Handling late and out-of-order events in Eventstream windows and Eventhouse aggregations?
I'm coming from Apache Flink, where late and out-of-order events are handled with event-time watermarks and allowed lateness. I'm trying to understand the equivalent approach in Fabric Real-Time Intelligence. Scenario: IoT devices send telemetry with an event timestamp. Because of network delays, some events arrive several minutes late, and occasionally out of order. I need accurate 5-minute aggregates (average and max per device) for dashboards and Activator rules. Questions: Eventstream: when using windowed aggregations (tumbling or hopping), are windows based on event time or arrival time? Is there a setting for out-of-order tolerance or late-arrival handling, and what happens to events that arrive after a window has closed: are they dropped, or do they produce a corrected result? Eventhouse: if I aggregate in Eventhouse instead, for example with a materialized view using bin(EventTime, 5m), are late events included automatically when they arrive? Any caveats with materialized views and late data? Which layer is better for aggregations when correctness under late data matters more than lowest latency? Activator: if a rule has already fired on an aggregate that later gets corrected by late data, is there a pattern for handling that, or should rules only run on finalized windows?
Fabric Business Events: what delivery guarantees and replay pattern should we design for?
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.
Dataverse Data (Preview) feature in Fabric RTI Error
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?
Error in Microsoft Applied Skills: Implement a Real-Time Intelligence Assessment Lab : Need help
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.
