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fit and finish 101

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This commit is contained in:
Dennis Eikelenboom 2021-09-20 10:41:09 -07:00
parent 5c6087899a
commit ae58331e4e
7 changed files with 15 additions and 9 deletions
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.gitignore vendored Normal file
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@ -0,0 +1,4 @@
quickstart/101-machine-learning/.terraform.lock.hcl
quickstart/101-machine-learning/.terraform/providers/registry.terraform.io/hashicorp/azurerm/2.76.0/windows_amd64/terraform-provider-azurerm_v2.76.0_x5.exe
quickstart/101-machine-learning/terraform.tfstate
quickstart/101-machine-learning/demo.tfplan

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quickstart/101-machine-learning/compute.tf
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@ -8,7 +8,7 @@ resource "azurerm_machine_learning_compute_instance" "compute_instance" {
# Compute Cluster
resource "azurerm_machine_learning_compute_cluster" "compute" {
name = "default-compute"
name = "cpu-cluster"
location = azurerm_resource_group.default.location
machine_learning_workspace_id = azurerm_machine_learning_workspace.default.id
vm_priority = "Dedicated"
@ -21,7 +21,7 @@ resource "azurerm_machine_learning_compute_cluster" "compute" {
scale_settings {
min_node_count = 0
max_node_count = 3
scale_down_nodes_after_idle_duration = "PT10M" # 10 minutes
scale_down_nodes_after_idle_duration = "PT15M" # 15 minutes
}
}

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quickstart/101-machine-learning/readme.md
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@ -31,6 +31,8 @@ Network connectivity to the workspace is allowed over public endpoints, making t
## Usage
```bash
terraform init
terraform plan -var name=azureml567 -out demo.tfplan
terraform apply "demo.tfplan"

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quickstart/201-machine-learning-moderately-secure/readme.md
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@ -6,7 +6,7 @@ and its associated resources including Azure Key Vault, Azure Storage, Azure App
In addition to these core services, this configuration specifies any networking components that are required to set up Azure Machine Learning
for private network connectivity using [Azure Private Link](https://docs.microsoft.com/en-us/azure/private-link/).
This configuration describes the minimal set of resources you require to get started with Azure Machine Learning in a network-isolated set-up.
This configuration describes the minimal set of resources you require to get started with Azure Machine Learning in a network-isolated set-up. This configuration creates new network components. If you want to reuse existing network components, see [202 example](../201-machine-learning-moderately-secure/readme.md).
## Resources

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quickstart/201-machine-learning-moderately-secure/workspace.tf
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@ -169,7 +169,7 @@ resource "azurerm_machine_learning_compute_cluster" "image-builder" {
scale_settings {
min_node_count = 0
max_node_count = 1
max_node_count = 3
scale_down_nodes_after_idle_duration = "PT15M" # 15 minutes
}

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quickstart/202-machine-learning-moderately-secure-existing-VNet/readme.md
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@ -1,4 +1,4 @@
# Azure Machine Learning workspace (moderately secure network set up)
# Azure Machine Learning workspace (moderately secure network set up - existing virtual network)
This deployment configuration specifies an [Azure Machine Learning workspace](https://docs.microsoft.com/en-us/azure/machine-learning/concept-workspace),
and its associated resources including Azure Key Vault, Azure Storage, Azure Application Insights and Azure Container Registry.
@ -6,9 +6,7 @@ and its associated resources including Azure Key Vault, Azure Storage, Azure App
In addition to these core services, this configuration specifies any networking components that are required to set up Azure Machine Learning
for private network connectivity using [Azure Private Link](https://docs.microsoft.com/en-us/azure/private-link/).
This configuration describes the minimal set of resources you require to get started with Azure Machine Learning in a network-isolated set-up.
To learn more about security configurations in Azure Machine Learning, see [Enterprise security and governance for Azure Machine Learning](https://docs.microsoft.com/en-us/azure/machine-learning/concept-enterprise-security).
This configuration describes the minimal set of resources you require to get started with Azure Machine Learning in a network-isolated set-up. This configurations assumes that you have existing network components to reuse. The [201 example](../201-machine-learning-moderately-secure/readme.md), alternatively creates new network components.
## Resources
@ -51,6 +49,8 @@ To learn more about security configurations in Azure Machine Learning, see [Ente
## Usage
```bash
terraform init
terraform plan -var name=azureml567 -out demo.tfplan
terraform apply "demo.tfplan"

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quickstart/202-machine-learning-moderately-secure-existing-VNet/workspace.tf
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@ -172,7 +172,7 @@ resource "azurerm_machine_learning_compute_cluster" "image-builder" {
scale_settings {
min_node_count = 0
max_node_count = 1
max_node_count = 3
scale_down_nodes_after_idle_duration = "PT15M" # 15 minutes
}