Update VM size

Author: mihaelablendea

samples/features/sql-big-data-cluster/deployment/aks/README.md

@@ -42,8 +42,8 @@ python deploy-sql-big-data-aks.py
 
 When prompted, provide your input for Azure subscription ID, Azure resource group to create the resources in, and Docker credentials. Optionally, you can also provide your input for below configurations or use the defaults provided:
 - azure_region
-- vm_size - we recommend to use a VM size to accommodate your workload. For an optimal experience while you are validating basic scenarios, we recommend a VM with at least 4 vCPUs and 32GB memory. The script uses Standard_L4s` as default.
-- aks_node_count - this is the number of the worker nodes for the AKS cluster, excluding master node. The script is using a default of 3 agent nodes. This is the minimum required for this VM size to have enough data disks available to provision all the necessary persistent volumes.
+- vm_size - we recommend to use a VM size to accommodate your workload. For an optimal experience while you are validating basic scenarios, we recommend at least 8 vCPUs and 32GB memory across all agent nodes in the cluster. The script uses **Standard_L8s** as default.
+- aks_node_count - this is the number of the worker nodes for the AKS cluster, excluding master node. The script is using a default of 1 agent node. This is the minimum required for this VM size to have enough resources and disks to provision all the necessary persistent volumes.
 - cluster_name - this value is used for both AKS cluster and SQL big data cluster created on top of AKS. Note that the name of the SQL big data cluster is going to be a Kubernetes namespace
 - password - same value is going to be used for all accounts that require user password input: SQL Server master instance SA account, controller user and Knox user
 - controller_username - this is the username for the cluster admin account