Real-Time Intelligence topics

Fabric Business Events: what delivery guarantees and replay pattern should we design for?

ShivekMaharaj — Mon, 17 Aug 2026 20:41:33 GMT

Hi all,

I am testing the newer Business Events capability in Fabric Real-Time Intelligence and trying to understand what reliability assumptions should be made for a production design.

The pattern I am looking at is roughly:

Eventstream → Business Event → Activator → downstream action / User Data Function

with Eventhouse enabled so the published business events are also retained for historical analysis.

The current documentation explains the publisher/consumer model and shows how Eventstream can publish a governed business event that Activator then consumes. What I have not been able to find clearly documented is the delivery contract between the published business event and its consumers.

A few things I am trying to clarify:

If an Activator consumer or downstream action is temporarily unavailable, does Fabric retry delivery of the business event?
Should consumers assume at-least-once delivery and therefore be designed to handle duplicate events, or is a different delivery model used?
Is event ordering guaranteed in any scope, for example for events from the same Eventstream publisher?
Since published business events can also be retained automatically in Eventhouse, is that retained history intended to support replay/reprocessing after a consumer outage, or is it primarily an analytical record and replay would need to be implemented separately?
Are there documented retry or delivery-retention windows that should be considered when designing an operational workflow?

I am mainly trying to understand what a resilient production pattern should look like when the business event triggers something with side effects, where processing the same event twice or silently missing an event would matter.

Would you generally make the downstream consumer idempotent and treat Eventhouse as an audit/recovery store, or is there a more Fabric-native pattern for this?

Interested to hear how others are approaching this with Business Events and Activator.

Best practice for handling schema evolution in Fabric Eventstream before data reaches Eventhouse?

ShivekMaharaj — Wed, 12 Aug 2026 21:33:25 GMT

I have an Eventstream receiving operational events where the schema may evolve over time.

For example, the producer initially sends:

DeviceId, Timestamp, Temperature, Status

but later adds fields such as:

Location, FirmwareVersion, ErrorCode

I want the pipeline to continue ingesting events without breaking downstream KQL tables, update policies, materialized views, or Real-Time Dashboards.

I am trying to understand where schema evolution should ideally be handled in a production Fabric RTI architecture.

Would you:

enforce the contract upstream using Schema Registry
normalize changing fields inside Eventstream before Eventhouse ingestion
land the raw payload first and handle schema evolution inside Eventhouse/KQL
maintain separate versioned event schemas/tables

How are people handling this in production when producers can add fields without notice?

I am particularly interested in avoiding a design where every small upstream schema change forces updates across Eventstream, KQL tables, update policies, and downstream dashboards.

Best practice for deciding between Eventstream transformations and Eventhouse update policies

ShivekMaharaj — Thu, 06 Aug 2026 18:41:22 GMT

Hi Fabric Community,

I am exploring a Real-Time Intelligence architecture and would appreciate some guidance on where transformation logic should ideally be placed.

The proposed flow is:

Azure Event Hubs → Fabric Eventstream → Eventhouse → Real-Time Dashboard / Power BI

Fabric Eventstream supports filtering, field management, aggregation and other processing before events are written to the destination. An Eventhouse can also ingest the raw events first and transform them into curated tables through KQL update policies.

I am trying to understand the recommended boundary between these two layers.

For example, assume the incoming event contains:

Device or customer identifier
Event timestamp
Event type
Location
Numeric readings
Additional JSON properties

The required processing includes:

Removing events that fail basic validation
Renaming and standardizing fields
Converting timestamps and data types
Flattening selected JSON properties
Enriching the event with reference data
Creating five-minute aggregates
Preserving the original event for auditing and future reprocessing

My current thinking is:

Use Eventstream for lightweight filtering, routing and simple schema normalization.
Land the original event in a Bronze table whenever replay or auditing is required.
Use Eventhouse update policies or KQL for enrichment, reusable business logic and curated Silver tables.
Use materialized views for frequently queried aggregations rather than calculating them repeatedly in dashboards.

However, I am unsure where Microsoft recommends drawing the line.

A few questions:

Are there transformation types that should generally remain in Eventstream rather than Eventhouse?
Is it considered good practice to send both the raw stream and a transformed derived stream into separate Eventhouse tables?
When using Eventstream’s Event processing before ingestion mode, what are the trade-offs compared with direct ingestion followed by an Eventhouse update policy?
How do teams handle changes to transformation logic when historical events need to be reprocessed?
For reference-data enrichment, would you normally perform the lookup in Eventstream or after ingestion with KQL?
Are five-minute or hourly aggregations better implemented in Eventstream, through an update policy, or with an Eventhouse materialized view?

Microsoft’s Eventstream destination guidance documents both direct ingestion and event processing before ingestion, while the KQL update-policy documentation provides another way to transform ingested data.

I would be interested to hear how others divide responsibility between Eventstream and Eventhouse in production, particularly where auditability, reprocessing and maintainability are important.

Thanks in advance!

Best Way to Monitor Marketing Campaign Performance in Real Time Using Microsoft Fabric or Power BI?

iluvsmmpanel — Wed, 05 Aug 2026 13:31:22 GMT

Hi everyone,

I'm building a real-time dashboard in Power BI to monitor social media marketing campaigns. The goal is to combine data from platforms like Instagram, Facebook, and Google Analytics into a single dashboard.

I would like to track metrics such as:

Impressions
Reach
Clicks
CTR (Click-Through Rate)
Engagement Rate
Conversions
ROI (Return on Investment)

I'm considering using Azure Data Factory, Azure SQL, and Power BI for data collection and visualization.

Has anyone implemented a similar solution? Which architecture or Microsoft services would you recommend for near real-time reporting? Any best practices for handling automatic refreshes, data modeling, and performance optimization would be greatly appreciated?

I also put together a guide on social media analytics and campaign monitoring on my website. If sharing resources is allowed here, I'd be happy to share it with anyone who is interested.

Thanks in advance for your suggestions!

Luv Kalra

Real time dashboard

powerbidev123 — Sun, 02 Aug 2026 13:33:26 GMT

Since the latest Microsoft Fabric update, I've noticed a change in how Real-Time Dashboard refresh behaves.

Previously, I could configure visuals with Continuous refresh, allowing them to update almost immediately whenever new data arrived (typically within a few seconds, with a maximum delay of around 10 seconds).

After the recent update, it appears that continuous refresh is enabled by default, but visuals now refresh at a fixed minimum interval of 10 seconds. In addition, visuals that don't support continuous refresh—or when no new data is received—seem to refresh every 30 seconds.

I'm trying to understand whether this is expected behavior or if there's a way to restore the previous experience.

Specifically:

Is it still possible to configure Real-Time Dashboard visuals to refresh more frequently than every 10 seconds?
Has the previous event-driven continuous refresh option been removed, or is it available through another setting?
Are there any recommended approaches to achieve near real-time updates when new data arrives instead of relying on fixed refresh intervals?
Was this change introduced intentionally as part of the latest Microsoft Fabric release?

Our dashboards are used to monitor live operational processes, so even a 10–30 second refresh delay has a noticeable impact compared to the earlier behavior. Any clarification or guidance from the community or Microsoft team would be greatly appreciated.

New to microsoft fabric- time intelligence.

Anj_il_a- — Sun, 26 Jul 2026 17:53:13 GMT

Hello everyone! I'm new to microsoft fabric and Real -Time Intellligence. I am excited to learn how the real time data processing

works and look forward to learning from this community.

I am beginner to microsoft fabric . So as a beginner with basic programming knowledge, what are the best beginner resources to start learning Real-Time Intelligence?

I hope you will favour me....

Streaming Architecture

binitafulpagare — Fri, 17 Jul 2026 04:06:22 GMT

Hi everyone,

I'm exploring Microsoft Fabric Real-Time Intelligence and would love to understand how it's being used in enterprise environments.

Which business scenarios have benefited the most from real-time analytics?

How do you balance:

Low latency
High throughput
Cost
Scalability
Reliability

I'm interested in learning from real production implementations.

Thank you!

How do you decide when to use Real-Time Intelligence instead of batch processing in Microsoft Fabric

binitafulpagare — Thu, 09 Jul 2026 04:28:25 GMT

Hi everyone,

I'm learning Microsoft Fabric and recently started exploring Real-Time Intelligence. I understand that it can process streaming data, but I'm trying to understand when it's the right choice compared to traditional batch processing.

I have a few questions:

What types of business scenarios benefit the most from Real-Time Intelligence?
When would you choose streaming over scheduled batch processing?
What are some common real-world use cases you've worked on?
Are there any performance or cost considerations that beginners should be aware of?

I'd really appreciate hearing about your experiences and any best practices you recommend.

Thank you!

Microsoft Fabric Activator generating repeated false alerts despite stable Power BI metric

egstst — Fri, 26 Jun 2026 13:32:11 GMT

Hi!

I'm experiencing an issue with Microsoft Fabric Activator that started last week after working reliably for several months.

I have several Activator alerts monitoring Power BI metrics that indicate whether data for the previous day is available. After the daily semantic model refresh, the metric correctly changes from FALSE (0) to TRUE (1) once yesterday's data is available.

The problem is that after the refresh has completed, the report/dashboard remains stable, but Activator continues to fire the alerts repeatedly.

What I observe

The semantic model refreshes successfully.
The Power BI report/dashboard correctly shows TRUE (or 1) and does not change afterwards.
The semantic model is not refreshed again for several hours.
However, the Activator PowerBI Metric live feed repeatedly alternates between TRUE/FALSE (or 1/0) for some monitored objects, even though the report values remain unchanged.
Since my alert is configured as "Changes to TRUE", these false state changes cause repeated alert notifications.

Expected behaviour

The semantic model refreshes.
The metric changes from FALSE to TRUE once.
Activator triggers a single alert.
No further alerts are generated until the metric actually changes again.

Actual behaviour

The semantic model refreshes successfully.
The report/dashboard values remain stable.
The Activator PowerBI Metric live feed shows alternating TRUE/FALSE (or 1/0) values.
Alerts continue to fire despite no changes to the underlying data.

Troubleshooting performed

Confirmed the semantic model had not refreshed again.
Confirmed the report/dashboard values remained unchanged.
Confirmed the alert definition had not been modified.
Deleted and recreated the Activator alerts.
Replaced numeric 1/0 measures with Boolean TRUE/FALSE measures.
The issue persists after all of the above.

Has anyone else experienced similar behaviour recently? Is this a known issue with Fabric Activator or the PowerBI Metric event source?

Thanks in advance!

Real-Time Dashboard continuous refresh no longer refreshes faster than 10 seconds

Borna — Tue, 16 Jun 2026 07:29:52 GMT

Hi everyone,

Until last week, I had an option in Microsoft Fabric Real-Time Dashboard to configure refresh as Continuous, meaning that visuals would refresh whenever new data arrived, with the maximum time without new data being around 10 seconds.

After the latest update, which I believe was released yesterday, the behavior seems to have changed. Continuous refresh now appears to be enabled by default, but the minimum refresh interval is 10 seconds, so it does not seem possible to refresh faster than every 10 seconds anymore.

Also, for visuals that do not support continuous refresh, or when no new data arrives, the dashboard now seems to refresh every 30 seconds.

My questions are:

Is there still a way to configure Real-Time Dashboard visuals to refresh faster than 10 seconds?
Is the old continuous refresh behavior still available somewhere in the settings?
Is there any workaround for achieving near real-time refresh when data arrives, instead of waiting for the fixed interval?
Was this change intentional as part of the latest Fabric update?

This is important for our use case because we monitor live operational data, and even a 10–30 second delay can make the dashboard less useful compared to the previous behavior.

Thanks in advance for any clarification or suggestions.

Digital Twin Builder (preview): Bounding storage growth for an incremental time-series

smorenodev — Fri, 12 Jun 2026 01:07:21 GMT

Is there any supported way to apply a retention horizon to a Digital Twin Builder time-series mapping that uses incremental processing, so the underlying dtdm table doesn't grow without bound?

My scenario: high-frequency live telemetry landing in an Eventhouse, surfaced to DTB through a lakehouse table (I've used both shortcuts and pipeline copy activities in my tests). The static layer and relationships are working well. The question is purely about the time-series layer.

With incremental mapping enabled, the series appends continuously and the dtdm table grows linearly with no eviction. I've confirmed a couple of things that don't solve it, so I'll pre-empt them:

Retention on the source table doesn't bound the twin copy. Incremental processing is forward-only, so source rows aging out are never removed from data the mapping already ingested.
A mapping filter governs ingestion, not eviction, and only limits initial backfill (no relative/dynamic date filter).

I assume full reload (incremental disabled) over a windowed source table does keep things bounded, since each run replaces the prior load, and that's my current fallback. But I'd like to confirm whether there's any retention/TTL control I've missed for the incremental path specifically, at the mapping, entity, or item level, or any sanctioned way to age out rows from the dtdm time-series table.

If the answer is "not currently supported," that's useful to know too, and I'll file it as an Idea. Running on a Fabric capacity, DTB still in preview. Thanks in advance

Dataverse Data (Preview) feature in Fabric RTI Error

Aavanade_365 — Fri, 05 Jun 2026 15:48:15 GMT

I am trying to test the new Dataverse Data (Preview) feature for streaming data from Dataverse to Fabric. After using the preview option for source data from Dataverse, I can also choose a table and events such as Create, Update, Delete to track. However, when everyting is finished I get this error:

MessageFailed to create data source: dataverse due to the following error: E0179001: Cannot connect to Kafka. Please check your configuration.

Details

E0179001: Cannot connect to Kafka. Please check your configuration.

What is the resolution for this?

Is this new preview feeature functional?

Working with Microsoft Fabric Support - A Collaborative Approach

krlitt — Wed, 03 Jun 2026 16:37:01 GMT

At Microsoft Fabric Support, our goal is simple: help you resolve issues as quickly and smoothly as possible. Just like the recommendations shared in the Microsoft Fabric Community’s guidance on getting questions answered effectively, providing clear and complete information upfront helps everyone move faster and avoid unnecessary back-and-forth.

Support is most effective when it’s a collaborative process. You bring the knowledge of your environment and workloads, and we bring deep platform expertise and diagnostics to help investigate the issue together.

Help Us Help You

When opening a support case, please include as much of the following information as possible:

Issue Details

Clear description of the problem
Expected behavior vs. actual behavior
Is the issue intermittent or consistently reproducible?
Approximate timeframe of when the issue occurred (UTC preferred)

Error Information

Please include:

Full error message text
Screenshots (highly recommended)
Activity IDs / Correlation IDs if available

Even small details can significantly speed up investigation.

Environment Information That Helps Investigation

Depending on the Fabric workload being used, please provide the relevant item IDs and environment details.

Workspace Information

Workspace ID / Workspace URL

To find this:

Open the Fabric workspace
Copy the URL from your browser

Example:

".. https://app.fabric.microsoft.com/groups/<WorkspaceID>/… …"

The value after /groups/ is the Workspace ID.

Screenshot example above showcases the WorkspaceID and EventhouseID.

Fabric Item IDs

Please provide the item ID related to the affected workload, such as:

EventhouseID
ActivatorID
LakehouseID
WarehouseID
SemanticModelID
EventstreamID
PipelineID

These IDs help us locate telemetry and backend diagnostics more efficiently.

You can typically find these:

In the browser URL while inside the Fabric item
Within item settings/details pages
From the Fabric portal navigation pane

Additional Environment Details

Please also include:

"… WorkspaceID:

Capacity Name:

Region …"

Example:

"… WorkspaceID: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx

Capacity Name: Fabric-Prod-EastUS

Region: East US …"

This information helps us identify:

Capacity-level issues
Regional service impact
Configuration-specific behavior

Why This Matters

Microsoft Fabric is a distributed cloud platform, and troubleshooting often depends on correlating logs, telemetry, timestamps, and resource identifiers together.

Providing complete details upfront helps:

Reduce delays
Avoid repeated clarification requests
Accelerate root cause analysis
Create a smoother support experience for everyone involved

We’re here to partner with you throughout the process, and we truly appreciate your collaboration in helping us investigate issues effectively.

We look forward to working with you!

Error in Microsoft Applied Skills: Implement a Real-Time Intelligence Assessment Lab : Need help

AshikaAlvakonda — Sat, 02 May 2026 12:22:56 GMT

Hello All, since a week I was stuck on one error in Microsoft Applied Skills: Implement a Real-Time Intelligence solution with Microsoft Fabric Lab. Did anyone face the same issue if so, can anyone help me out how to resolve it. Attaching the error and related images below.

Error: It says " unable to load container blobs. Verify that workspace identity is enabled and has storage blob data reader access to the storage account" . I am familiar with this permission and have enabled it in my own azure environment for my own blob that I have created but since these are pre created by Microsoft, I don't have access to these storage blobs and hence I am not sure how to proceed here. I have attempted this twice but I was stuck at the same point.

I really appreciate your help and taking time in looking into my post. Thank you so much.

Realtime - Business Events - cannot create business event shcema

KimTutein — Fri, 10 Apr 2026 11:27:38 GMT

Has anyone succeeded in creating business event shcema?

I keep getting the error "An unexpected error occourred". I have tried waiting a week but it seems we simply cannot make a "business event schema" (se screendump in appendix).

Our tennant is in West Europe.

Appendix - screendumps

Activator Not Showing in My Workspace

kasun_rumesh — Mon, 06 Apr 2026 06:06:29 GMT

According to the Fabric Capacity Metrics, an Activator item is consuming a high amount of capacity units. However, when I check the workspace manually, no Activator item is visible. I wanted to delete or remove this item, as it appears to have been activated by mistake.

How to reset Eventhouse Ingestion from Batching to Streaming ?

lavginqo — Fri, 27 Mar 2026 23:58:33 GMT

Hi everyone,

I am experiencing a persistent latency issue in our Microsoft Fabric Eventhouse. A table that was previously performing perfectly has suddenly "downgraded" its ingestion path from Streaming to Batching and refuses to recover.

The Situation:

The Problem: In our PROD Eventhouse, ingestion latency is stuck at 12–15 seconds. The table is generating 45+ shards (extents) every 10 minutes, confirming it is in Batching Mode.
The Discrepancy: Our DEV Eventhouse (identical schema and higher data volume) is still Streaming perfectly with ~5-second latency and 0 shards created per 10 minutes.
The History: PROD was working fine (5s latency) and then switched to this slow Batching state on its own without any schema or policy changes.

What we have verified:

Streaming Policy: Both DEV and PROD have streamingingestion enabled.
Batching Policy: We tested various ingestionbatching settings in a separate environment. We confirmed that the 12s latency in PROD is a result of the Batching Path overhead
Unable to restore streaming: Running .alter table ... streamingingestion enable in PROD does not trigger a return to the Streaming.

Our Questions:

Why would an Eventhouse suddenly "blacklist" a table from the Streaming path and move it to permanent Batching if the Capacity (CU) is healthy (~50%)?
How do we reverse this process? Once a table is stuck in this "Permanent Batching" state, what is the specific command or workflow to force the Eventhouse to re-evaluate it for the Streaming (Fast) Lane?

We need to restore the 5-second latency to meet our real-time requirements.

Any insights into the internal health-check logic of the Eventhouse would be incredibly helpful.

Thank you !

Architecture question and brainstorming

Ira_27 — Fri, 20 Mar 2026 18:39:13 GMT

Hello Community,

I have a design question that I need help with, we have a lot of vendor data that comes in form of CSV, XML, XLSX files via sftp. I already have ADF that copies this files into ADLS Gen2. Now when implementing in fabric I actually used blob storage events to trigger a notebook to load this files into a Lakehouse. I want to get suggestions if it's a good idea to use real time intelligence to stream data from this files and stage into a lakehouse? Has anyone implemented this? If so would love to get guidance. I am fairly new to evetstream and need more details on CU consumption, cost etc. what are disadvantages of using streaming notebook?

Error while saving a dashboard having a Tile with a simple table

mshafieluru — Sat, 21 Mar 2026 19:59:08 GMT

I am creating a RTI Dashboard with a Single Tile having following query

Table1 | extend AccountId = account_id, AccountName = account_name | order by account_id asc | project AccountId, AccountName

The query runs fine, but on saving the dashboard i get following error:

Any suggestions on how to fix this.

Not Able to create a Connection between Fabric EventStream and Azure Event Hub.

Abhishek_Puru — Fri, 06 Mar 2026 04:59:22 GMT

Working on a real-time data pipeline using 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗙𝗮𝗯𝗿𝗶𝗰 𝗘𝘃𝗲𝗻𝘁𝘀𝘁𝗿𝗲𝗮𝗺 and 𝗔𝘇𝘂𝗿𝗲 𝗘𝘃𝗲𝗻𝘁 𝗛𝘂𝗯, and I ran into an issue I’m hoping the community might have seen before.

While trying to create a new Azure Event Hub connection inside Fabric Eventstream, the connection configuration panel appears completely 𝗯𝗹𝗮𝗻𝗸, so I’m unable to enter the required details like the connection string or namespace.

𝗧𝗵𝗶𝗻𝗴𝘀 𝗜’𝘃𝗲 𝗮𝗹𝗿𝗲𝗮𝗱𝘆 𝘁𝗿𝗶𝗲𝗱:

• Refreshing the browser and clearing cache.
• Using different browsers (Edge, Chrome).
• Logging out and back into Fabric.

Still facing the same issue.

Has anyone encountered this while integrating Fabric Eventstream with Azure Event Hub? Any suggestions or configuration checks I should try?

Appreciate any insights from the community