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AI and Machine Learning template-specs-upgraded Retrieval tool Microsoft Learn describes the file search tool for Microsoft Foundry agents as a retrieval tool that lets an agent search uploaded or connected documents, create vector stores, and ground responses in external knowledge. Standard setup uses connected Azure AI Search and Blob Storage resources. Agents and grounding intermediate 5 commands Aliases: file search tool, agent retrieval tool, Foundry retrieval tool, vector store tool, knowledge retrieval tool Quick peek Open full term page

AI and Machine Learning premium Grounding Grounding is the practice of supplying relevant external information, retrieved content, or tool results so a generative AI model can base its answer on known context. AI platform and search intermediate 4 commands Aliases: AI grounding, model grounding, grounding a prompt Quick peek Open full term page

AI and Machine Learning premium Grounding data Grounding data is the source content, retrieved documents, indexed chunks, tool results, or external information supplied to a model so generated output can be based on approved facts. Azure OpenAI intermediate 4 commands Aliases: RAG grounding data, source grounding data, AI source material Quick peek Open full term page

Integration verified Receive and delete Receive and delete is an Azure Service Bus receive mode where the broker considers a message settled as soon as it sends the message to the receiver. If transfer or processing fails afterward, the message is lost instead of being redelivered. Azure Service Bus intermediate 5 commands Aliases: ReceiveAndDelete, receive-and-delete mode, destructive read, at-most-once receive Quick peek Open full term page

Integration verified Receive-and-delete mode A integration pattern or service capability in Messaging that helps teams connect services reliably without tightly coupling every component with clearer ownership, safety, and operational context. Messaging fundamentals 5 commands Aliases: No aliases yet 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 Agentic retrieval Agentic retrieval is an Azure AI Search retrieval pipeline that uses an LLM to plan focused subqueries for complex RAG questions. In everyday Azure work, teams use it to answer multi-part questions by decomposing the user request and chat history into targeted searches over indexed content. The useful evidence is knowledge base, knowledge source, search Azure AI Search intermediate 4 commands Aliases: Azure AI Search agentic retrieval, multi-query retrieval, agentic RAG retrieval Quick peek Open full term page

AI and Machine Learning premium Azure AI metrics Azure AI metrics is the measurable signals used to observe Azure AI applications, model endpoints, agents, evaluations, safety checks, and business outcomes. Azure AI services intermediate 4 commands Aliases: AI metrics, AI service metrics, Azure AI Metrics Advisor, Azure Monitor metrics for AI, Metrics Advisor, time series anomaly detection Quick peek Open full term page

AI and Machine Learning premium Azure AI Search Azure AI Search is a managed retrieval service for full-text, vector, hybrid, and semantic search across application and enterprise content. It provides search services, indexes, indexers, skillsets, ranking features, security controls, and APIs used by apps, copilots, and knowledge portals. Search fundamentals 4 commands Aliases: Azure AI Search, AI Search, Azure Cognitive Search, enterprise search, vector search, hybrid search, semantic search, Search service 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

Containers learning-path-anchor System node pool A system node pool is the AKS worker pool that keeps the cluster itself functioning. It hosts core Kubernetes and AKS add-on pods such as DNS, networking agents, metrics, and connectivity components. You can technically run application pods there, but experienced teams avoid that because noisy workloads can starve the services that make the... Azure Kubernetes Service intermediate 4 commands Aliases: AKS system pool, system mode node pool, AKS platform node pool, kube-system node pool 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

AI and Machine Learning verified RAG Retrieval-augmented generation grounds generative AI responses in retrieved enterprise content instead of relying only on model training. In Azure, RAG commonly combines Azure AI Search indexes, grounding data, embeddings, and an Azure OpenAI or Foundry model to answer using current, domain-specific information. Generative AI advanced 5 commands Aliases: Retrieval augmented generation, retrieval-augmented generation 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

Analytics learning-path-anchor Synapse Spark pool A Synapse Spark pool is the workspace compute definition Azure Synapse uses to start Apache Spark sessions. It records node size, node count, autoscale behavior, runtime version, packages, and idle timeout so notebooks, Spark jobs, and pipelines get repeatable distributed processing. Synapse Analytics fundamentals 8 commands Aliases: Apache Spark pool, Spark pool, Synapse Apache Spark pool, serverless Spark pool Quick peek Open full term page

Analytics learning-path-anchor Synapse workspace managed identity A Synapse workspace managed identity is the workspace's own identity in Microsoft Entra ID. Instead of saving passwords, keys, or connection strings inside pipelines and notebooks, Synapse can use this identity to ask for tokens and reach trusted Azure resources. It is commonly used for Data Lake Storage, Key Vault, SQL, and linked service... Synapse Analytics intermediate 8 commands Aliases: Synapse managed service identity, Synapse MSI, workspace system-assigned identity, Synapse workspace identity Quick peek Open full term page

Web premium App Service private endpoint An App Service private endpoint uses Azure Private Link to give an app a private IP address in a virtual network for inbound client access. App Service Networking intermediate 6 commands Aliases: No aliases yet Quick peek Open full term page

Developer Tools premium Azure CLI A cross-platform command-line tool for connecting to Azure and executing administrative commands on Azure resources. Command line fundamentals 6 commands Aliases: az, Azure command-line interface Quick peek Open full term page

Storage premium File service endpoint A File service endpoint is the Azure Storage endpoint used by clients and services to access Azure Files shares in a storage account through supported protocols and network paths. Teams use it to connect applications, users, file sync agents, and automation to Azure file shares through the correct public endpoint, private endpoint, or virtual network service endpoint path. It is not a file share itself, a private endpoint by itself, a DNS record alone, authorization proof, or a guarantee that SMB, NFS, FileREST, firewall, and identity settings all match. Azure Files intermediate 6 commands Aliases: Azure Files endpoint, storage file endpoint, file endpoint, Azure Storage file service endpoint 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 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 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 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 Hybrid search Hybrid search in Azure AI Search combines vector search and keyword or full-text search in a single request and merges the results. Azure AI Search advanced 5 commands Aliases: Hybrid search, hybrid search Quick peek Open full term page

AI and Machine Learning premium Input token Input token controls how much information an AI request can send to the model and how that request consumes quota, cost, latency, and context capacity. Teams see it in azure openai requests, chat completions. It is not an output token, API key, authentication token, session token, or tokenizer algorithm; confusing them can create truncated prompts, high cost. Use the term when reviewing access, monitoring, cost, recovery, or performance. It keeps architects, operators, security reviewers, and support teams focused on the same setting, resource, or behavior. Azure OpenAI Fundamentals 5 commands Aliases: prompt token, input tokens, request tokens, model input token, context input token Quick peek Open full term page

AI and Machine Learning premium Jailbreak detection Jailbreak detection is the AI safety capability that identifies prompts or embedded document instructions attempting to bypass system rules, policies, or intended model behavior. AI safety intermediate 5 commands Aliases: Prompt Shields, prompt attack detection, jailbreak risk detection, user prompt attack detection, document attack detection Quick peek Open full term page

AI and Machine Learning premium Knowledge source Knowledge source controls which indexed or remote content an agentic retrieval workflow can query before ranking and returning grounding material to an AI application. Teams see it in knowledge base definitions, azure ai search services. It is not a search index, data source connection, knowledge store, vectorizer, skillset, or generic document library; confusing them can create ungrounded answers, wrong content source. Use the term when reviewing access, monitoring, cost, recovery, or performance. It keeps architects, operators, security reviewers, and support teams focused on the same setting, resource, or behavior. Azure AI Search Intermediate 5 commands Aliases: Azure AI Search knowledge source, agentic retrieval knowledge source, indexed knowledge source, remote knowledge source Quick peek Open full term page

Containers premium Kubernetes DaemonSet A Kubernetes DaemonSet is a workload controller that ensures a copy of a pod runs on selected nodes, commonly for logging agents, monitoring collectors, security agents, and node-level services. Kubernetes workloads Intermediate 5 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning premium Search semantic configuration A search semantic configuration is an Azure AI Search index setting that names the fields used by semantic ranker. It prioritizes title, content, and keyword fields so semantic ranking, captions, and answers can evaluate the most meaningful document text during semantic queries. Search advanced 5 commands Aliases: Azure AI Search semantic configuration, semantic search configuration, semantic ranker configuration, prioritized fields, semantic config Quick peek Open full term page

Analytics learning-path-anchor Synapse SQL CETAS Synapse SQL CETAS means CREATE EXTERNAL TABLE AS SELECT. It creates external table metadata and exports the result of a T-SQL SELECT statement in parallel to files in Azure Storage or Azure Data Lake Storage Gen2 for later SQL or lake consumption. Synapse Analytics fundamentals 6 commands Aliases: CREATE EXTERNAL TABLE AS SELECT, CETAS, Synapse CETAS, serverless SQL CETAS Quick peek Open full term page

Analytics learning-path-anchor Synapse SQL external table A Synapse SQL external table is database metadata that lets Synapse SQL query files stored outside the database, usually in Azure Storage or ADLS Gen2. It references an external data source, file format, and file location for governed SQL analytics. Synapse Analytics fundamentals 6 commands Aliases: external table in Synapse, Synapse external table, SQL external table, external table over lake files Quick peek Open full term page

Analytics learning-path-anchor Synapse SQL on-demand Synapse SQL on-demand is the serverless SQL pool model in Azure Synapse Analytics. It lets teams run T-SQL queries over data in the lake without provisioning dedicated warehouse capacity, storing only metadata objects while using external data sources, views, functions, and security objects. Synapse Analytics fundamentals 6 commands Aliases: SQL on-demand, Synapse serverless SQL, serverless SQL in Synapse, built-in serverless SQL pool Quick peek Open full term page

Analytics learning-path-anchor Synapse Studio Synapse Studio is the browser-based workspace experience for Azure Synapse Analytics. It exposes hubs for data, development, integration, monitoring, and management, letting users author notebooks and SQL scripts, build pipelines, configure connections, review access, and work with Git-backed or live artifacts. Synapse Analytics fundamentals 6 commands Aliases: Azure Synapse Studio, Synapse web workspace, Synapse workspace UI, Synapse authoring experience Quick peek Open full term page

Analytics learning-path-anchor Synapse workspace firewall A Synapse workspace firewall is the IP allowlist around a Synapse workspace when it accepts public network traffic. It decides which client IPv4 ranges can attempt to connect before identity permissions are evaluated. It does not grant access by itself; a user or service still needs the right Azure, Synapse, or SQL permissions. It... Synapse Analytics intermediate 6 commands Aliases: Synapse IP firewall rule, workspace firewall rule, Synapse workspace IP allowlist, Synapse public endpoint firewall Quick peek Open full term page

Storage learning-path-anchor Sync group A sync group is the container that tells Azure File Sync which cloud file share and which Windows Server folders should stay synchronized. Think of it as one file namespace with a hub in Azure and one or more on-premises or edge locations attached to it. If two groups represent different shares or business... Files, queues, and tables fundamentals 6 commands Aliases: Azure File Sync group, file sync group, sync topology, storage sync group 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 Agent tool Agent tool is a capability an agent can invoke to search, run code, query data, call APIs, or perform a configured action. In everyday Azure work, teams use it to let an agent go beyond text generation by grounding answers or carrying out controlled work. The useful evidence is tool type, configuration, authentication method, allowed Microsoft Foundry intermediate 4 commands Aliases: Foundry agent tool, AI agent tool, agent built-in tool, agent custom tool 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

Networking premium Application Gateway Application Gateway is an Azure web traffic load balancer for HTTP and HTTPS applications. It routes requests by host name, path, listener, rule, backend pool, and health status, and can add TLS termination and Web Application Firewall controls when those features are configured. Application delivery fundamentals 4 commands Aliases: Azure Application Gateway, App Gateway, regional layer 7 load balancer, HTTP application load balancer 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

AI and Machine Learning premium Azure AI Search skillset Azure AI Search skillset is a reusable Azure AI Search enrichment object that applies built-in or custom processing during indexer execution. AI platform and search intermediate 4 commands Aliases: AI enrichment skillset, Search skillset, cognitive skillset, skillset Quick peek Open full term page

Hybrid and Multicloud premium Azure Arc A hybrid and multicloud management platform that extends Azure governance, security, operations, and services to resources running outside Azure. Hybrid management fundamentals 4 commands Aliases: Arc, Arc-enabled infrastructure, Azure Arc hybrid management Quick peek Open full term page

Hybrid and Multicloud premium Azure Arc-enabled Kubernetes An Azure Arc capability that connects Kubernetes clusters running anywhere to Azure for centralized management, governance, security, and application operations. Hybrid management fundamentals 4 commands Aliases: Arc-enabled Kubernetes, Azure Arc Kubernetes, connected Kubernetes cluster Quick peek Open full term page

Storage premium Azure Storage Mover Azure Storage Mover is a fully managed migration service that helps move files and folders from on-premises or AWS S3 sources to Azure Storage while minimizing workload downtime. Storage migration intermediate 4 commands Aliases: No aliases yet Quick peek Open full term page

Web premium Custom container web app an Azure App Service web app that runs a team-supplied container image instead of a built-in runtime stack. App Service intermediate 4 commands Aliases: App Service custom container, Web App for Containers, containerized App Service app Quick peek Open full term page

Management and Governance premium DeployIfNotExists effect The DeployIfNotExists effect is an Azure Policy effect that runs a template deployment when a related required resource or configuration is missing. Azure Policy advanced 4 commands Aliases: DINE effect, deploy if not exists, Azure Policy DeployIfNotExists, policy remediation deployment Quick peek Open full term page

AI and Machine Learning premium Function calling Function calling is an AI application pattern where a model chooses a developer-defined tool and returns structured arguments so the application can call real business logic. Teams use it to let assistants retrieve data, create tickets, schedule work, search systems, or call APIs while the application remains responsible for execution and validation. In daily Azure work, it shows up when engineers build agents, connect chat to backend tools, audit model-selected actions, validate JSON arguments, or debug why a model called the wrong function. Azure OpenAI advanced 4 commands Aliases: tool calling, OpenAI function calling, model tool call 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