Modelos de Início Rápido do Azure
Implemente recursos do Azure através do Gestor de Recursos do Azure com modelos fornecidos pela comunidade para produzir mais. Implemente, aprenda, distribua e contribua de volta.
O que é o Gestor de Recursos do Azure
O Gestor de Recursos do Azure permite utilizar modelos declarativos para aprovisionar as suas aplicações. Num único modelo, pode implementar vários serviços, bem como as respetivas dependências. Pode utilizar o mesmo modelo para implementar repetidamente a sua aplicação durante cada fase do ciclo de vida da aplicação.
- Tudo
- Microsoft.Aad (1)
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- Microsoft.Compute (391)
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A mostrar todos os 13 modelos. Refinar os resultados com a pesquisa.
Create an Azure Machine Learning service workspace.
This deployment template specifies an Azure Machine Learning workspace, and its associated resources including Azure Key Vault, Azure Storage, Azure Application Insights and Azure Container Registry. This configuration describes the set of resources you require to get started with Azure Machine Learning in a network isolated set up.
Import Container Images into ACR
This template leverages the Import ACR module from the bicep registry to import public container images into an Azure Container Registry.
Create an Azure Machine Learning service workspace.
This deployment template specifies an Azure Machine Learning workspace, and its associated resources including Azure Key Vault, Azure Storage, Azure Application Insights and Azure Container Registry. This configuration describes the set of resources you require to get started with Azure Machine Learning in a network isolated set up.
AKS Cluster with a NAT Gateway and an Application Gateway
This sample shows how to a deploy an AKS cluster with NAT Gateway for outbound connections and an Application Gateway for inbound connections.
Azure Container Registry with Policies and Diagnostics
Azure Container Registry with Policies and Diagnostics (bicep)
Azure Container Registry with Geo-replication Template
A template for creating a new Azure Container Registry with geo-replication
Create an Azure Machine Learning service workspace.
This deployment template specifies an Azure Machine Learning workspace, and its associated resources including Azure Key Vault, Azure Storage, Azure Application Insights and Azure Container Registry. The example shows how to configure Azure Machine Learning for encryption with a customer-managed encryption key.
Create an Azure Machine Learning service workspace.
This deployment template specifies an Azure Machine Learning workspace, and its associated resources including Azure Key Vault, Azure Storage, Azure Application Insights and Azure Container Registry. This configuration describes the minimal set of resources you require to get started with Azure Machine Learning.
Create a Private AKS Cluster with a Public DNS Zone
This sample shows how to a deploy a private AKS cluster with a Public DNS Zone.
AKS cluster with the Application Gateway Ingress Controller
This sample shows how to deploy an AKS cluster with Application Gateway, Application Gateway Ingress Controller, Azure Container Registry, Log Analytics and Key Vault
CI/CD using Jenkins on Azure Container Service (AKS)
Containers make it very easy for you to continuously build and deploy your applications. By orchestrating deployment of those containers using Kubernetes in Azure Container Service, you can achieve replicable, manageable clusters of containers. By setting up a continuous build to produce your container images and orchestration, you can increase the speed and reliability of your deployment.
Create an AKS compute target with a Private IP address.
This template creates an AKS compute target in given Azure Machine Learning service workspace with a private IP address.
Azure Container Registry Template
A template for creating a new Azure Container Registry.