong>Workspace-level Private Link</strong> for inbound workspace access, an external Azure Blob staging account with Trusted Workspace Access, and Snowflake storage integration configured with <strong>USE_PRIVATELINK_ENDPOINT = TRUE</strong>. Fabric and Snowflake use separate identities, requiring Blob Data Reader and Blob Data Contributor permissions respectively.</p><p>OneLake cannot currently provide the required private staging path in this configuration, so external Azure Blob is necessary. Workspace-level Private Link requires supported capacity and region settings, while Snowflake-managed outbound private connectivity requires Business Critical edition or higher. The Snowflake private endpoint also requires approval on the storage account.</p>
Provides a concrete private-network topology, identity model, prerequisites, and Snowflake edition limitation for regulated workloads.
<p>The <strong>List Networking Communication Policies Admin API</strong> is generally available for tenant-wide visibility into workspace networking policies. It exposes inbound controls such as public access, IP firewall rules, and default behavior, alongside outbound restrictions, connection and gateway rules, Git communication policies, and managed private endpoints.</p><p>Results are paginated and support filters for selected inbound and outbound conditions. Fabric administrators or authorized service principals can incorporate the response into governance dashboards, SIEM monitoring, security reviews, and compliance evidence without inspecting workspaces individually.</p>
A GA tenant-level Admin API enables automated auditing of workspace network controls at enterprise scale.
Migration · 2
<p><strong>Power BI and Fabric are transitioning eight connectors from embedded ODBC drivers to Apache Arrow Database Connectivity (ADBC)</strong>, including Snowflake, BigQuery, Databricks, Spark, Impala, and Dremio. ADBC uses Arrow-oriented transport to reduce serialization and copying for large result sets, while improving driver security and memory safety.</p><p>Existing connections continue using ODBC until edited or explicitly configured with <strong>Implementation="2.0"</strong>. During the validation window, administrators can enable ADBC for individual connections, a workspace, or the tenant. ODBC becomes unavailable in the service after the connector-specific cutover, currently expected in early 2027 for the listed connectors, with no tenant opt-out afterward.</p>
GA driver transition has mandatory cutover dates, validation controls, connector-specific behavior, and production migration risk.
<p><strong>Fabric Migration Assistant for SQL database is generally available.</strong> Its new <strong>Validate</strong> step analyzes an uploaded DACPAC before a Fabric SQL database is provisioned, identifying compatible and incompatible objects, failure reasons, and dependency chains without consuming a target or committing capacity.</p><p>After assessment, the guided workflow provisions the database, deploys the schema with interactive fix suggestions, copies data through Fabric Copy Jobs, and supports on-premises access through Fabric Data Gateway. Pre- and post-deployment scripts can handle load-specific constraint changes before validation and cutover.</p>
GA migration workflow adds pre-provisioning DACPAC validation, dependency-aware remediation, schema deployment, and integrated data movement.
Real-Time Intelligence · 3
<p><strong>Eventstream can retrieve streaming data from private MQTT, Kafka, CDC, and messaging sources through an approved virtual network path.</strong> A customer-owned Azure VNet connects to the private source using VPN or ExpressRoute, while a delegated subnet hosts the managed streaming connector.</p><p>The workspace identity needs permission to use the VNet, and Fabric represents the network through a streaming virtual network data gateway. Publishing the Eventstream injects the connector into the subnet, allowing outbound retrieval without exposing the source publicly. Network routing, DNS, firewalls, credentials, certificates, source availability, and subnet IP consumption remain customer responsibilities.</p>
Detailed private-network Eventstream architecture covers routing, identity permissions, connector placement, and subnet capacity implications.
<p><strong>Real-Time Dashboards can now embed a published Fabric Map as a reusable tile in preview.</strong> The dashboard stores a reference to the map item rather than copying its queries, layers, filters, styling, or data-source configuration.</p><p>Viewers can pan, zoom, change basemaps, toggle layers, and adjust unlocked filters temporarily. Locked filters enforce a baseline scope. Map creation and editing remain outside the dashboard in this phase, and viewers need permission to the referenced map and its data source; unavailable dependencies surface an error.</p>
Preview integration embeds reusable Fabric Maps in Real-Time Dashboards, with clear reference, filter, permission, and authoring boundaries.
<p><strong>Five scenarios show a common Fabric Business Events pattern:</strong> a workload detects a meaningful condition, publishes a schema-defined event, Real-Time Hub routes it, and Activator or Eventhouse reacts. Publishers include notebooks, User Data Functions, Eventstream, and Activator.</p><p>The scenarios distinguish immediate action from durable analysis. Activator handles alerts and chained automation, while Eventhouse preserves queryable event history for dashboards and audits. The reusable boundary keeps detection with the publisher and action, retention, or analysis with independent consumers.</p>
Concrete Business Event scenarios demonstrate reusable publisher-schema-consumer boundaries across Activator, Eventhouse, notebooks, and Eventstream.
Warehouse · 2
<p>Reliable medallion architecture depends on operating discipline: batch writes, rerunnable transformations, consumer-oriented Gold models, evidence-based tuning, and monitoring by layer.</p><p>The guidance favors bulk loading with <strong>COPY INTO</strong> or pipelines, set-based CTAS, INSERT...SELECT, and MERGE patterns, with 100 MB to 1 GB files as a starting point for file-based ingestion. Silver should enforce quality rules and idempotent processing, while Gold should expose explicit-grain facts, dimensions, marts, or aggregates shaped around analytical use.</p><p>Fabric Warehouse defaults and V-Order should generally remain enabled unless measurements justify change. Query Insights and warehouse monitoring views should be combined with pipeline metrics such as duration, accepted and rejected records, refresh time, and critical Gold query performance.</p>
Gives practical medallion operating guidance with batch-size ranges, rerunnable Silver transformations, Gold modeling, and layer monitoring.
<p>The new preview guidance compares four dbt patterns: Warehouse-only, Lakehouse landing with Warehouse transformation, Lakehouse refinement with Warehouse serving, and Lakehouse-only Delta-first architecture. The choice depends on where raw data lands, which engine performs transformations, ownership boundaries, and how curated data is consumed.</p><p>It separates architecture from orchestration. dbt can own transformation logic, tests, dependencies, and materialization, while native scheduling or Fabric pipelines can orchestrate broader workflow dependencies. The guidance is architectural rather than a performance benchmark, so engine behavior and operational cost still require workload-specific validation.</p>
Preview guidance compares practical dbt medallion ownership patterns across Lakehouse and Warehouse architectures.
