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AI and Machine Learning premium Foundry Models Foundry Models is the Microsoft Foundry model catalog and deployment experience for discovering, evaluating, and using cloud AI models through managed endpoints. Microsoft Foundry intermediate 5 commands Aliases: Microsoft Foundry Models, Foundry model catalog, AI Foundry models, model catalog Quick peek Open full term page

AI and Machine Learning premium Azure OpenAI Service Azure OpenAI Service provides managed access to OpenAI model capabilities through Azure endpoints and enterprise controls. Generative AI fundamentals 11 commands Aliases: Azure OpenAI Quick peek Open full term page

AI and Machine Learning premium Deployment type Deployment type is the Azure AI or Microsoft Foundry model hosting option, such as standard, global, data-zone, regional, batch, serverless, or provisioned deployment, that determines availability, data processing location, capacity model, cost, and operational behavior. Microsoft Foundry intermediate 4 commands Aliases: Microsoft Foundry deployment type, Azure AI deployment type, model deployment type, Foundry Models deployment type Quick peek Open full term page

AI and Machine Learning field-manual-ready Model router A model router sends each prompt to an appropriate underlying model so teams can balance quality, latency, and cost. Microsoft Foundry Models intermediate 4 commands Aliases: Foundry model router, automatic model routing, model router, prompt routing Quick peek Open full term page

AI and Machine Learning premium Microsoft Foundry Microsoft Foundry is the Microsoft AI platform experience used to build, evaluate, deploy, and manage AI applications, models, agents, and related project assets. Teams should manage it with clear ownership, monitoring, rollback evidence, and production change discipline. AI platform intermediate 4 commands Aliases: Azure AI Foundry, Foundry, AI Foundry Quick peek Open full term page

AI and Machine Learning premium Azure AI Foundry Create a governed project boundary where AI teams can build agents, evaluations, files, and model deployments without unmanaged sprawl.; Compare, evaluate, and approve model deployments before a generative AI feature is AI platform fundamentals 5 commands Aliases: AI Foundry, Microsoft Foundry, Foundry resource, Foundry project, Azure AI Foundry, azure ai foundry Quick peek Open full term page

AI and Machine Learning premium Foundry Local Foundry Local is an on-device AI runtime and SDK for shipping applications that run curated generative AI models locally on user hardware. Microsoft Foundry intermediate 5 commands Aliases: Microsoft Foundry Local, Foundry Local CLI, on-device AI inference, local AI runtime Quick peek Open full term page

AI and Machine Learning premium Foundry project A Foundry project organizes agents, model deployments, evaluations, files, and team access inside a Microsoft Foundry resource for building AI applications. Microsoft Foundry intermediate 5 commands Aliases: Microsoft Foundry project, AI Foundry project, Foundry workspace project Quick peek Open full term page

AI and Machine Learning premium Foundry resource A Foundry resource is the primary Azure resource for building, deploying, and managing generative AI models, agents, evaluations, and applications. Microsoft Foundry intermediate 5 commands Aliases: Microsoft Foundry resource, Foundry AIServices resource, AI Services Foundry resource Quick peek Open full term page

AI and Machine Learning premium Foundry Agent A Foundry Agent is an AI agent built or hosted in Microsoft Foundry Agent Service with instructions, model selection, tools, knowledge, and runtime execution evidence. Teams use it to automate business tasks that require model reasoning, tool calls, enterprise knowledge, workflow steps, retrieval, approvals, and observable runs inside a governed Azure AI platform. It is not a magic autonomous worker, a security principal by itself, a replacement for process controls, or a safe production feature without tool permissions, evaluation, monitoring, and human escalation. Microsoft Foundry intermediate 6 commands Aliases: Microsoft Foundry agent, Foundry Agent Service agent, AI agent in Foundry, agent service agent Quick peek Open full term page

AI and Machine Learning premium Foundry hub A Foundry hub is a hub-style Microsoft Foundry resource used in selected scenarios to group AI projects with shared security, connections, data access, and governance settings. Teams use it to organize related AI projects that need common connections, managed identities, network controls, storage, security review, and platform governance across teams or application portfolios. It is not a whole Azure tenant, a model deployment by itself, a replacement for project-level permissions, or the required resource shape for every modern Foundry scenario. Microsoft Foundry intermediate 6 commands Aliases: Azure AI Foundry hub, Foundry hub resource, hub-based project, AI hub Quick peek Open full term page

AI and Machine Learning premium Foundry IQ Foundry IQ is a managed knowledge layer for Microsoft Foundry that connects enterprise data into reusable, permission-aware knowledge bases for AI agents. Teams use it to ground agents in approved enterprise knowledge from Azure, SharePoint, OneLake, the web, and Azure AI Search-backed knowledge bases while preserving permissions and reusable retrieval configuration. It is not a general data lake, a replacement for source-system permissions, a guarantee that retrieved content is correct, or a reason to skip citation, freshness, and access reviews. Microsoft Foundry intermediate 6 commands Aliases: Microsoft Foundry IQ, Foundry IQ knowledge base, managed knowledge layer, permission-aware knowledge base Quick peek Open full term page

AI and Machine Learning premium Azure AI Foundry hub Azure AI Foundry hub is the classic Foundry hub resource used to group AI projects that share common security, data access, connections, and platform settings. In Azure, teams encounter it when teams need hub-based projects for selected Foundry and Azure Machine Learning scenarios such as fine-tuning, shared connections, and custom ML work. The useful question AI platform advanced 4 commands Aliases: AI Hub, Foundry AI Hub, hub-based project, Azure AI hub Quick peek Open full term page

AI and Machine Learning premium Azure AI Foundry project An Azure AI Foundry project is the working area where a team builds and organizes an AI application inside Microsoft Foundry. It keeps related agents, evaluations, files, indexes, tools, connections, and model usage together instead of scattering them across a shared portal. Think of it as the project boundary for one AI product, prototype, or team. It is useful because AI work quickly becomes messy: prompts, test data, model deployments, safety checks, and access decisions all need a home with ownership and repeatable operations. AI platform advanced 4 commands Aliases: AI Foundry project, AI project, Foundry project, Microsoft Foundry project Quick peek Open full term page

Analytics premium Microsoft Fabric lakehouse Microsoft Fabric lakehouse is a Microsoft Fabric data item that stores files and tables in OneLake while exposing lakehouse-style analytics and engineering experiences. Teams should manage it with clear ownership, monitoring, rollback evidence, and production change discipline. Microsoft Fabric intermediate 4 commands Aliases: Fabric lakehouse, lakehouse item, OneLake lakehouse Quick peek Open full term page

Databases premium Azure SQL Microsoft Entra authentication A database capability or setting in Azure SQL Database that helps teams store, query, scale, secure, and recover application data with clearer ownership, safety, and operational context. Azure SQL Database fundamentals 5 commands Aliases: No aliases yet Quick peek Open full term page

Storage premium Trusted Microsoft services access Trusted Microsoft services access is an Azure Storage firewall exception that allows selected Azure services to reach a restricted storage account when their service traffic cannot be represented by virtual network or IP rules. The services still authenticate and must be allowed for supported operations. Azure Storage intermediate 5 commands Aliases: trusted Azure services access, AzureServices bypass, allow trusted Microsoft services, storage trusted services access Quick peek Open full term page

Storage premium Trusted Microsoft services for storage Trusted Microsoft services for Azure Storage are specific Azure services that Microsoft documents as eligible for storage firewall exceptions. Depending on the service, access may be based on tenant registration, supported operations, or managed identity authorization combined with Azure RBAC or Data Lake ACLs. Storage platform intermediate 5 commands Aliases: trusted Azure services for Storage, storage trusted services list, Azure Storage trusted services, trusted services storage firewall Quick peek Open full term page

Identity premium Microsoft 365 group Microsoft 365 group is a collaboration-backed group object in Microsoft Entra ID used for shared membership across Microsoft 365 resources and some Azure access patterns. Teams should manage it with clear ownership, monitoring, rollback evidence, and production change discipline. Microsoft Entra ID fundamentals 4 commands Aliases: M365 group, Office 365 group, Microsoft 365 collaboration group Quick peek Open full term page

Databases premium Microsoft Entra admin for SQL Microsoft Entra admin for SQL is the Microsoft Entra identity designated to administer an Azure SQL logical server or SQL Managed Instance through Entra authentication. Teams should manage it with clear ownership, monitoring, rollback evidence, and production change discipline. Azure SQL identity intermediate 4 commands Aliases: Azure SQL Entra admin, Azure AD admin for SQL, SQL Entra administrator Quick peek Open full term page

Databases premium Microsoft Entra authentication for SQL Microsoft Entra authentication for SQL is the use of Microsoft Entra identities to authenticate to Azure SQL Database, SQL Managed Instance, or related SQL resources. Teams should manage it with clear ownership, monitoring, rollback evidence, and production change discipline. Azure SQL identity intermediate 4 commands Aliases: Azure SQL Entra authentication, Azure AD authentication for SQL, SQL Entra auth Quick peek Open full term page

Identity premium Microsoft Entra group Entra group means a Microsoft Entra ID group object used to manage membership, access assignments, application permissions, and governance workflows as a unit. Teams should manage it with clear ownership, monitoring, rollback evidence, and production change discipline. Directory groups intermediate 4 commands Aliases: Entra group, Azure AD group, directory group Quick peek Open full term page

Identity premium Microsoft Entra ID Microsoft Entra ID is the cloud identity platform that stores tenant identities and provides authentication, authorization, application registration, and access governance for Azure. Teams should manage it with clear ownership, monitoring, rollback evidence, and production change discipline. Identity platform fundamentals 4 commands Aliases: Entra ID, Azure Active Directory, Azure AD, AAD Quick peek Open full term page

Management and Governance premium Microsoft Purview account Microsoft Purview account is the Azure resource boundary for Microsoft Purview data governance, catalog, scanning, classification, lineage, and policy workflows. Teams should manage it with clear ownership, monitoring, rollback evidence, and production change discipline. Data governance intermediate 4 commands Aliases: Purview account, Microsoft Purview governance account, Azure Purview account Quick peek Open full term page

Storage premium Microsoft-managed key for storage Microsoft-managed key for Storage means the default Azure Storage encryption approach where Microsoft manages the keys that protect stored data at rest. Teams should manage it with clear ownership, monitoring, rollback evidence, and production change discipline. Storage encryption advanced 4 commands Aliases: platform-managed key for storage, PMK for storage, Microsoft managed storage encryption key Quick peek Open full term page

Databases complete SQL Microsoft Entra authentication Microsoft Learn describes Microsoft Entra authentication for Azure SQL as using identities from Microsoft Entra ID to authenticate to Azure SQL Database, Azure SQL Managed Instance, Synapse SQL, and related SQL platforms. It supports users, groups, applications, and managed identities while database permissions still control authorization. Azure SQL security and identity intermediate 5 commands Aliases: Azure SQL Entra authentication, Microsoft Entra authentication for Azure SQL, Azure AD authentication for SQL, Entra ID SQL authentication Quick peek Open full term page

Security top-250-pre130-priority-upgraded Microsoft Sentinel Microsoft Sentinel means Microsoft cloud SIEM and SOAR service for collecting security signals, detecting threats, investigating incidents, and automating response. Teams should manage it with clear ownership, monitoring, rollback evidence, and production change discipline. SIEM and SOAR fundamentals 4 commands Aliases: Sentinel, Azure Sentinel, Microsoft Sentinel SIEM Quick peek Open full term page

AI and Machine Learning premium Azure OpenAI Azure OpenAI provides OpenAI model capabilities through Azure resources, deployments, identity, networking, quota, and monitoring controls. Azure OpenAI intermediate 8 commands Aliases: Azure OpenAI Service Quick peek Open full term page

AI and Machine Learning premium Azure Machine Learning Azure Machine Learning is a cloud service for managing the machine learning lifecycle, including workspaces, data, training jobs, model deployment, monitoring, and MLOps. Machine learning operations advanced 5 commands Aliases: Azure ML, AML, Machine Learning workspace Quick peek Open full term page

AI and Machine Learning premium Chat completion A AI platform capability in Azure OpenAI that helps teams build, secure, observe, and govern intelligent applications with clearer ownership, safety, and operational context. Azure OpenAI fundamentals 5 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning premium Agent service Agent service is Microsoft Foundry Agent Service, a managed platform for building, deploying, and scaling AI agents. In everyday Azure work, teams use it to create prompt agents, workflow agents, or hosted code-based agents that use models and tools to perform tasks. The useful evidence is project, agent ID, instructions, model, tool configuration, deployment type, Microsoft Foundry intermediate 4 commands Aliases: Microsoft Foundry Agent Service, Foundry Agent Service, Azure AI agent service Quick peek Open full term page

AI and Machine Learning premium AI connection AI connection is a Microsoft Foundry project connection that links the project to an external or Azure resource such as models, storage, search, or services. In everyday Azure work, teams use it to let AI applications and agents use approved resources without every prototype hardcoding endpoints and credentials. The useful evidence is connection name, target AI platform intermediate 4 commands Aliases: Foundry connection, AI project connection, connected resource, AI service connection Quick peek Open full term page

AI and Machine Learning premium Custom document model an Azure AI Document Intelligence model trained or built for a team’s specific document layout, fields, and extraction needs. Document Intelligence fundamentals 4 commands Aliases: Document Intelligence custom model, custom extraction model, custom neural document model Quick peek Open full term page

AI and Machine Learning premium Custom Vision an Azure AI service for building, training, publishing, and improving custom image classification models from labeled images. Azure AI Vision fundamentals 4 commands Aliases: Azure AI Custom Vision, Custom Vision Service, custom image classifier Quick peek Open full term page

AI and Machine Learning premium Deployment capacity Deployment capacity is the throughput allocation configured for an Azure OpenAI or Foundry model deployment, affecting available request volume, quota use, latency, and cost. Azure OpenAI intermediate 4 commands Aliases: Azure OpenAI deployment capacity, model deployment capacity, deployment throughput capacity, PTU deployment capacity Quick peek Open full term page

AI and Machine Learning premium Fine-tuned model Fine-tuned model is a customized model produced from a supported base model by a completed fine-tuning job and then deployed for inference in Azure. Azure AI Foundry and Azure OpenAI intermediate 4 commands Aliases: Fine-tuned model, fine tuned model Quick peek Open full term page

AI and Machine Learning premium Fine-tuning Fine-tuning is the process of customizing a supported model with curated training examples so it performs better for a specific task in Azure. Azure AI Foundry and Azure OpenAI intermediate 4 commands Aliases: Fine-tuning, fine tuning Quick peek Open full term page

AI and Machine Learning premium Grounded generation Grounded generation is a generative AI pattern where model responses are based on supplied source material, retrieved enterprise content, tool results, or other approved grounding data. Generative AI intermediate 4 commands Aliases: grounded AI generation, grounded response generation, RAG answer generation Quick peek Open full term page

AI and Machine Learning premium Image Analysis Image Analysis is an Azure AI Vision capability that uses pretrained models to extract visual features, text, people, objects, tags, and captions from images. Azure AI Vision intermediate 4 commands Aliases: Analyze Image, Azure AI Vision Image Analysis, Computer Vision Image Analysis, image analysis, Image Analysis Quick peek Open full term page

AI and Machine Learning premium Image generation model Image generation model is an Azure OpenAI or Foundry model deployment that creates images from prompts, commonly using the current gpt-image model family. Azure OpenAI intermediate 4 commands Aliases: Azure OpenAI image model, gpt-image model, image generation model, Image generation model, text-to-image model Quick peek Open full term page

AI and Machine Learning premium Model deployment Model deployment is the step where a trained or selected model becomes something an application can actually call. The model may have performed well in experiments, but deployment decides how it is hosted, secured, scaled, monitored, and routed. Generative AI fundamentals 4 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning premium AI token An AI token is a unit of text processed by a language model. Azure AI and Foundry model quotas, cost, and rate limits commonly use tokens to measure prompt input, generated output, and throughput such as tokens per minute. Azure OpenAI and Foundry Models fundamentals 3 commands Aliases: model token, LLM token, input token, output token, TPM Quick peek Open full term page

AI and Machine Learning premium Chat completions Chat completions are API calls to chat-capable models where the client sends role-based messages and receives the next model response, commonly through Azure OpenAI or Microsoft Foundry endpoints. Azure OpenAI intermediate 3 commands Aliases: No aliases yet Quick peek Open full term page

Analytics learning-path-anchor Databricks metastore The top-level Unity Catalog container for catalogs, schemas, tables, volumes, models, functions, and governance permissions. Databricks intermediate 4 commands Aliases: Unity Catalog metastore, Databricks Unity Catalog metastore, metastore Quick peek Open full term page

Analytics learning-path-anchor Databricks MLflow The managed MLflow experience in Azure Databricks for experiments, runs, metrics, artifacts, model lineage, and MLOps evidence. Databricks fundamentals 4 commands Aliases: MLflow on Databricks, Databricks experiment tracking, MLflow tracking Quick peek Open full term page

Analytics learning-path-anchor Databricks model serving A managed serving endpoint pattern for exposing Databricks models or AI workloads for online inference with operational controls. Databricks intermediate 4 commands Aliases: Databricks Model Serving, serving endpoint, model serving endpoint Quick peek Open full term page

Analytics learning-path-anchor Databricks notebook A collaborative Azure Databricks document for code, SQL, visualizations, exploration, jobs, and ML workflows attached to compute. Databricks fundamentals 4 commands Aliases: Azure Databricks notebook, Databricks workspace notebook, interactive notebook Quick peek Open full term page

Analytics learning-path-anchor Databricks schema A Unity Catalog namespace under a catalog that groups tables, views, volumes, models, functions, and permissions. Databricks fundamentals 4 commands Aliases: Unity Catalog schema, Databricks database schema, schema in Unity Catalog Quick peek Open full term page

Storage learning-path-anchor Data Lake storage account A storage feature or access model in Data Lake Storage Gen2 that helps teams store, protect, move, and govern application or analytics data with clearer ownership, safety, and operational context. Data Lake Storage Gen2 advanced 19 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning verified Prompt evaluation Prompt evaluation is how teams test whether a prompt actually works instead of relying on a good demo. You run the AI behavior against a dataset of representative inputs, expected answers, safety cases, or business rules. Evaluators score quality, grounding, safety, formatting, and task success. In Azure and Microsoft Foundry, prompt evaluation helps decide whether a prompt, model, agent, or retrieval change is ready for production. It turns subjective “looks good” reviews into measurable evidence. Azure Machine Learning intermediate 6 commands Aliases: No aliases yet Quick peek Open full term page