Merge pull request #314206 from jlian/fix/dfg-profileref-concat

AIO: Remove profileRef from DFG Bicep examples, use concatenate in prose

Author: prmerger-automator[bot]

articles/iot-operations/connect-to-cloud/concept-dataflow-graphs.md

@@ -6,7 +6,7 @@ ms.author: sethm
 ms.service: azure-iot-operations
 ms.subservice: azure-data-flows
 ms.topic: concept-article
-ms.date: 03/13/2026
+ms.date: 04/02/2026
 ai-usage: ai-assisted
 
 ---
@@ -27,9 +27,9 @@ Azure IoT Operations provides two ways to process data in a pipeline:
 | Capability | Data flows | Data flow graphs |
 |-----------|-----------|-----------------|
 | Pipeline shape | Fixed: enrich, filter, map | Flexible: any order, branching, merging |
-| Transform types | Map, filter, enrich | Map, filter, branch, concat, window, enrich |
+| Transform types | Map, filter, enrich | Map, filter, branch, concatenate, window, enrich |
 | Time-based aggregation | Not available | Window transforms with tumbling windows |
-| Conditional routing | Not available | Branch and concat transforms |
+| Conditional routing | Not available | Branch and concatenate transforms |
 | Endpoint support | All endpoint types | MQTT, Kafka, and OpenTelemetry only |
 
 For new projects that use supported endpoint types, we recommend data flow graphs. Data flows remain fully supported for all scenarios, and they support the full range of endpoint types.
@@ -43,7 +43,7 @@ Each transform is a pre-built processing step that you configure with rules and
 | **Map** | Rename, restructure, compute, and copy fields | [Transform data with map](howto-dataflow-graphs-map.md) |
 | **Filter** | Drop messages that match a condition | [Filter and route data](howto-dataflow-graphs-filter-route.md) |
 | **Branch** | Route each message to a `true` or `false` path based on a condition | [Filter and route data](howto-dataflow-graphs-filter-route.md#branch-transform) |
-| **Concat** | Merge two or more paths back into one | [Filter and route data](howto-dataflow-graphs-filter-route.md#merge-paths-with-concat) |
+| **Concatenate** | Merge two or more paths back into one | [Filter and route data](howto-dataflow-graphs-filter-route.md#merge-paths-with-concatenate) |
 | **Window** | Collect messages over a time interval, then aggregate | [Aggregate data over time](howto-dataflow-graphs-window.md) |
 
 All transforms share an [expression language](concept-dataflow-graphs-expressions.md) for operators, functions, and field references. You can also [enrich](howto-dataflow-graphs-enrich.md) messages with external data from a state store in map, filter, and branch transforms.
@@ -52,7 +52,7 @@ All transforms share an [expression language](concept-dataflow-graphs-expression
 
 Transforms connect in sequence inside a `DataflowGraph` resource: **Source > Transform A > Transform B > … > Destination**.
 
-Branch transforms split the flow into parallel paths, and concat transforms merge them back.
+Branch transforms split the flow into parallel paths, and concatenate transforms merge them back.
 
 You can chain any number of transforms in any order. A pipeline with a single map transform is as valid as one that filters, branches, maps each path differently, merges, and then aggregates over a time window.
 
@@ -84,7 +84,6 @@ resource dataflowGraph 'Microsoft.IoTOperations/instances/dataflowProfiles/dataf
   name: 'temperature-conversion'
   parent: dataflowProfile
   properties: {
-    profileRef: dataflowProfileName
     mode: 'Enabled'
     nodes: [
       {
@@ -187,7 +186,7 @@ In the how-to articles that follow, examples focus on the transform rules themse
 
 Data flow graphs support two kinds of transforms:
 
-- **Built-in transforms** are pre-built by Microsoft (map, filter, branch, concat, window). You configure them with rules. No coding required.
+- **Built-in transforms** are pre-built by Microsoft (map, filter, branch, concatenate, window). You configure them with rules. No coding required.
 - **WASM transforms** are custom WebAssembly modules that developers build and deploy. Use them when you need logic that the built-in transforms don't cover.
 
 Both kinds of transforms run inside the same `DataflowGraph` resource and can be mixed in a single pipeline. For information on building and deploying custom transforms, see [Use WASM transforms in data flow graphs](howto-dataflow-graph-wasm.md).

articles/iot-operations/connect-to-cloud/howto-create-dataflow-graph.md

@@ -6,7 +6,7 @@ ms.author: sethm
 ms.service: azure-iot-operations
 ms.subservice: azure-data-flows
 ms.topic: how-to
-ms.date: 03/19/2026
+ms.date: 04/02/2026
 ai-usage: ai-assisted
 
 #CustomerIntent: As an operator, I want to create a data flow graph to process data with transforms like map, filter, and window.
@@ -49,7 +49,7 @@ A data flow graph contains three types of elements: **sources** that bring data
 
        :::image type="content" source="media/howto-create-dataflow-graph/source-configuration.png" alt-text="Screenshot of the operations experience source configuration panel showing endpoint dropdown and topic input." lightbox="media/howto-create-dataflow-graph/source-configuration.png":::
 
-       1. **Add transforms**: Select one or more transforms to process the data. Available transforms include map, filter, branch, concat, and window. For details on each transform type, see [Data flow graphs overview](concept-dataflow-graphs.md#available-transforms).
+       1. **Add transforms**: Select one or more transforms to process the data. Available transforms include map, filter, branch, concatenate, and window. For details on each transform type, see [Data flow graphs overview](concept-dataflow-graphs.md#available-transforms).
 
        :::image type="content" source="media/howto-create-dataflow-graph/transform-selection.png" alt-text="Screenshot of the operations experience transform selection menu showing available transform types." lightbox="media/howto-create-dataflow-graph/transform-selection.png":::
 
@@ -275,7 +275,7 @@ The available built-in transforms are:
 | Map | `azureiotoperations/graph-dataflow-map:1.0.0` | Rename, restructure, compute, and copy fields |
 | Filter | `azureiotoperations/graph-dataflow-filter:1.0.0` | Drop messages that match a condition |
 | Branch | `azureiotoperations/graph-dataflow-branch:1.0.0` | Route messages to a `true` or `false` path |
-| Concat | `azureiotoperations/graph-dataflow-concatenate:1.0.0` | Merge branched paths back together |
+| Concatenate | `azureiotoperations/graph-dataflow-concatenate:1.0.0` | Merge branched paths back together |
 | Window | `azureiotoperations/graph-dataflow-window:1.0.0` | Aggregate data over a time interval |
 
 For detailed configuration of each transform type, see:

articles/iot-operations/connect-to-cloud/howto-dataflow-graphs-enrich.md

@@ -6,7 +6,7 @@ ms.author: sethm
 ms.service: azure-iot-operations
 ms.subservice: azure-data-flows
 ms.topic: how-to
-ms.date: 03/19/2026
+ms.date: 04/02/2026
 ai-usage: ai-assisted
 
 ---
@@ -274,7 +274,6 @@ resource dataflowGraph 'Microsoft.IoTOperations/instances/dataflowProfiles/dataf
   name: 'enrich-example'
   parent: dataflowProfile
   properties: {
-    profileRef: dataflowProfileName
     mode: 'Enabled'
     nodes: [
       {

articles/iot-operations/connect-to-cloud/howto-dataflow-graphs-filter-route.md

@@ -6,14 +6,14 @@ ms.author: sethm
 ms.service: azure-iot-operations
 ms.subservice: azure-data-flows
 ms.topic: how-to
-ms.date: 03/13/2026
+ms.date: 04/02/2026
 ai-usage: ai-assisted
 
 ---
 
 # Filter and route data in data flow graphs
 
-Data flow graphs provide two ways to control which messages flow through your pipeline: **filter** transforms drop unwanted messages, and **branch** transforms route each message down one of two paths based on a condition. After branching, a **concat** transform merges the paths back together.
+Data flow graphs provide two ways to control which messages flow through your pipeline: **filter** transforms drop unwanted messages, and **branch** transforms route each message down one of two paths based on a condition. After branching, a **concatenate** transform merges the paths back together.
 
 For an overview of data flow graphs and how transforms compose in a pipeline, see [Data flow graphs overview](concept-dataflow-graphs.md).
 
@@ -266,7 +266,7 @@ Key constraints:
 - **Exactly one branch rule.** The `branch` key takes a single object, not an array.
 
 > [!IMPORTANT]
-> Branching splits messages into separate processing paths, but all paths must merge back together using a concat transform before reaching the destination. Think of branching as a way to apply different transformations to different messages, not as a way to route to multiple endpoints.
+> Branching splits messages into separate processing paths, but all paths must merge back together using a concatenate transform before reaching the destination. Think of branching as a way to apply different transformations to different messages, not as a way to route to multiple endpoints.
 
 ### Define a branch rule
 
@@ -344,13 +344,13 @@ nodeConnections:
 
 ---
 
-## Merge paths with concat
+## Merge paths with concatenate
 
-All branch paths must converge before reaching a destination. A concat transform merges them. It has no configuration and no rules. Messages from all connected inputs pass through unmodified.
+All branch paths must converge before reaching a destination. A concatenate transform merges them. It has no configuration and no rules. Messages from all connected inputs pass through unmodified.
 
 # [Operations experience](#tab/portal)
 
-Add a concat transform to the canvas and connect both branch paths to it, then connect the concat to the destination.
+Add a concatenate transform to the canvas and connect both branch paths to it, then connect the concatenate to the destination.
 
 # [Bicep](#tab/bicep)
 
@@ -394,9 +394,9 @@ To build this pipeline in the Operations experience:
 1. Add a **branch** transform. Configure the condition `severity > 5` to route high-severity messages to the true path.
 1. Add a **map** transform on the true path. Configure rules to rename `deviceId` to `id`, `temperature` to `temp`, and add a field `alert` set to `true`.
 1. Add a **map** transform on the false path. Configure rules to rename `deviceId` to `id` and `temperature` to `temp`.
-1. Add a **concat** transform to merge both paths.
+1. Add a **concatenate** transform to merge both paths.
 1. Add a **destination** that sends to `telemetry/processed`.
-1. Connect the elements: source → filter → branch → (true path: alert map, false path: normal map) → concat → destination.
+1. Connect the elements: source → filter → branch → (true path: alert map, false path: normal map) → concatenate → destination.
 
 # [Bicep](#tab/bicep)
 

articles/iot-operations/connect-to-cloud/howto-dataflow-graphs-map.md

@@ -6,7 +6,7 @@ ms.author: sethm
 ms.service: azure-iot-operations
 ms.subservice: azure-data-flows
 ms.topic: how-to
-ms.date: 03/26/2026
+ms.date: 04/02/2026
 ai-usage: ai-assisted
 
 ---
@@ -546,7 +546,6 @@ resource dataflowGraph 'Microsoft.IoTOperations/instances/dataflowProfiles/dataf
   name: 'temperature-map-example'
   parent: dataflowProfile
   properties: {
-    profileRef: dataflowProfileName
     mode: 'Enabled'
     nodes: [
       {

articles/iot-operations/connect-to-cloud/howto-dataflow-graphs-topic-routing.md

@@ -6,7 +6,7 @@ ms.author: sethm
 ms.service: azure-iot-operations
 ms.subservice: azure-data-flows
 ms.topic: how-to
-ms.date: 03/13/2026
+ms.date: 04/02/2026
 ai-usage: ai-assisted
 
 ---
@@ -151,7 +151,7 @@ spec:
 
 ## Option 2: Branch, map each path, and merge
 
-If you need different transformations on each path (not just a different topic), use a branch transform to split the flow, a map transform on each arm to set the topic and apply path-specific rules, and a concat transform to merge the paths.
+If you need different transformations on each path (not just a different topic), use a branch transform to split the flow, a map transform on each arm to set the topic and apply path-specific rules, and a concatenate transform to merge the paths.
 
 # [Operations experience](#tab/portal)
 
@@ -161,7 +161,7 @@ In the Operations experience:
 1. Add a **branch** transform with condition `$1 > 1000` on the `temperature` field.
 1. On the **true** path, add a **map** transform with a wildcard passthrough and a rule that sets `$metadata.topic` to `"alerts"`.
 1. On the **false** path, add a **map** transform with a wildcard passthrough and a rule that sets `$metadata.topic` to `"historian"`.
-1. Add a **concat** transform to merge both paths.
+1. Add a **concatenate** transform to merge both paths.
 1. Add a **destination** with topic `factory/${outputTopic}`.
 
 # [Bicep](#tab/bicep)

articles/iot-operations/connect-to-cloud/howto-dataflow-graphs-window.md

@@ -6,7 +6,7 @@ ms.author: sethm
 ms.service: azure-iot-operations
 ms.subservice: azure-data-flows
 ms.topic: how-to
-ms.date: 03/19/2026
+ms.date: 04/02/2026
 ai-usage: ai-assisted
 
 ---
@@ -231,7 +231,6 @@ resource dataflowGraph 'Microsoft.IoTOperations/instances/dataflowProfiles/dataf
   name: 'temperature-window'
   parent: dataflowProfile
   properties: {
-    profileRef: dataflowProfileName
     mode: 'Enabled'
     nodes: [
       {

articles/iot-operations/connect-to-cloud/overview-dataflow-comparison.md

@@ -6,7 +6,7 @@ ms.author: sethm
 ms.service: azure-iot-operations
 ms.subservice: azure-data-flows
 ms.topic: concept-article
-ms.date: 03/19/2026
+ms.date: 04/02/2026
 ai-usage: ai-assisted
 
 #CustomerIntent: As an operator, I want to understand when to use data flows vs. data flow graphs.
@@ -33,8 +33,8 @@ Data flow graphs support MQTT, Kafka, and OpenTelemetry endpoints.
 | Feature | Data flows | Data flow graphs |
 |---------|-----------|-----------------|
 | Pipeline shape | Fixed: enrich, filter, map | Flexible: any graph topology |
-| Transforms | Map, filter, enrich | Map, filter, branch, concat, window (aggregation), enrich |
-| Branch and merge | Not supported | Branch on conditions, merge with concat |
+| Transforms | Map, filter, enrich | Map, filter, branch, concatenate, window (aggregation), enrich |
+| Branch and merge | Not supported | Branch on conditions, merge with concatenate |
 | Time-based aggregation | Not supported | Tumbling windows with avg, min, max, count |
 | Endpoint support (source) | MQTT, Kafka | MQTT, Kafka, OpenTelemetry |
 | Endpoint support (destination) | MQTT, Kafka, ADLS, Fabric, ADX, local storage, OpenTelemetry | MQTT, Kafka, OpenTelemetry |

articles/iot-operations/develop-edge-apps/howto-configure-registry-endpoint.md

@@ -5,7 +5,7 @@ author: sethmanheim
 ms.author: sethm
 ms.service: azure-iot-operations
 ms.topic: how-to
-ms.date: 03/25/2026
+ms.date: 04/02/2026
 ai-usage: ai-assisted
 
 #CustomerIntent: As an operator, I want to understand how to configure registry endpoints in Azure IoT Operations so that I can pull custom connectors, WASM modules, and graph definitions from container registries for use in data flow graphs and connectors.
@@ -457,7 +457,7 @@ spec:
 
 ---
 
-The built-in data flow graph transforms (map, filter, branch, concat, window) use this endpoint to pull processing artifacts from MCR. When you use `registryEndpointRef: default` in a `DataflowGraph` resource, no extra registry configuration is needed. For more information about built-in transforms, see [Data flow graphs overview](../connect-to-cloud/concept-dataflow-graphs.md).
+The built-in data flow graph transforms (map, filter, branch, concatenate, window) use this endpoint to pull processing artifacts from MCR. When you use `registryEndpointRef: default` in a `DataflowGraph` resource, no extra registry configuration is needed. For more information about built-in transforms, see [Data flow graphs overview](../connect-to-cloud/concept-dataflow-graphs.md).
 
 > [!NOTE]
 > For custom WASM transforms or third-party artifacts, you need to create a separate registry endpoint that points to the registry where your artifacts are stored.