This post has been republished via RSS; it originally appeared at: New blog articles in Microsoft Tech Community.
Over the last few days a significant amount of new documents have been released to support all the new features, new products and services announced at the Microsoft Build 2022 conference. This post was designed for you to be able to find content relevant and aligned to your interests. You can use the Table Of Content or your browser built-in search tool (in most browsers click on Ctrl+f to open the search box).
| Note! This post focus on the English documents, but there are versions in other languages including: Arabic, Japanese, Bahasa Indonesia, Korean, Chinese (Simplified), Hungarian, Chinese (Traditional) Polish, Czech, Portuguese, Dutch, Portuguese (Brazilian), English, Russian, French, Spanish, German, Swedish, Italian, Turkish |
Table Of Content
- Application Development: .NET: MAUI
- Application Development: AKS: DAPR
- Application Development: AKS
- Application Development: App Service
- Application Development: Arc Enabled Servers
- Application Development: Arc for Kuberetes
- Application Development: Arc for Kubernetes
- Application Development: Communication Services
- Application Development: Container Apps
- Application Development: Event Hubs
- Application Development: Functions
- Application Development: nginx
- Application Development: Service Bus: Messaging
- Application Development: Service Connector
- Application Development: Spring Cloud
- Application Development
- Data & AI: .NET: ADO.NET
- Data & AI: Azure Arc for Data
- Data & AI: Azure Data Factory
- Data & AI: Azure Data Studio
- Data & AI: Azure Monitor
- Data & AI: Azure SQL
- Data & AI: Cognitive Services: Language Services
- Data & AI: Cognitive Services: Open AI
- Data & AI: Cognitive Services: Translator
- Data & AI: Cosmos DB
- Data & AI: Machine Learning
- Data & AI: MySQL
- Data & AI: Open Datasets
- Data & AI: Purview
- Data & AI: Search: Machine Learning
- Data & AI: SQL Server
- Data & AI: Stream Analytics
- Data & AI: Synapse Analytics
- Data & AI: Visual Studio Code: SQL Server Tooling
- Identity: Active Directory
- Identity: Azure Active Directory: Permissions Consent
- Security: Sentinel
Don't see what you're looking for? View entire directory
Product & Services Directory
Application Development: .NET: MAUI
Application Development: AKS: DAPR
Application Development: AKS
- Deploy and manage cluster extensions for Azure Kubernetes Service (AKS)
- Customize node configuration for Azure Kubernetes Service (AKS) node pools
- Draft for Azure Kubernetes Service (AKS) (preview)
- Use GPUs for compute-intensive workloads on Azure Kubernetes Service (AKS)
- Add-ons, extensions, and other integrations with Azure Kubernetes Service
- Simplified application autoscaling with Kubernetes Event-driven Autoscaling (KEDA) add-on (Preview)
- Create a Windows Server container on an Azure Kubernetes Service (AKS) cluster using the Azure CLI
- Quickstart: Deploy an application using the Dapr cluster extension for Azure Kubernetes Service (AKS) or Arc-enabled Kubernetes
- Supported Kubernetes versions in Azure Kubernetes Service (AKS)
- Tutorial: Upgrade Kubernetes in Azure Kubernetes Service (AKS)
- Upgrade an Azure Kubernetes Service (AKS) cluster
- Create and manage multiple node pools for a cluster in Azure Kubernetes Service (AKS)
- Web Application Routing (Preview)
Application Development: App Service
Application Development: Arc Enabled Servers
- Azure Arc-enabled servers Azure landing zone sandbox
- Network topology and connectivity for Azure Arc-enabled servers
- Automation disciplines for Azure Arc-enabled servers
- Cost governance for Azure Arc-enabled servers
- Identity and access management for Azure Arc-enabled servers
- Management and monitoring for Azure Arc-enabled servers
- Resource organization for Azure Arc-enabled servers
- Governance, security, and compliance baseline for Azure Arc-enabled servers
Application Development: Arc for Kuberetes
- Deploy and manage Azure Arc-enabled Kubernetes cluster extensions
- What is Azure Arc-enabled Kubernetes?
Application Development: Arc for Kubernetes
- Azure Arc-enabled Kubernetes Azure landing zone sandbox
- Automation for Azure Arc-enabled Kubernetes
- CI/CD and GitOps disciplines with Azure Arc-enabled Kubernetes
- Cost governance for Azure Arc-enabled Kubernetes
- Extensions management for Azure Arc-enabled Kubernetes
- Governance, security, and compliance baseline for Azure Arc-enabled Kubernetes
- Identity and access management for Azure Arc-enabled Kubernetes
- Management and monitoring for Azure Arc-enabled Kubernetes
- Network connectivity for Azure Arc-enabled Kubernetes
- Resource organization for Azure Arc-enabled Kubernetes
- Services observability for Azure Arc-enabled Kubernetes
Application Development: Communication Services
- Best practices for sender authentication support in Azure Communication Services Email
- Email domains and sender authentication for Azure Communication Services
- Email in Azure Communication Services
- Prepare Email Communication resource for Azure Communication Service
- Email client library overview for Azure Communication Services
- Email pricing in Azure Communication Services
- Number types
- Subscription eligibility and number capabilities
- Pricing Scenarios
- Telephony (PSTN) pricing
- SMS FAQ
- SMS Pricing
- Quickstart: How to add Azure Managed Domains to Email Communication Service
- Quickstart: How to add custom verified domains to Email Communication Service
- Quickstart: How to connect a verified email domain with Azure Communication Service resource
- Quickstart - Create and manage Email Communication Service resource in Azure Communication Service
- Quickstart: How to send an email using Azure Communication Service
Application Development: Container Apps
- Application lifecycle management in Azure Container Apps
- Enable authentication and authorization in Azure Container Apps with Azure Active Directory
- Enable authentication and authorization in Azure Container Apps with Facebook
- Enable authentication and authorization in Azure Container Apps with GitHub
- Enable authentication and authorization in Azure Container Apps with Google
- Enable authentication and authorization in Azure Container Apps with a Custom OpenID Connect provider
- Enable authentication and authorization in Azure Container Apps with Twitter
- Authentication and authorization in Azure Container Apps
- Container Apps ARM template API specification
- Tutorial: Deploy a background processing application with Azure Container Apps
- Billing in Azure Container Apps
- Comparing Container Apps with other Azure container options
- Connect applications in Azure Container Apps
- Containers in Azure Container Apps
- Dapr integration with Azure Container Apps
- Tutorial: Deploy to Azure Container Apps using Visual Studio
- Azure Container Apps environments
- Securing a custom VNET in Azure Container Apps
- Quickstart: Deploy an existing container image in the Azure portal
- Quickstart: Deploy an existing container image with the Azure CLI
- Quickstart: Deploy your first container app
- Publish revisions with GitHub Actions in Azure Container Apps
- Health probes in Azure Container Apps
- Azure Container Apps documentation
- Set up HTTPS ingress in Azure Container Apps
- Manage secrets in Azure Container Apps
- Managed identities in Azure Container Apps
- Tutorial: Deploy a Dapr application to Azure Container Apps with an Azure Resource Manager or Bicep template
- Microservices with Azure Containers Apps
- Monitor an app in Azure Container Apps
- Observability in Azure Container Apps
- Azure Container Apps overview
- Quickstart: Deploy your first container app using the Azure portal
- Quotas for Azure Container Apps
- Manage revisions Azure Container Apps
- Revisions in Azure Container Apps
- Provide a virtual network to an internal Azure Container Apps environment
- Provide a virtual network to an external Azure Container Apps environment
Application Development: Event Hubs
- Features and terminology in Azure Event Hubs
- Resource governance with application groups (preview)
- Govern resources for client applications with application groups
Application Development: Functions
- Azure SQL input binding for Azure Functions (preview)
- Azure SQL output binding for Azure Functions (preview)
- Azure SQL bindings for Azure Functions overview (preview)
Application Development: nginx
- NGINX for Azure (preview)
- QuickStart: Get started with NGINX
- Manage your NGINX for Azure (preview) integration through the portal
- What is NGINX for Azure (preview)?
- Troubleshooting NGINX integration with Azure
- Extend Azure with solutions from partners
Application Development: Service Bus: Messaging
Application Development: Service Connector
- Service Connector region support
- Service Connector internals
- Integrate Apache kafka on Confluent Cloud with Service Connector
- Integrate Azure Cosmos DB with Service Connector
- Integrate Azure Event Hubs with Service Connector
- Integrate Azure Key Vault with Service Connector
- Integrate Azure Database for MySQL with Service Connector
- Integrate Azure Database for PostgreSQL with Service Connector
- Integrate Azure Cache for Redis with Service Connector
- Integrate Service Bus with Service Connector
- Integrate Azure SignalR Service with Service Connector
- Integrate Azure Blob Storage with Service Connector
- Integrate Azure File Storage with Service Connector
- Integrate Azure Queue Storage with Service Connector
- Integrate Azure Table Storage with Service Connector
- How to troubleshoot with Service Connector
- Service Connector documentation
- What is Service Connector?
- Quickstart: Create a service connection in App Service with the Azure CLI
- Quickstart: Create a service connection in Spring Cloud with the Azure CLI
- Quickstart: Create a service connection in App Service from the Azure portal
- Quickstart: Create a service connection in Container Apps from the Azure portal
- Quickstart: Create a service connection in Spring Cloud from the Azure portal
- Tutorial: Deploy a web application connected to Azure Blob Storage with Service Connector
- Tutorial: Using Service Connector to build a Django app with Postgres on Azure App Service
- Tutorial: Deploy a Spring Boot app connected to Apache Kafka on Confluent Cloud with Service Connector in Azure Spring Cloud
- Tutorial: Deploy Spring Cloud Application Connected to Azure Database for MySQL with Service Connector
- Quickstart: Create a service connection and store secrets into Key Vault
Application Development: Spring Cloud
- Access your application in a private network
- App status in Azure Spring Apps
- Manage and monitor app with Spring Boot Actuator
- Metrics for Azure Spring Apps
- Security controls for Azure Spring Apps Service
- App and deployment in Azure Spring Apps
- Blue-green deployment strategies in Azure Spring Apps
- Use a managed identity to connect Azure SQL Database to an Azure Spring Apps app
- Analyze logs and metrics with diagnostics settings
- Azure Spring Apps disaster recovery
- Expose applications with end-to-end TLS in a virtual network
- Expose applications to the internet with TLS Termination at Application Gateway
- Azure Spring Apps FAQ
- Authenticate Azure Spring Apps with Azure Key Vault in GitHub Actions
- Access Config Server and Service Registry
- How to monitor Spring Boot apps with the AppDynamics Java Agent (Preview)
- Use Application Insights Java In-Process Agent in Azure Spring Apps
- Bind an Azure Cosmos DB database to your application in Azure Spring Apps
- Bind an Azure Database for MySQL instance to your application in Azure Spring Apps
- Bind Azure Cache for Redis to your application in Azure Spring Apps
- Use built-in persistent storage in Azure Spring Apps
- Capture heap dump and thread dump manually and use Java Flight Recorder in Azure Spring Apps
- Automate application deployments to Azure Spring Apps
- Collect Spring Cloud Resilience4J Circuit Breaker Metrics with Micrometer (Preview)
- Configure a managed Spring Cloud Config Server in Azure Spring Apps
- How to configure Palo Alto for Azure Spring Apps
- How to enable your own persistent storage in Azure Spring Apps
- Deploy Azure Spring Apps in a virtual network
- Create and deploy applications by using PowerShell
- Deploy an application with a custom container image (Preview)
- Use distributed tracing with Azure Spring Apps (deprecated)
- Use the diagnostic settings of JVM options for advanced troubleshooting in Azure Spring Apps
- How to monitor Spring Boot apps with Dynatrace Java OneAgent
- How to monitor Spring Boot apps with Elastic APM Java Agent
- Analyze logs with Elastic (ELK) using diagnostics settings
- Create Azure Spring Apps instance with availability zone enabled
- Enable ingress-to-app TLS for an application
- Enable system-assigned managed identity for an application in Azure Spring Apps
- Use Application Configuration Service for Tanzu
- Use Tanzu Build Service
- How to deploy non-Java applications in Azure Spring Apps
- View Azure Spring Apps Enterprise Tier offering in Azure Marketplace
- Use Tanzu Service Registry
- Use Azure Spring Apps CI/CD with GitHub Actions
- Integrate Azure Spring Apps with Azure Load Balance Solutions
- Deploy Spring Boot applications using IntelliJ
- How to Deploy Spring Boot applications from Azure CLI
- Stream Azure Spring Apps app logs in real-time
- Manage user-assigned managed identities for an application in Azure Spring Apps (preview)
- Deploy Spring Boot applications using Maven
- Migrate an Azure Spring Apps Basic or Standard tier instance to Enterprise tier
- Move an Azure Spring Apps service instance to another region
- How to monitor Spring Boot apps using New Relic Java agent (Preview)
- How to identify outbound public IP addresses in Azure Spring Apps
- How to use permissions in Azure Spring Apps
- Prepare an application for deployment in Azure Spring Apps
- Scale an application in Azure Spring Apps
- Self-diagnose running Azure Spring Apps in VNET
- Self-diagnose and solve problems in Azure Spring Apps
- Discover and register your Spring Boot applications
- Set up autoscale for applications
- Set up a staging environment in Azure Spring Apps
- Start, stop, and delete an application in Azure Spring Apps
- Start or stop your Azure Spring Apps service instance
- Use API portal for VMware Tanzu
- Use Spring Cloud Gateway for Tanzu
- Use managed identities for applications in Azure Spring Apps
- Use TLS/SSL certificates in your application in Azure Spring Apps
- How to use Logback to write logs to custom persistent storage
- Azure Spring Apps documentation
- Monitor app lifecycle events using Azure Activity log and Azure Service Health
- What is Azure Spring Apps?
- Azure Policy built-in definitions for Azure Spring Apps
- Java and Base OS for Azure Spring Apps apps
- Quickstart: Build and deploy apps to Azure Spring Apps using the Enterprise tier
- Quickstart: Build and deploy apps to Azure Spring Apps
- Quickstart: Provision Azure Spring Apps using Azure CLI
- Quickstart: Provision Azure Spring Apps using Bicep
- Quickstart: Provision Azure Spring Apps using Terraform
- Quickstart: Provision Azure Spring Apps using an ARM template
- Quickstart: Integrate Azure Spring Apps with Azure Database for MySQL
- Quickstart: Monitoring Azure Spring Apps apps with logs, metrics, and tracing
- Quickstart: Provision an Azure Spring Apps service instance using the Enterprise tier
- Quickstart: Provision an Azure Spring Apps service instance
- Introduction to the sample app
- Quickstart: Set up Application Configuration Service for Tanzu
- Quickstart: Set up Azure Spring Apps Config Server
- Quickstart: Set up a Log Analytics workspace
- Quickstart: Deploy your first application to Azure Spring Apps
- Quotas and service plans for Azure Spring Apps
- Azure Spring Apps reference architecture
- Azure Spring Apps developer resources
- Azure Policy Regulatory Compliance controls for Azure Spring Apps
- Structured application log for Azure Spring Apps
- Troubleshoot common Azure Spring Apps issues
- Troubleshooting Azure Spring Apps in virtual networks
- Tutorial: Monitor Spring app resources using alerts and action groups
- Tutorial: Use Circuit Breaker Dashboard with Azure Spring Apps
- Tutorial: Map an existing custom domain to Azure Spring Apps
- Tutorial: Use a managed identity to invoke Azure Functions from an Azure Spring Apps app
- Tutorial: Use a managed identity to connect Key Vault to an Azure Spring Apps app
- Tutorial: Use a managed identity to connect an Azure Database for MySQL to an app in Azure Spring Apps
- Customer responsibilities for running Azure Spring Apps in VNET
Application Development
- Azure Arc landing zone accelerator for hybrid and multicloud
- Prepare your environment for a hybrid and multicloud scenario
Data & AI: .NET: ADO.NET
- Configuring parameters
- Example demonstrating use of Azure Key Vault provider with Always Encrypted
- Tutorial: Develop a .NET application using Always Encrypted with secure enclaves
Data & AI: Azure Arc for Data
- Enable transparent data encryption on Azure Arc-enabled SQL Managed Instance
- Limitations of Azure Arc-enabled SQL Managed Instance
- Overview: Azure Arc-enabled SQL Managed Instance business continuity
- Azure Arc-enabled SQL Managed Instance - disaster recovery
- Features and Capabilities of Azure Arc-enabled SQL Managed Instance
- High Availability with Azure Arc-enabled SQL Managed Instance
- Perform a point-in-time Restore
- Release notes - Azure Arc-enabled data services
- Reserved capacity - Azure Arc-enabled SQL Managed Instance
- Azure Arc-enabled SQL Managed Instance service tiers
- Sizing Guidance
- Storage Configuration
- Upgrade an indirectly connected Azure Arc-enabled Managed Instance using the CLI
- Upgrade a directly connected Azure Arc-enabled Managed Instance using the CLI
- Upgrade an an indirectly connected Azure Arc-enabled Managed Instance using Kubernetes tools
- Version log
Data & AI: Azure Data Factory
Data & AI: Azure Data Studio
- Azure Cosmos DB API for MongoDB extension (Preview)
- Schema Compare extension
- Build a database project from command line
- SQL Database Projects extension (Preview)
- Quickstart: Use Azure Data Studio to connect and query Azure Cosmos DB API for MongoDB (Preview)
Data & AI: Azure Monitor
Data & AI: Azure SQL
- What's new in Azure SQL Database?
- Ledger overview
- Quickstart: Create a database in Azure SQL Database with ledger enabled
- What is the database ledger?
- Ledger overview
- Ledger documentation
- Ledger considerations and limitations
- Create a project for a local Azure SQL Database development environment
- What is the local development experience for Azure SQL Database?
- Publish a Database Project for Azure SQL Database to the local emulator
- Quickstart: Create a local development environment for Azure SQL Database
- Set up a local development environment for Azure SQL Database
- Introducing the Azure SQL Database emulator (preview)
- Detectable types of query performance bottlenecks in Azure SQL Database and Azure SQL Managed Instance
- Auto-failover groups overview & best practices (Azure SQL Managed Instance)
- What's new in Azure SQL Managed Instance?
- Link feature for Azure SQL Managed Instance (preview)
- Documentation changes for SQL Server on Azure Virtual Machines
Data & AI: Cognitive Services: Language Services
- Service limits for Azure Cognitive Service for Language
- Model lifecycle
- Accepted data formats
- Evaluation metrics
- Back up and recover your custom text classification models
- Terms and definitions used in custom text classification
- Query deployment to classify text
- How to create custom text classification project
- Improve custom text classification model performance
- Label text data for training your model
- How to train a custom text classification model
- View your text classification model's evaluation and details
- What is custom text classification?
- Custom text classification limits
- Accepted custom NER data formats
- Evaluation metrics for custom named entity recognition models
- Back up and recover your custom NER models
- Frequently asked questions for Custom Named Entity Recognition
- Custom named entity recognition definitions and terms
- Query deployment to extract entities
- How to create custom NER project
- Deploy a model and extract entities from text using the runtime API
- How to prepare data and define a schema for custom NER
- Improve model performance
- Label your data in Language Studio
- Train your custom named entity recognition model
- How to use auto-labeling
- View the custom NER model's evaluation and details
- Language support for custom named entity recognition
- What is custom named entity recognition?
- Quickstart: Custom named entity recognition (preview)
- Custom named entity recognition service limits
- Tutorial: Enrich a Cognitive Search index with custom entities from your data
- Accepted data formats
- Evaluation metrics
- Back up and recover your custom text classification models
- Frequently asked questions
- Terms and definitions used in custom text classification
- Query deployment to classify text
- How to create custom text classification project
- Deploy a model and classify text using the runtime API
- How to prepare data and define a text classification schema
- Improve custom text classification model performance
- Label text data for training your model
- How to train a custom text classification model
- View your text classification model's evaluation and details
- Language support for custom text classification
- What is custom text classification?
- Quickstart: Custom text classification (preview)
- Custom text classification limits
- Tutorial: Enrich Cognitive Search index with custom classes from your data
- Azure Cognitive Service for Language documentation
- What is Azure Cognitive Service for Language?
- How to use conversation summarization (preview)
- How to use document summarization (preview)
- Summarization language support
- What is document and conversation summarization (preview)?
- Quickstart: using document summarization and conversation summarization (preview)
- What is document and conversation summarization (preview)?
- What's new in Azure Cognitive Service for Language?
Data & AI: Cognitive Services: Open AI
Data & AI: Cognitive Services: Translator
- Answers to frequently asked questions
- What is Document Translation?
- Translator language support
- What's new in Azure Cognitive Services Translator?
Data & AI: Cosmos DB
- Frequently asked questions on burst capacity in Azure Cosmos DB (preview)
- Burst capacity in Azure Cosmos DB (preview)
- Frequently asked questions on hierarchical partition keys in Azure Cosmos DB (preview)
- Hierarchical partition keys in Azure Cosmos DB (preview)
- Run the emulator on Docker for Linux (Preview)
- Merge partitions in Azure Cosmos DB (preview)
- Azure Cosmos DB serverless
- Frequently asked questions on distributing throughput across partitions in Azure Cosmos DB (preview)
- Redistribute throughput across partitions (preview)
- How to choose between provisioned throughput and serverless
Data & AI: Machine Learning
- Azure Machine Learning CLI (v2) release notes
- Azure Machine Learning Python SDK release notes
- Convert to Image Directory
- Execute Python Script component
- Execute R Script component
- Import Data component
- What is automated machine learning (AutoML)?
- How Azure Machine Learning works: resources and assets (v2)
- Make data-driven policies and influence decision making (preview)
- What is an Azure Machine Learning component?
- What is an Azure Machine Learning compute instance?
- What are compute targets in Azure Machine Learning?
- Counterfactuals analysis and what-if (preview)
- Understand your datasets (preview)
- Data encryption with Azure Machine Learning
- Data in Azure Machine Learning
- What is Azure Machine Learning designer?
- What are Azure Machine Learning endpoints?
- Enterprise security and governance for Azure Machine Learning
- Assess errors in ML models (preview)
- What are Azure Machine Learning pipelines?
- MLflow and Azure Machine Learning
- MLOps: Model management, deployment, lineage, and monitoring with Azure Machine Learning
- Use open-source machine learning libraries and platforms with Azure Machine Learning
- Optimize data processing with Azure Machine Learning
- Plan to manage costs for Azure Machine Learning
- Assess AI systems and make data-driven decisions with Azure Machine Learning Responsible AI dashboard (preview)
- What is responsible AI? (preview)
- Network traffic flow when using a secured workspace
- Train models with Azure Machine Learning
- Git integration for Azure Machine Learning
- What is Azure Machine Learning CLI & Python SDK v2?
- Vulnerability management for Azure Machine Learning
- What is an Azure Machine Learning workspace?
- Track experiments and deploy models in Azure Machine Learning
- Configure inbound and outbound network traffic
- Connect to storage with Azure Machine Learning datastores
- Access Azure resources from an online endpoint with a managed identity
- Access a compute instance terminal in your workspace
- Manage access to an Azure Machine Learning workspace
- Azure Machine Learning anywhere with Kubernetes (preview)
- Azure Machine Learning anywhere with Kubernetes (preview)
- Key and token-based authentication for online endpoints
- Configure authentication for models deployed as web services
- Set up AutoML to train a time-series forecasting model with Python
- Set up AutoML to train computer vision models
- # Set up AutoML to train a natural language processing model (preview)
- Autoscale a managed online endpoint
- Regenerate storage account access keys
- Data featurization in automated machine learning
- Set up AutoML training with the Azure ML Python SDK v2 (preview)
- Install and set up the CLI (v2)
- Configure training, validation, cross-validation and test data in automated machine learning
- Set up a Python development environment for Azure Machine Learning
- Configure a private endpoint for an Azure Machine Learning workspace
- Connect to data with the Azure Machine Learning studio
- Consume an Azure Machine Learning model deployed as a web service
- Convert custom ML models to MLflow formatted models
- Create an Azure Machine Learning compute cluster
- Create compute targets for model training and deployment in Azure Machine Learning studio
- Create and attach an Azure Kubernetes Service cluster
- Create and run machine learning pipelines using components with the Azure Machine Learning SDK v2 (Preview)
- Create and run machine learning pipelines using components with the Azure Machine Learning CLI
- Create and run machine learning pipelines using components with the Azure Machine Learning studio (Preview)
- Create and run machine learning pipelines with Azure Machine Learning SDK
- Create and manage an Azure Machine Learning compute instance
- Create Azure Machine Learning data assets
- How to use your workspace with a custom DNS server
- Customize the compute instance with a script (preview)
- Data ingestion with Azure Data Factory
- Data wrangling with Apache Spark pools (preview)
- Troubleshooting the ParallelRunStep
- Troubleshooting machine learning pipelines
- Interactive debugging with Visual Studio Code
- Advanced entry script authoring
- Deploy machine learning models to Azure
- How to deploy an AutoML model to an online endpoint
- Deploy models with REST for batch scoring
- Deploy a TensorFlow model served with TF Serving using a custom container in an online endpoint
- Deploy ML models to field-programmable gate arrays (FPGAs) with Azure Machine Learning
- Deploy a deep learning model for inference with GPU
- Deploy a model locally
- Deploy models trained with Azure Machine Learning on your local machines
- Deploy and score a machine learning model by using an online endpoint
- Deploy MLflow models to online endpoints (preview)
- Deploy a model for use with Cognitive Search
- Use the studio to deploy models trained in the designer
- How to package a registered model with Docker
- Publish and track machine learning pipelines
- Update a deployed web service (v1)
- Deploy models with REST
- High-performance serving with Triton Inference Server (Preview)
- Import data into Azure Machine Learning designer
- Monitor and collect data from ML web service endpoints
- Collect data from models in production
- Use Azure Machine Learning studio in an Azure virtual network
- View automated ML model's training code (preview)
- Failover for business continuity and disaster recovery
- Connect to storage by using identity-based data access
- Make predictions with ONNX on computer vision models from AutoML
- Azure Machine Learning anywhere with Kubernetes (preview)
- Link Azure Synapse Analytics and Azure Machine Learning workspaces and attach Apache Spark pools(preview)
- Collect machine learning pipeline log files in Application Insights for alerts and debugging
- Log & view metrics and log files
- Use Azure Machine Learning with the Fairlearn open-source package to assess the fairness of ML models (preview)
- Use the Python interpretability package to explain ML models & predictions (preview)
- Interpretability: Model explainability in automated ML (preview)
- Model interpretablity (preview)
- Manage Azure Machine Learning environments with the CLI (v2)
- Work with Models in Azure Machine Learning
- Manage and optimize Azure Machine Learning costs
- Manage and increase quotas for resources with Azure Machine Learning
- Manage Azure Machine Learning resources with the VS Code Extension (preview)
- Manage Azure Machine Learning workspaces using Azure CLI
- Manage Azure Machine Learning workspaces in the portal or with the Python SDK
- Migrating from Estimators to ScriptRunConfig
- Detect data drift (preview) on datasets
- Monitor managed online endpoints
- Visualize experiment runs and metrics with TensorBoard and Azure Machine Learning
- Moving data into and between ML pipeline steps (Python)
- Secure Azure Machine Learning workspace resources using virtual networks (VNets)
- Python package extensibility for prebuilt Docker images (preview)
- Prepare data for computer vision tasks with automated machine learning (preview)
- Read and write data for ML experiments
- Generate Responsible AI dashboard with YAML and Python (preview)
- Generate Responsible AI dashboard in the studio UI (preview)
- How to use the Responsible AI dashboard in studio (preview)
- Share insights with Responsible AI scorecard (preview)
- Run batch predictions using Azure Machine Learning designer
- Safe rollout for online endpoints
- Secure an Azure Machine Learning inferencing environment with virtual networks
- Use network isolation with managed online endpoints (preview)
- Secure an Azure Machine Learning training environment with virtual networks
- Use TLS to secure a web service through Azure Machine Learning
- Secure an Azure Machine Learning workspace with virtual networks
- Configure and submit training runs
- Set up authentication for Azure Machine Learning resources and workflows
- Use customer-managed keys with Azure Machine Learning
- Set up the Visual Studio Code Azure Machine Learning extension (preview)
- Enable logging in Azure Machine Learning designer pipelines
- Start, monitor, and track run history in studio
- Train models with the CLI (v2)
- Distributed GPU training guide
- Train Keras models at scale with Azure Machine Learning
- Train ML models with MLflow Projects and Azure Machine Learning (preview)
- Train PyTorch models at scale with Azure Machine Learning
- Train scikit-learn models at scale with Azure Machine Learning
- Train models with the Azure ML Python SDK v2 (preview)
- Train TensorFlow models at scale with Azure Machine Learning
- Train a model by using a custom Docker image
- Train models with Azure Machine Learning datasets
- Train models with REST (preview)
- Create a training job with the job creation UI (preview)
- Trigger machine learning pipelines
- Troubleshoot automated ML experiments in Python
- Troubleshooting batch endpoints
- Troubleshooting with a local model deployment
- Troubleshooting remote model deployment
- Troubleshoot environment image builds
- Troubleshooting online endpoints deployment and scoring
- Hyperparameter tuning a model (v2)
- Evaluate automated machine learning experiment results
- Set up no-code AutoML training with the studio UI
- Train a small object detection model with AutoML (preview)
- Use automated ML in an Azure Machine Learning pipeline in Python
- Use Azure AD identity with your machine learning web service in Azure Kubernetes Service
- Use batch endpoints for batch scoring
- How to use batch endpoints in Azure Machine Learning studio
- Work with data using SDK v2 preview
- Create & use software environments in Azure Machine Learning
- Create and explore Azure Machine Learning dataset with labels
- Use Managed identities with Azure Machine Learning
- Create and use managed online endpoints in the studio
- Track Azure Databricks ML experiments with MLflow and Azure Machine Learning
- Track ML experiments and models with MLflow or the Azure Machine Learning CLI (v2)
- How to use studio UI to build and debug Azure Machine Learning pipelines
- Use private Python packages with Azure Machine Learning
- Reinforcement learning (preview) with Azure Machine Learning
- Use authentication credential secrets in Azure Machine Learning training runs
- How to do hyperparameter tuning in pipeline (V2) (preview)
- How to use Apache Spark (powered by Azure Synapse Analytics) in your machine learning pipeline (preview)
- Version and track Azure Machine Learning datasets
- View costs for an Azure Machine Learning managed online endpoint (preview)
- How to use workspace diagnostics
- Azure Machine Learning documentation
- Migrate to Azure Machine Learning from ML Studio (classic)
- Rebuild a Studio (classic) web service in Azure Machine Learning
- Migrate a Studio (classic) dataset to Azure Machine Learning
- What happened to Azure Machine Learning Workbench?
- What is Azure Machine Learning?
- Azure Machine Learning feature availability across clouds regions
- Managed online endpoints SKU list (preview)
- Migrate logging from SDK v1 to SDK v2 (preview)
- CLI (v2) command component YAML schema
- CLI (v2) compute cluster (AmlCompute) YAML schema
- CLI (v2) compute instance YAML schema
- CLI (v2) Attached Azure Arc-enabled Kubernetes cluster (KubernetesCompute) YAML schema
- CLI (v2) attached Virtual Machine YAML schema
- CLI (v2) core YAML syntax
- CLI (v2) data YAML schema
- CLI (v2) Azure Blob datastore YAML schema
- CLI (v2) Azure Data Lake Gen1 YAML schema
- CLI (v2) Azure Data Lake Gen2 YAML schema
- CLI (v2) Azure Files datastore YAML schema
- CLI (v2) batch deployment YAML schema
- CLI (v2) Azure Arc-enabled Kubernetes online deployment YAML schema
- CLI (v2) managed online deployment YAML schema
- CLI (v2) batch endpoint YAML schema
- CLI (v2) online endpoint YAML schema
- CLI (v2) environment YAML schema
- CLI (v2) command job YAML schema
- CLI (v2) pipeline job YAML schema
- CLI (v2) sweep job YAML schema
- CLI (v2) model YAML schema
- CLI (v2) YAML schemas
- CLI (v2) workspace YAML schema
- Tutorial: Upload data and train a model (part 3 of 3)
- Tutorial: Get started with a Python script in Azure Machine Learning (part 1 of 3)
- Tutorial: Train your first machine learning model (part 2 of 3)
- Tutorial: Train an object detection model (preview) with AutoML and Python
- Tutorial: Train a regression model with AutoML and Python
- Tutorial: Convert ML experiments to production Python code
- How to create a secure workspace
- Tutorial: Designer - deploy a machine learning model
- Tutorial: Designer - train a no-code regression model
- Tutorial: Create production ML pipelines with Python SDK v2 (preview) in a Jupyter notebook
- Tutorial: Power BI integration - Create the predictive model with a Jupyter Notebook (part 1 of 2)
- Train an image classification TensorFlow model using the Azure Machine Learning Visual Studio Code Extension (preview)
- Tutorial: Train and deploy an image classification model with an example Jupyter Notebook
- Automated machine learning (AutoML)?
- How Azure Machine Learning works: Architecture and concepts (v1)
- Secure data access in Azure Machine Learning
- MLflow and Azure Machine Learning (v1)
- MLOps: Model management, deployment, lineage, and monitoring with Azure Machine Learning v1
- Connect to storage services on Azure with datastores
- Train models with the Azure Machine Learning Python SDK (v1)
- Set up AutoML to train computer vision models with Python (v1)
- Set up AutoML to train a natural language processing model with Python (preview)
- Set up AutoML training with Python
- Create an Azure Machine Learning compute cluster with CLI v1
- Create and manage an Azure Machine Learning compute instance with CLI v1
- Create Azure Machine Learning datasets
- Deploy a model to Azure Container Instances with CLI (v1)
- Deploy a model to an Azure Kubernetes Service cluster with v1
- Deploy MLflow models as Azure web services
- Profile your model to determine resource utilization
- Log & view metrics and log files v1
- Prepare data for computer vision tasks with automated machine learning v1
- Start, monitor, and track run history
- Hyperparameter tuning a model with Azure Machine Learning (v1)
- Create & use software environments in Azure Machine Learning with CLI v1
- Use Managed identities with Azure Machine Learning CLI v1
- Track ML models with MLflow and Azure Machine Learning
- Azure Machine Learning SDK & CLI v1
- Install & use the CLI (v1)
- CLI (v1) pipeline job YAML schema
- Tutorial: Train an object detection model (preview) with AutoML and Python (v1)
- Tutorial: Build an Azure Machine Learning pipeline for image classification
Data & AI: MySQL
- Server concepts in Azure Database for MySQL Flexible Server
- Backup and restore in Azure Database for MySQL Flexible Server
- Overview of business continuity with Azure Database for MySQL - Flexible Server
- Compute and storage options in Azure Database for MySQL - Flexible Server
- Scheduled maintenance in Azure Database for MySQL ??? Flexible server
- Read replicas in Azure Database for MySQL - Flexible Server
- Server parameters in Azure Database for MySQL - Flexible Server
- Supported versions for Azure Database for MySQL - Flexible Server
- Manage zone redundant high availability in Azure Database for MySQL Flexible Server with Azure CLI
- Manage zone redundant high availability in Azure Database for MySQL Flexible Server
- Configure server parameters in Azure Database for MySQL Flexible Server using the Azure CLI
- Connect to Azure Database for MySQL - Flexible Server with encrypted connections
- Azure Database for MySQL - Flexible Server
- Azure CLI samples for Azure Database for MySQL - Flexible Server
- Configure same-zone high availability in an Azure Database for MySQL - Flexible Server using Azure CLI
- Configure zone-redundant high availability in an Azure Database for MySQL - Flexible Server using Azure CLI
- What's new in Azure Database for MySQL - Flexible Server?
Data & AI: Open Datasets
- The MNIST database of handwritten digits
- Create Azure Machine Learning datasets from Azure Open Datasets
Data & AI: Purview
- Asset insights on your data in Microsoft Purview
- Access control in the Microsoft Purview Data Map
- Classification insights about your data in Microsoft Purview
- Understand the Microsoft Purview Data Estate Insights application
- Get insights into data stewardship from Microsoft Purview
- Insights for your business glossary in Microsoft Purview
- Provision access by data owner for SQL Server on Azure Arc-enabled servers (preview)
- Provision access by data owner for Azure SQL DB (preview)
- Resource group and subscription access provisioning by data owner (Preview)
- Access provisioning by data owner to Azure Storage datasets (Preview)
- Authoring and publishing data owner access policies (Preview)
- Access control in Data Estate Insights within Microsoft Purview
- What is Microsoft Purview?
- Microsoft Purview product glossary
- Sensitivity label insights about your data in Microsoft Purview
Data & AI: Search: Machine Learning
Data & AI: SQL Server
- Big data options on the Microsoft SQL Server platform
- What is a contained availability group?
- Configure the max degree of parallelism Server Configuration Option
- Deprecated database engine features in SQL Server 2022 (16.x) Preview
- Discontinued database engine functionality in SQL Server
- Install SQL Server from the Command Prompt
- Extensibility architecture in SQL Server Language Extensions
- Install SQL Server Java Language Extension on Windows
- Install SQL Server Java Language Extension on Linux
- Install SQL Server 2022 Machine Learning Services (Python and R) on Linux
- Install SQL Server 2019 Machine Learning Services (Python and R) on Linux
- Extensibility architecture in SQL Server Machine Learning Services
- R language extension in SQL Server Machine Learning Services
- Modify R/Python code to run in SQL Server (In-Database) instances
- SQL machine learning documentation
- Install a Python custom runtime for SQL Server
- Install an R custom runtime for SQL Server
- Install SQL Server 2022 Machine Learning Services (Python and R) on Windows
- Install SQL Server Machine Learning Services (Python and R) on Windows
- Install Machine Learning Server (Standalone) or R Server (Standalone) using SQL Server Setup
- CAB downloads for offline installation of cumulative updates for SQL Server Machine Learning Services
- Install SQL Server Machine Learning Services with R and Python from the command line
- Offline install SQL Server Machine Learning Services on Windows computers with no internet access
- Install pre-trained machine learning models on SQL Server
- SQL Server on Windows: Isolation changes for Machine Learning Services
- Get R package information
- Tips for using R packages
- Set up a data science client for Python development on SQL Server Machine Learning Services
- Set up a data science client for R development on SQL Server
- What is SQL Server Machine Learning Services with Python and R?
- Quickstart: Run simple Python scripts with SQL machine learning
- What's new in SQL Server Machine Learning Services?
- Accelerated database recovery
- Automatic tuning
- Create a Transact-SQL snapshot backup
- Restore and Recovery Overview (SQL Server)
- SQL Server backup and restore with Azure Blob Storage
- SQL Server backup and restore with S3-compatible object storage preview
- SQL Server back up to URL for Microsoft Azure Blob Storage best practices and troubleshooting
- SQL Server back up to URL for S3-compatible object storage best practices and troubleshooting
- SQL Server backup to URL for S3-compatible object storage
- SQL Server backup to URL for Microsoft Azure Blob Storage
- Shrink a database
- Shrink a file
- Best practices with Query Store
- Cardinality Estimation (SQL Server)
- Intelligent query processing in SQL databases
- Monitor performance by using the Query Store
- Optimized plan forcing with Query Store
- Parameter Sensitivity Plan optimization
- Plan Guides
- Query Store hints (preview) best practices
- Query Store hints (preview)
- Query Store Usage Scenarios
- Specify Query Parameterization Behavior by Using Plan Guides
- Use the External Table Wizard with ODBC data sources
- Configure PolyBase to access external data in MongoDB
- Configure PolyBase to access external data in S3-compatible object storage
- Introducing data virtualization with PolyBase
- Virtualize parquet file in a S3-compatible object storage with PolyBase
- Post-migration Validation and Optimization Guide
- Query Processing Architecture Guide
- Dynamic Data Masking
- Develop applications using Always Encrypted with secure enclaves
- Configure the secure enclave in SQL Server
- Configure column encryption in-place with Transact-SQL
- Configure column encryption in-place using Always Encrypted with secure enclaves
- Create and use indexes on columns using Always Encrypted with secure enclaves
- Enable Always Encrypted with secure enclaves for existing encrypted columns
- Deploy the Host Guardian Service for SQL Server
- Plan for Host Guardian Service attestation
- Register computer with Host Guardian Service
- Manage keys for Always Encrypted with secure enclaves
- Provision enclave-enabled keys
- Run Transact-SQL statements using secure enclaves
- Rotate enclave-enabled keys
- Always Encrypted with secure enclaves
- Configure and use Always Encrypted with secure enclaves
- Append-only ledger tables
- What is the database ledger?
- Database verification
- Digest management
- Create and use append-only ledger tables
- Configure a ledger database
- Enable automatic digest storage
- Migrate data from regular tables to ledger tables
- Recover ledger database after tampering
- Create and use updatable ledger tables
- Ledger documentation
- Ledger considerations and limitations
- Ledger overview
- Updatable ledger tables
- Verify a ledger table to detect tampering
- Tutorial: Develop a .NET Framework application using Always Encrypted with secure enclaves
- Tutorial: Create and use indexes on enclave-enabled columns using randomized encryption
- Tutorial: Getting started with Always Encrypted with secure enclaves in SQL Server
- Create Statistics
- Statistics
- Update Statistics
- Query Store catalog views (Transact-SQL)
- Security Catalog Views (Transact-SQL)
- sys.all_columns (Transact-SQL)
- sys.columns (Transact-SQL)
- sys.database_ledger_blocks (Transact-SQL)
- sys.database_ledger_digest_locations (Transact-SQL)
- sys.database_ledger_transactions (Transact-SQL)
- sys.database_query_store_internal_state (Transact-SQL)
- sys.databases (Transact-SQL)
- sys.ledger_column_history (Transact-SQL)
- sys.ledger_table_history (Transact-SQL)
- sys.query_store_plan (Transact-SQL)
- sys.query_store_query_hints (Transact-SQL)
- sys.query_store_runtime_stats (Transact-SQL)
- sys.query_store_wait_stats (Transact-SQL)
- sys.system_columns (Transact-SQL)
- sys.tables (Transact-SQL)
- sys.views (Transact-SQL)
- Change Data Capture - sys.dm_cdc_errors
- Change Data Capture - sys.dm_cdc_log_scan_sessions
- sys.dm_change_feed_errors (Transact-SQL)
- sys.dm_change_feed_log_scan_sessions (Transact-SQL)
- sys.dm_exec_requests (Transact-SQL)
- sys.dm_exec_text_query_plan (Transact-SQL)
- sys.dm_os_workers (Transact-SQL)
- sys.dm_tran_persistent_version_store_stats (Transact-SQL)
- sys.dm_xtp_system_memory_consumers (Transact-SQL)
- Query Store stored procedures (Transact-SQL)
- Security Stored Procedures (Transact-SQL)
- sp_change_feed_disable_db (Transact-SQL)
- sp_change_feed_disable_table (Transact-SQL)
- sp_change_feed_drop_table_group (Transact-SQL)
- sp_help_change_feed (Transact-SQL)
- sp_query_store_clear_message_queues (Transact-SQL)
- sp_query_store_flush_db (Transact-SQL)
- sp_query_store_force_plan (Transact-SQL)
- sp_query_store_reset_exec_stats (Transact-SQL)
- sys.sp_copy_data_in_batches (Transact-SQL)
- sys.sp_generate_database_ledger_digest (Transact-SQL)
- sp_query_store_clear_hints (Transact-SQL)
- sp_query_store_set_hints (Transact-SQL)
- sys.sp_verify_database_ledger_from_digest_storage (Transact-SQL)
- sys.sp_verify_database_ledger (Transact-SQL)
- backupset (Transact-SQL)
- Thread and Task Architecture Guide
- XML data (SQL Server)
- XML indexes (SQL Server)
- Connect your SQL Server to Azure Arc
- SQL Server technical documentation
- SQL Server 2022 (16.x) Preview release notes
- Manage Azure Synapse Link for SQL Server and Azure SQL Database
- Azure Synapse Link for SQL change feed
- What's new in SQL Server 2022 (16.x) Preview
- DBCC SHRINKDATABASE (Transact-SQL)
- DBCC SHRINKFILE (Transact-SQL)
- Analytic functions (Transact-SQL)
- Date and time data types and functions (Transact-SQL)
- DATE_BUCKET (Transact-SQL)
- FIRST_VALUE (Transact-SQL)
- GENERATE_SERIES (Transact-SQL)
- ISJSON (Transact-SQL)
- JSON_ARRAY (Transact-SQL)
- JSON Functions (Transact-SQL)
- JSON_OBJECT (Transact-SQL)
- JSON_PATH_EXISTS (Transact-SQL)
- LAST_VALUE (Transact-SQL)
- Logical Functions - GREATEST (Transact-SQL)
- Logical Functions - LEAST (Transact-SQL)
- PERCENTILE_DISC (Transact-SQL)
- STRING_SPLIT (Transact-SQL)
- Relational operators (Transact-SQL)
- Hints (Transact-SQL) - Query
- ALTER DATABASE SCOPED CONFIGURATION (Transact-SQL)
- ALTER DATABASE SET options (Transact-SQL)
- ALTER INDEX (Transact-SQL)
- ALTER TABLE index_option (Transact-SQL)
- ALTER TABLE (Transact-SQL)
- BACKUP CERTIFICATE (Transact-SQL)
- BACKUP MASTER KEY (Transact-SQL)
- BACKUP SYMMETRIC KEY (Transact-SQL)
- BACKUP (Transact-SQL)
- CREATE AVAILABILITY GROUP (Transact-SQL)
- CREATE CERTIFICATE (Transact-SQL)
- CREATE DATABASE
- CREATE EXTERNAL DATA SOURCE (Transact-SQL)
- CREATE EXTERNAL TABLE (Transact-SQL)
- CREATE INDEX (Transact-SQL)
- CREATE MASTER KEY (Transact-SQL)
- CREATE STATISTICS (Transact-SQL)
- CREATE TABLE (Transact-SQL)
- CREATE XML INDEX (Transact-SQL)
- DROP STATISTICS (Transact-SQL)
- DROP TABLE (Transact-SQL)
- MERGE (Transact-SQL)
- RESTORE MASTER KEY (Transact-SQL)
- RESTORE Statements - Arguments (Transact-SQL)
- RESTORE Statements (Transact-SQL)
- RESTORE SYMMETRIC KEY (Transact-SQL)
- UPDATE STATISTICS (Transact-SQL)
Data & AI: Stream Analytics
- Capture data from Event Hubs in Parquet format
- Overview of Azure Stream Analytics Cluster
- Quickstart: Create a dedicated Azure Stream Analytics cluster using Azure portal
- Filter and ingest to Azure Data Lake Storage Gen2 using the Stream Analytics no code editor
- Filter and ingest to Azure Synapse SQL using the Stream Analytics no code editor
- Integrate Azure Stream Analytics with Azure Machine Learning
- Materialize data in Azure Cosmos DB using the Stream Analytics no code editor
- No code stream processing using Azure Stream Analytics (Preview)
- Autoscale streaming units (Preview)
- Checkpoint and replay concepts in Azure Stream Analytics jobs
- Leverage query parallelization in Azure Stream Analytics
- Choose a real-time analytics and streaming processing technology on Azure
Data & AI: Synapse Analytics
- Azure Synapse Analytics frequently asked questions
- Create and use views using serverless SQL pool in Azure Synapse Analytics
- Transact-SQL features supported in Azure Synapse SQL
- Query Azure Cosmos DB data with a serverless SQL pool in Azure Synapse Link
- Self-help for serverless SQL pool
- How to set up access control on synchronized objects in serverless SQL pool
- Get started with Azure Synapse Link for Azure SQL Database (Preview)
- Get started with Azure Synapse Link for SQL Server 2022 (Preview)
- Azure Synapse Link for SQL FAQ
- Copy data from Azure Cosmos DB into a dedicated SQL pool using Apache Spark
- Azure Synapse Link for Azure SQL Database (Preview)
- Azure Synapse Link for SQL Server 2022 (Preview)
- What is Azure Synapse Link for SQL? (Preview)
- Known limitations and issues with Azure Synapse Link for SQL
Data & AI: Visual Studio Code: SQL Server Tooling
Identity: Active Directory
Identity: Azure Active Directory: Permissions Consent
Security: Sentinel
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