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Sreekanth Iyer (Ushta Te Consultancy Services) · Sreekanth Iyer (Ushta Te Consultancy Services) · commit 1c1b86c72e31 · 2024-06-05T15:29:10.000+05:30
diff --git a/articles/hdinsight-aks/hdinsight-on-aks-autoscale-clusters.md b/articles/hdinsight-aks/hdinsight-on-aks-autoscale-clusters.md
@@ -8,7 +8,6 @@ ms.date: 02/06/2024
 
 # Auto Scale HDInsight on AKS Clusters
 
-[!INCLUDE [feature-in-preview](includes/feature-in-preview.md)]
 
 The sizing of any cluster to meet job performance and manage costs ahead of time is always tricky, and hard to determine! One of the lucrative benefits of building data lake house over Cloud is its elasticity, which means to use autoscale feature to maximize the utilization of resources at hand. Auto scale with Kubernetes is one key to establishing a cost optimized ecosystem. With varied usage patterns in any enterprise, there could be variations in cluster loads over time that could lead to clusters being under-provisioned (lousy performance) or overprovisioned (unnecessary costs due to idle resources).  
 
diff --git a/articles/hdinsight-aks/how-to-azure-monitor-integration.md b/articles/hdinsight-aks/how-to-azure-monitor-integration.md
@@ -8,8 +8,6 @@ ms.date: 08/29/2023
 
 # How to integrate with Log Analytics
 
-[!INCLUDE [feature-in-preview](includes/feature-in-preview.md)]
-
 This article describes how to enable Log Analytics to monitor & collect logs for cluster pool and cluster operations on HDInsight on AKS. You can enable the integration during cluster pool creation or post the creation.
 Once the integration at cluster pool is enabled, it isn't possible to disable the integration. However, you can disable the log analytics for individual clusters, which are part of the same pool.
 
diff --git a/articles/hdinsight-aks/manage-cluster-pool.md b/articles/hdinsight-aks/manage-cluster-pool.md
@@ -8,8 +8,6 @@ ms.date: 08/29/2023
 
 # Manage cluster pools
 
-[!INCLUDE [feature-in-preview](includes/feature-in-preview.md)]
-
 Cluster pools are a logical grouping of clusters and maintain a set of clusters in the same pool. It helps in building robust interoperability across multiple cluster types and allow enterprises to have the clusters in the same virtual network. One cluster pool corresponds to one cluster in AKS infrastructure. 
 
 This article describes how to manage a cluster pool. 
diff --git a/articles/hdinsight-aks/manage-cluster.md b/articles/hdinsight-aks/manage-cluster.md
@@ -8,8 +8,6 @@ ms.date: 08/29/2023
 
 # Manage clusters
 
-[!INCLUDE [feature-in-preview](includes/feature-in-preview.md)]
-
 Clusters are individual compute workloads such as Apache Spark, Apache Flink, and Trino, which can be created rapidly in few minutes with preset configurations and few clicks.
 
 This article describes how to manage a cluster using Azure portal. 
diff --git a/articles/hdinsight-aks/manage-script-actions.md b/articles/hdinsight-aks/manage-script-actions.md
@@ -7,8 +7,6 @@ ms.date: 08/29/2023
 ---
 # Script actions during cluster creation
 
-[!INCLUDE [feature-in-preview](includes/feature-in-preview.md)]
-
 Azure HDInsight on AKS provides a mechanism called **Script Actions** that invoke custom scripts to customize the cluster. These scripts are used to install additional components and change configuration settings. Script actions can be provisioned only during cluster creation as of now. Post cluster creation, Script Actions are part of the roadmap.
 This article explains how you can provision script actions when you create an HDInsight on AKS cluster.
 
diff --git a/articles/hdinsight-aks/manual-scale.md b/articles/hdinsight-aks/manual-scale.md
@@ -8,8 +8,6 @@ ms.date: 02/06/2024
 
 # Manual scale
 
-[!INCLUDE [feature-in-preview](includes/feature-in-preview.md)]
-
 HDInsight on AKS provides elasticity with options to scale up and scale down the number of cluster nodes. This elasticity works to help increase resource utilization and improve cost efficiency.
 
 ## Utility to scale clusters
diff --git a/articles/hdinsight-aks/secure-traffic-by-firewall-azure-portal.md b/articles/hdinsight-aks/secure-traffic-by-firewall-azure-portal.md
@@ -8,8 +8,6 @@ ms.date: 08/3/2023
 
 # Use firewall to restrict outbound traffic using Azure portal
 
-[!INCLUDE [feature-in-preview](includes/feature-in-preview.md)]
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 When an enterprise wants to use their own virtual network for the cluster deployments, securing the traffic of the virtual network becomes important.
 This article provides the steps to secure outbound traffic from your HDInsight on AKS cluster via Azure Firewall using Azure portal.
 
diff --git a/articles/hdinsight-aks/secure-traffic-by-firewall.md b/articles/hdinsight-aks/secure-traffic-by-firewall.md
@@ -9,7 +9,6 @@ ms.date: 02/19/2024
 
 # Use firewall to restrict outbound traffic using Azure CLI
 
-[!INCLUDE [feature-in-preview](includes/feature-in-preview.md)]
 
 When an enterprise wants to use their own virtual network for the cluster deployments, securing the traffic of the virtual network becomes important.
 This article provides the steps to secure outbound traffic from your HDInsight on AKS cluster via Azure Firewall using [Azure CLI](/azure/cloud-shell/quickstart?tabs=azurecli).
diff --git a/articles/hdinsight-aks/secure-traffic-by-nsg.md b/articles/hdinsight-aks/secure-traffic-by-nsg.md
@@ -8,8 +8,6 @@ ms.date: 08/3/2023
 
 # Use NSG to restrict traffic to HDInsight on AKS
 
-[!INCLUDE [feature-in-preview](includes/feature-in-preview.md)]
-
 HDInsight on AKS relies on AKS outbound dependencies and they're entirely defined with FQDNs, which don't have static addresses behind them. The lack of static IP addresses means one can't use Network Security Groups (NSGs) to lock down the outbound traffic from the cluster using IPs. 
 
 If you still prefer to use NSG to secure your traffic, then you need to configure the following rules in the NSG to do a coarse-grained control. 

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`@@ -8,7 +8,6 @@ ms.date: 02/06/2024`
`8`	`8`
`9`	`9`	`# Auto Scale HDInsight on AKS Clusters`
`10`	`10`
`11`		`-[!INCLUDE [feature-in-preview](includes/feature-in-preview.md)]`
`12`	`11`
`13`	`12`	The sizing of any cluster to meet job performance and manage costs ahead of time is always tricky, and hard to determine! One of the lucrative benefits of building data lake house over Cloud is its elasticity, which means to use autoscale feature to maximize the utilization of resources at hand. Auto scale with Kubernetes is one key to establishing a cost optimized ecosystem. With varied usage patterns in any enterprise, there could be variations in cluster loads over time that could lead to clusters being under-provisioned (lousy performance) or overprovisioned (unnecessary costs due to idle resources).
`14`	`13`