Add notice about using Kubernetes to manage resources

jlian · jlian · commit 4d3681342902 · 2024-11-08T14:21:43.000-08:00
diff --git a/articles/iot-operations/connect-to-cloud/concept-dataflow-conversions.md b/articles/iot-operations/connect-to-cloud/concept-dataflow-conversions.md
@@ -13,6 +13,8 @@ ms.service: azure-iot-operations
 
 # Convert data by using dataflow conversions
 
+[!INCLUDE [kubernetes-management-preview-note](../includes/kubernetes-management-preview-note.md)]
+
 You can use dataflow conversions to transform data in Azure IoT Operations. The *conversion* element in a dataflow is used to compute values for output fields. You can use input fields, available operations, data types, and type conversions in dataflow conversions.
 
 The dataflow conversion element is used to compute values for output fields:
diff --git a/articles/iot-operations/connect-to-cloud/concept-dataflow-enrich.md b/articles/iot-operations/connect-to-cloud/concept-dataflow-enrich.md
@@ -13,6 +13,8 @@ ms.service: azure-iot-operations
 
 # Enrich data by using dataflows
 
+[!INCLUDE [kubernetes-management-preview-note](../includes/kubernetes-management-preview-note.md)]
+
 You can enrich data by using the *contextualization datasets* function. When incoming records are processed, you can query these datasets based on conditions that relate to the fields of the incoming record. This capability allows for dynamic interactions. Data from these datasets can be used to supplement information in the output fields and participate in complex calculations during the mapping process.
 
 For example, consider the following dataset with a few records, represented as JSON records:
diff --git a/articles/iot-operations/connect-to-cloud/concept-dataflow-mapping.md b/articles/iot-operations/connect-to-cloud/concept-dataflow-mapping.md
@@ -14,6 +14,8 @@ ms.service: azure-iot-operations
 
 # Map data by using dataflows
 
+[!INCLUDE [kubernetes-management-preview-note](../includes/kubernetes-management-preview-note.md)]
+
 Use the dataflow mapping language to transform data in Azure IoT Operations. The syntax is a simple, yet powerful, way to define mappings that transform data from one format to another. This article provides an overview of the dataflow mapping language and key concepts.
 
 Mapping allows you to transform data from one format to another. Consider the following input record:
diff --git a/articles/iot-operations/connect-to-cloud/howto-configure-adlsv2-endpoint.md b/articles/iot-operations/connect-to-cloud/howto-configure-adlsv2-endpoint.md
@@ -14,6 +14,8 @@ ai-usage: ai-assisted
 
 # Configure dataflow endpoints for Azure Data Lake Storage Gen2
 
+[!INCLUDE [kubernetes-management-preview-note](../includes/kubernetes-management-preview-note.md)]
+
 To send data to Azure Data Lake Storage Gen2 in Azure IoT Operations, you can configure a dataflow endpoint. This configuration allows you to specify the destination endpoint, authentication method, table, and other settings.
 
 ## Prerequisites
diff --git a/articles/iot-operations/connect-to-cloud/howto-configure-adx-endpoint.md b/articles/iot-operations/connect-to-cloud/howto-configure-adx-endpoint.md
@@ -14,6 +14,8 @@ ai-usage: ai-assisted
 
 # Configure dataflow endpoints for Azure Data Explorer
 
+[!INCLUDE [kubernetes-management-preview-note](../includes/kubernetes-management-preview-note.md)]
+
 To send data to Azure Data Explorer in Azure IoT Operations, you can configure a dataflow endpoint. This configuration allows you to specify the destination endpoint, authentication method, table, and other settings.
 
 ## Prerequisites
diff --git a/articles/iot-operations/connect-to-cloud/howto-configure-dataflow-endpoint.md b/articles/iot-operations/connect-to-cloud/howto-configure-dataflow-endpoint.md
@@ -13,6 +13,8 @@ ms.date: 11/01/2024
 
 # Configure dataflow endpoints
 
+[!INCLUDE [kubernetes-management-preview-note](../includes/kubernetes-management-preview-note.md)]
+
 To get started with dataflows, first create dataflow endpoints. A dataflow endpoint is the connection point for the dataflow. You can use an endpoint as a source or destination for the dataflow. Some endpoint types can be used as both sources and destinations, while others are for destinations only. A dataflow needs at least one source endpoint and one destination endpoint.
 
 Use the following table to choose the endpoint type to configure:
diff --git a/articles/iot-operations/connect-to-cloud/howto-configure-dataflow-profile.md b/articles/iot-operations/connect-to-cloud/howto-configure-dataflow-profile.md
@@ -13,6 +13,8 @@ ms.date: 10/30/2024
 
 # Configure dataflow profile
 
+[!INCLUDE [kubernetes-management-preview-note](../includes/kubernetes-management-preview-note.md)]
+
 Dataflow profiles can be used to group dataflows together so that they share the same configuration. You can create multiple dataflow profiles to manage sets of different dataflow configurations. 
 
 The most important setting is the instance count, which determines the number of instances that run the dataflows. For example, you might have a dataflow profile with a single instance for development and testing, and another profile with multiple instances for production. Or, you might use a dataflow profile with low instance count for low-throughput dataflows and a profile with high instance count for high-throughput dataflows. Similarly, you can create a dataflow profile with different diagnostic settings for debugging purposes.
diff --git a/articles/iot-operations/connect-to-cloud/howto-configure-fabric-endpoint.md b/articles/iot-operations/connect-to-cloud/howto-configure-fabric-endpoint.md
@@ -14,6 +14,8 @@ ai-usage: ai-assisted
 
 # Configure dataflow endpoints for Microsoft Fabric OneLake
 
+[!INCLUDE [kubernetes-management-preview-note](../includes/kubernetes-management-preview-note.md)]
+
 To send data to Microsoft Fabric OneLake in Azure IoT Operations, you can configure a dataflow endpoint. This configuration allows you to specify the destination endpoint, authentication method, table, and other settings.
 
 ## Prerequisites
diff --git a/articles/iot-operations/connect-to-cloud/howto-configure-kafka-endpoint.md b/articles/iot-operations/connect-to-cloud/howto-configure-kafka-endpoint.md
@@ -14,6 +14,8 @@ ai-usage: ai-assisted
 
 # Configure Azure Event Hubs and Kafka dataflow endpoints
 
+[!INCLUDE [kubernetes-management-preview-note](../includes/kubernetes-management-preview-note.md)]
+
 To set up bi-directional communication between Azure IoT Operations and Apache Kafka brokers, you can configure a dataflow endpoint. This configuration allows you to specify the endpoint, Transport Layer Security (TLS), authentication, and other settings.
 
 ## Prerequisites
diff --git a/articles/iot-operations/connect-to-cloud/howto-configure-local-storage-endpoint.md b/articles/iot-operations/connect-to-cloud/howto-configure-local-storage-endpoint.md
@@ -14,6 +14,8 @@ ai-usage: ai-assisted
 
 # Configure dataflow endpoints for local storage
 
+[!INCLUDE [kubernetes-management-preview-note](../includes/kubernetes-management-preview-note.md)]
+
 To send data to local storage in Azure IoT Operations, you can configure a dataflow endpoint. This configuration allows you to specify the endpoint, authentication, table, and other settings.
 
 ## Prerequisites
diff --git a/articles/iot-operations/connect-to-cloud/howto-configure-mqtt-endpoint.md b/articles/iot-operations/connect-to-cloud/howto-configure-mqtt-endpoint.md
@@ -14,6 +14,8 @@ ai-usage: ai-assisted
 
 # Configure MQTT dataflow endpoints
 
+[!INCLUDE [kubernetes-management-preview-note](../includes/kubernetes-management-preview-note.md)]
+
 MQTT dataflow endpoints are used for MQTT sources and destinations. You can configure the endpoint settings, Transport Layer Security (TLS), authentication, and other settings.
 
 ## Prerequisites
diff --git a/articles/iot-operations/connect-to-cloud/howto-create-dataflow.md b/articles/iot-operations/connect-to-cloud/howto-create-dataflow.md
@@ -14,6 +14,8 @@ ai-usage: ai-assisted
 
 # Configure dataflows in Azure IoT Operations
 
+[!INCLUDE [kubernetes-management-preview-note](../includes/kubernetes-management-preview-note.md)]
+
 A dataflow is the path that data takes from the source to the destination with optional transformations. You can configure the dataflow by creating a *Dataflow* custom resource or using the Azure IoT Operations Studio portal. A dataflow is made up of three parts: the **source**, the **transformation**, and the **destination**. 
 
 <!--
diff --git a/articles/iot-operations/connect-to-cloud/tutorial-mqtt-bridge.md b/articles/iot-operations/connect-to-cloud/tutorial-mqtt-bridge.md
@@ -13,6 +13,8 @@ ms.date: 10/22/2024
 
 # Tutorial: Bi-directional MQTT bridge to Azure Event Grid
 
+[!INCLUDE [kubernetes-management-preview-note](../includes/kubernetes-management-preview-note.md)]
+
 In this tutorial, you set up a bi-directional MQTT bridge between an Azure IoT Operations MQTT broker and Azure Event Grid. To keep the tutorial simple, use the default settings for the Azure IoT Operations MQTT broker and Azure Event Grid endpoints, and no transformation is applied.
 
 ## Prerequisites
diff --git a/articles/iot-operations/deploy-iot-ops/howto-manage-update-uninstall.md b/articles/iot-operations/deploy-iot-ops/howto-manage-update-uninstall.md
@@ -129,6 +129,20 @@ az iot ops update --name <INSTANCE_NAME> --resource-group --tags ""
 
 ---
 
+### Manage components
+
+Each Azure IoT Operations instance includes several components, like the MQTT broker, OPC UA connector, and dataflows. To learn more about managing these components, see their respective articles. For example, to manage the MQTT broker, start with [Broker overview](../manage-mqtt-broker/overview-broker.md).
+
+### (Preview) Manage components using Kubernetes deployment manifests
+
+In general, Azure IoT Operations uses the Azure Arc platform to provide a hybrid cloud experience where you can manage the configuration through Azure Resource Manager (ARM) and front-end tools like the Azure portal, Bicep, and the Azure CLI.
+
+However, you can also manage the components of Azure IoT Operations using YAML Kubernetes deployment manifests. This means you can use tools like `kubectl` to manage some components of Azure IoT Operations. This feature is in preview and has some limitations:
+
+- Only some components support using Kubernetes deployment manifests. These components are the [MQTT broker](../manage-mqtt-broker/overview-broker.md) and [dataflows](../connect-to-cloud/overview-dataflow.md). Other components like the the OPC UA connector and Akri don't support this feature.
+- Unless Azure IoT Operations is [deployed with resource sync enabled using `az iot ops create --enable-rsync`](/cli/azure/iot/ops#az-iot-ops-create), changes made to the resources using Kubernetes deployment manifests are not synced to Azure. To learn more about resource sync, see [Resource sync](/azure/azure-arc/data/resource-sync).
+- Even if resource sync is enabled, brand new resources created using Kubernetes deployment manifests are not synced to Azure. Only changes to existing resources are synced.
+
 ## Uninstall
 
 The Azure CLI and Azure portal offer different options for uninstalling Azure IoT Operations.
diff --git a/articles/iot-operations/includes/kubernetes-management-preview-note.md b/articles/iot-operations/includes/kubernetes-management-preview-note.md
@@ -0,0 +1,16 @@
+---
+ title: include file
+ description: include file
+ author: jlian
+ ms.topic: include
+ ms.date: 11/08/2024
+ ms.author: jlian
+ms.custom:
+  - include file
+  - ignite-2024
+---
+
+> [!IMPORTANT]
+> This page includes instructions for managing Azure IoT Operations components using Kubernetes deployment manifests, which is in **preview**. This feature is provided with [several limitations](/azure/iot-operations/deploy-iot-ops/howto-manage-update-uninstall#preview-manage-components-using-kubernetes-deployment-manifests), and shouldn't be used for production workloads. 
+> 
+> See the [Supplemental Terms of Use for Microsoft Azure Previews](https://azure.microsoft.com/support/legal/preview-supplemental-terms/) for legal terms that apply to Azure features that are in beta, preview, or otherwise not yet released into general availability.
diff --git a/articles/iot-operations/manage-mqtt-broker/howto-configure-authentication.md b/articles/iot-operations/manage-mqtt-broker/howto-configure-authentication.md
@@ -15,6 +15,8 @@ ms.date: 11/02/2024
 
 # Configure MQTT broker authentication
 
+[!INCLUDE [kubernetes-management-preview-note](../includes/kubernetes-management-preview-note.md)]
+
 MQTT broker supports multiple authentication methods for clients, and you can configure each listener to have its own authentication system with *BrokerAuthentication* resources. For a list of the available settings, see the [Broker Authentication](/rest/api/iotoperationsmq/broker-authentication) API reference.
 
 ## Link BrokerListener and BrokerAuthentication
diff --git a/articles/iot-operations/manage-mqtt-broker/howto-configure-authorization.md b/articles/iot-operations/manage-mqtt-broker/howto-configure-authorization.md
@@ -15,6 +15,8 @@ ms.service: azure-iot-operations
 
 # Configure MQTT broker authorization
 
+[!INCLUDE [kubernetes-management-preview-note](../includes/kubernetes-management-preview-note.md)]
+
 Authorization policies determine what actions the clients can perform on the broker, such as connecting, publishing, or subscribing to topics. Configure MQTT broker to use one or multiple authorization policies with the *BrokerAuthorization* resource. Each *BrokerAuthorization* resource contains a list of rules that specify the principals and resources for the authorization policies.
 
 ## Link BrokerAuthorization to BrokerListener
diff --git a/articles/iot-operations/manage-mqtt-broker/howto-configure-brokerlistener.md b/articles/iot-operations/manage-mqtt-broker/howto-configure-brokerlistener.md
@@ -15,6 +15,8 @@ ms.date: 11/06/2024
 
 # Secure MQTT broker communication using BrokerListener
 
+[!INCLUDE [kubernetes-management-preview-note](../includes/kubernetes-management-preview-note.md)]
+
 To customize the network access and security use the BrokerListener resource. A listener corresponds to a network endpoint that exposes the broker to the network. You can have one or more BrokerListener resources for each Broker, and thus multiple ports with different access control each.
 
 Each listener port can have its own authentication and authorization rules that define who can connect to the listener and what actions they can perform on the broker. You can use [BrokerAuthentication](./howto-configure-authentication.md) and [BrokerAuthorization](./howto-configure-authorization.md) resources to specify the access control policies for each listener. This flexibility allows you to fine-tune the permissions and roles of your MQTT clients, based on their needs and use cases.
diff --git a/articles/iot-operations/manage-mqtt-broker/howto-test-connection.md b/articles/iot-operations/manage-mqtt-broker/howto-test-connection.md
@@ -15,6 +15,8 @@ ms.service: azure-iot-operations
 
 # Test connectivity to MQTT broker with MQTT clients
 
+[!INCLUDE [kubernetes-management-preview-note](../includes/kubernetes-management-preview-note.md)]
+
 This article shows different ways to test connectivity to MQTT broker with MQTT clients in a nonproduction environment.
 
 By default, MQTT broker:
diff --git a/articles/iot-operations/manage-mqtt-broker/overview-broker.md b/articles/iot-operations/manage-mqtt-broker/overview-broker.md
@@ -15,6 +15,8 @@ ms.service: azure-iot-operations
 
 # Azure IoT Operations built-in local MQTT broker
 
+[!INCLUDE [kubernetes-management-preview-note](../includes/kubernetes-management-preview-note.md)]
+
 Azure IoT Operations features an enterprise-grade, standards-compliant MQTT broker that is scalable, highly available, and Kubernetes-native. It provides the messaging plane for Azure IoT Operations Preview, enables bi-directional edge/cloud communication and powers [event-driven applications](/azure/architecture/guide/architecture-styles/event-driven) at the edge.
 
 ## MQTT compliance
