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Monitoring and Observability premium Error rate Error rate is the proportion of requests, operations, or events that fail compared with the total volume over a defined time window. Metrics and SRE fundamentals 4 commands Aliases: error rate Quick peek Open full term page

Monitoring and Observability premium Platform metrics Platform metrics are numeric measurements that Azure resources emit and Azure Monitor collects at regular intervals. They describe resource health, capacity, utilization, latency, throughput, failures, and dimensions over time, helping operators chart behavior, create alerts, and diagnose service conditions quickly. Monitoring fundamentals 5 commands Aliases: Azure platform metrics, Azure Monitor platform metrics, resource metrics 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

Storage complete Storage account metrics Microsoft Learn lists storage account metrics as Azure Monitor measurements for Microsoft.Storage accounts. They expose signals such as availability, transactions, capacity, latency, ingress, egress, errors, and service-level dimensions so operators can watch storage behavior, alert on problems, and trend usage over time. Storage accounts advanced 5 commands Aliases: Azure Storage metrics, storage metrics, storage account Azure Monitor metrics, Microsoft.Storage metrics Quick peek Open full term page

Monitoring and Observability field-manual-complete Live Metrics Microsoft Learn describes Live Metrics in Application Insights as real-time monitoring for web applications. It lets teams watch selected metrics and performance counters live, filter telemetry, and inspect sample failed requests or exceptions while an application is running. Application Insights fundamentals 2 commands Aliases: No aliases yet 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

Monitoring and Observability premium Error budget An error budget is the amount of unreliability a service can consume while still meeting its service level objective over a defined measurement window. SRE and reliability intermediate 4 commands Aliases: error budget Quick peek Open full term page

Databases learning-path-anchor Synthetic partition key A synthetic partition key is a partition key value you create because no single natural field distributes Cosmos DB data well enough. For example, tenantId alone may create one huge tenant partition, while date alone may concentrate today's traffic. A synthetic key might combine tenant, region, and date bucket into one stored value that... Cosmos DB intermediate 5 commands Aliases: generated partition key, composite partition key value, calculated partition key, synthetic key 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

Databases learning-path-anchor Temporary bytes Disk space used by temporary files created during queries, sorts, hashes, or joins. PostgreSQL advanced 4 commands Aliases: Temporary bytes, temporary bytes, Azure Temporary bytes, temp_bytes, Temporary Files Size, PostgreSQL temporary files Quick peek Open full term page

Monitoring and Observability learning-path-anchor Throughput Throughput is the amount of work a system completes over time, such as requests, messages, bytes, events, or transactions per second. In Azure, teams measure it with service metrics, logs, and capacity settings to judge whether an app, database, storage account, or messaging pipeline can sustain demand. Performance intermediate 4 commands Aliases: Throughput, throughput, Azure Throughput, Microsoft Learn Throughput, requests per second, events per second, transactions per second, bytes per second, work completed over time Quick peek Open full term page

Databases learning-path-anchor Cosmos DB dedicated gateway Azure Cosmos DB dedicated gateway is provisioned server-side compute that fronts an account and enables the integrated cache for supported NoSQL workloads. Azure Cosmos DB fundamentals 3 commands Aliases: No aliases yet 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

Databases premium Conflict resolution policy the container-level Cosmos DB setting that defines how write conflicts are resolved when more than one region can update the same data Cosmos DB intermediate 15 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning premium Computer Vision the Azure AI capability that helps applications understand images, read text, detect visual features, and return structured insights from pictures or screenshots Azure AI services fundamentals 12 commands Aliases: No aliases yet Quick peek Open full term page

Databases premium Cosmos DB trigger Cosmos DB trigger is a registered JavaScript pre-trigger or post-trigger for Cosmos DB for NoSQL operations inside a container. It runs server-side logic around an item operation when application code explicitly asks Cosmos DB to use it. You see it when teams maintain legacy NoSQL scripts, troubleshoot write behavior, or compare triggers with change feed and Azure Functions. The production check is whether the trigger is necessary, explicitly invoked, partition-scoped, tested, and safer than handling the logic in application code. Document the decision in code, templates, metrics, and runbooks. Azure Cosmos DB intermediate 8 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning premium Search analyzer A search analyzer is the Azure AI Search text-processing component that breaks strings into searchable tokens during indexing and query execution. Built-in, language, or custom analyzers control tokenization, normalization, stemming, stop words, and other lexical behavior for searchable string fields. Azure AI Search fundamentals 8 commands Aliases: Azure AI Search analyzer, text analyzer, search text analyzer, custom analyzer, language analyzer Quick peek Open full term page

Databases premium Cosmos DB physical partition Cosmos DB physical partition means a fully managed internal storage and compute partition that hosts ranges of logical partition keys in Azure Cosmos DB. In plain English, it is the thing developers and operators check when they need to understand how data access really works. It connects the application model to automatic scale-out, replica placement, RU distribution, and operational signals such as hot partition diagnostics. For a production team, it turns vague database talk into a specific thing to inspect in the portal, SDK code, templates, metrics, and incident notes. Azure Cosmos DB intermediate 7 commands Aliases: No aliases yet Quick peek Open full term page

Databases premium Cosmos DB provisioned throughput Cosmos DB provisioned throughput means the request-unit-per-second capacity reserved for a database or container, either manually or with autoscale behavior in Azure Cosmos DB. In plain English, it is the thing developers and operators check when they need to understand how data access really works. It connects the application model to capacity planning, throttling prevention, RU allocation, cost control, and predictable performance for operational workloads. For a production team, it turns vague database talk into a specific thing to inspect in the portal, SDK code, templates, metrics, and incident notes. Azure Cosmos DB intermediate 7 commands Aliases: No aliases yet Quick peek Open full term page

Databases premium Cosmos DB spatial index Cosmos DB spatial index is an indexing-policy entry that helps Cosmos DB for NoSQL query valid GeoJSON points, lines, polygons, and multipolygons efficiently. It makes location-aware queries practical without scanning every item in a container. You see it when applications store coordinates, service areas, delivery zones, device positions, or map features in JSON items. The production check is whether GeoJSON shape, indexed path, query function, and partition strategy all line up. Document the decision in code, templates, metrics, and runbooks. Azure Cosmos DB intermediate 7 commands Aliases: No aliases yet Quick peek Open full term page

Databases premium Cosmos DB vector embedding policy Cosmos DB vector embedding policy is the container policy that defines vector paths, dimensions, data type, and distance function for embeddings stored in Cosmos DB for NoSQL. It tells Cosmos DB which item properties contain embeddings and how those vectors should be interpreted. You see it when teams build semantic search, recommendation, image similarity, or retrieval-augmented generation features on Cosmos DB data. The production check is whether the vector path, dimensions, data type, and distance function are correct before production data lands. Document the decision in code, templates, metrics, and runbooks. Azure Cosmos DB intermediate 7 commands Aliases: No aliases yet Quick peek Open full term page

Databases premium Cosmos DB vector index Cosmos DB vector index is an indexing-policy configuration that improves vector-search latency and RU efficiency for embeddings in Cosmos DB for NoSQL. It helps Cosmos DB find similar vectors without comparing every embedding in a container one by one. You see it when queries use VectorDistance, hybrid search combines text and vectors, or teams tune flat, quantized flat, and DiskANN-style index choices. The production check is whether the index type, vector path, dimensions, filters, and recall target fit the workload. Document the decision in code, templates, metrics, and runbooks. Azure Cosmos DB intermediate 7 commands Aliases: No aliases yet 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

Compute premium Azure Functions Azure Functions is Azure serverless compute for running code from triggers such as HTTP requests, queues, timers, events, and service integrations without managing servers. Serverless compute intermediate 6 commands Aliases: Functions, Function App, serverless functions Quick peek Open full term page

Integration premium Capacity unit A capacity measure used by Event Hubs Dedicated clusters. Messaging and eventing intermediate 6 commands Aliases: No aliases yet Quick peek Open full term page

Databases premium Conflict resolution the way Azure Cosmos DB decides the winning version when concurrent writes from multiple regions change the same item or logical record Data platform intermediate 6 commands Aliases: No aliases yet Quick peek Open full term page

Databases premium Cosmos DB serverless Cosmos DB serverless is the Cosmos DB capacity mode that bills for request units consumed and storage used instead of pre-provisioned RU/s. It lets intermittent or unpredictable workloads use Cosmos DB without reserving throughput all day. You see it when a new account is created, a workload has bursty usage, or a team compares serverless with provisioned throughput. The production check is whether consumption billing, throughput limits, regional design, and workload shape fit the production objective. Document the decision in code, templates, metrics, and runbooks. Azure Cosmos DB intermediate 6 commands Aliases: No aliases yet Quick peek Open full term page

Databases premium Cosmos DB serverless account Cosmos DB serverless account is a Cosmos DB account created with the serverless capacity mode so databases and containers are billed by consumed request units and storage. It turns serverless billing into an account-level design choice rather than a per-container toggle. You see it when teams create accounts for prototypes, seasonal apps, low-duty-cycle workloads, or services with uncertain early demand. The production check is whether the account capacity mode supports the API, scale target, compliance need, and migration plan. Document the decision in code, templates, metrics, and runbooks. Azure Cosmos DB intermediate 6 commands Aliases: No aliases yet Quick peek Open full term page

Databases premium Cosmos DB TTL Cosmos DB TTL is the time-to-live setting that lets Cosmos DB automatically delete items after a configured number of seconds. It turns data expiration into a database policy instead of a manual cleanup job. You see it when containers store sessions, events, temporary search data, soft-delete markers, or records with explicit retention windows. The production check is whether container-level TTL, item overrides, change-feed behavior, and recovery expectations match the business retention rule. Document the decision in code, templates, metrics, and runbooks. Azure Cosmos DB intermediate 6 commands Aliases: No aliases yet Quick peek Open full term page

Containers premium Event-driven scale rule An Event-driven scale rule is a Container Apps scaling configuration that uses event-source metrics to decide how many replicas or job executions to run. Teams use it to connect queue length, event backlog, HTTP load, Kafka lag, or other scaler metadata to automatic scaling decisions. It is not the event source itself, a Kubernetes HPA object, a fixed replica count, or a complete guarantee that the application processes events correctly. In production, confirm scaler type, metadata names, authentication method, min and max replicas, polling interval, cooldown behavior, event source metrics, container revision, and downstream capacity before treating the design as. Azure Container Apps intermediate 6 commands Aliases: KEDA scale rule, Container Apps event scale rule, custom scale rule Quick peek Open full term page

AI and Machine Learning premium Experiment An Experiment in Azure Machine Learning groups related runs so parameters, metrics, artifacts, models, and lineage can be tracked and compared. Teams use it to organize model training, evaluation, and tuning work so teams can compare runs and reproduce how a model version was produced. It is not a deployed endpoint, a registered model, a notebook file, a compute cluster, or proof that a model is fair, secure, or production-ready. In production, confirm workspace, experiment name, run IDs, parameters, metrics, artifacts, data version, environment, compute target, model registration, owner, and promotion criteria before treating the design as healthy or ready. Machine learning intermediate 6 commands Aliases: Azure ML experiment, MLflow experiment, machine learning experiment Quick peek Open full term page

Networking premium ExpressRoute ExpressRoute lets organizations extend on-premises networks into Microsoft cloud services over private connectivity provided through a connectivity provider. Teams use it to connect datacenters, branches, or colocation environments to Azure with predictable private paths for workloads that need stronger latency, bandwidth, and routing control than public internet connections. It is not a VPN tunnel, a private endpoint, an internet performance guarantee, or proof that every connected application is secure, redundant, or correctly routed. In production, confirm circuit state, provider state, peering configuration, BGP routes, gateway SKU, connected virtual networks, bandwidth, metrics, DNS path, firewall path, and provider escalation details before. Hybrid connectivity intermediate 6 commands Aliases: Azure ExpressRoute, ExpressRoute circuit, private Microsoft cloud connectivity Quick peek Open full term page

Analytics premium Fabric capacity A Fabric capacity is a dedicated pool of compute resources that powers Microsoft Fabric workloads assigned to workspaces. Teams use it to provide shared compute for Fabric workspaces, reports, lakehouses, warehouses, notebooks, pipelines, and real-time workloads under an assigned capacity SKU. It is not a single workspace, a Power BI report, a storage account, a Databricks cluster, or a guarantee that every tenant workload has unlimited performance. In production, confirm capacity name, SKU, region, admin list, assigned workspaces, workload settings, metrics app evidence, throttling, refresh history, pause state, billing owner, and reservation or scaling plan before treating the design as. Microsoft Fabric intermediate 6 commands Aliases: Microsoft Fabric capacity, Fabric F SKU, Fabric compute capacity Quick peek Open full term page

Integration premium Service Bus Azure Service Bus is a fully managed enterprise message broker with message queues and publish-subscribe topics. It helps decouple applications and services, load-balance work across competing consumers, route data across boundaries, and coordinate transactional workflows that require reliable messaging, ordering, sessions, duplicate detection, and dead-letter handling. Messaging fundamentals 6 commands Aliases: Azure Service Bus, Service Bus Messaging Quick peek Open full term page

Monitoring and Observability premium Action group An Azure Monitor action group defines who gets notified and which actions run when an alert fires. It can include notification receivers such as email, SMS, and push, plus automation actions such as webhooks, secure webhooks, Azure Functions, Logic Apps, runbooks, ITSM, or Event Hubs. Alerts fundamentals 5 commands Aliases: Azure Monitor action group, alert action group, monitor action group Quick peek Open full term page

Databases premium Active connections Active connections are the current database client sessions using a database service. For Azure SQL Database, Azure Monitor exposes this operational signal through metrics such as Sessions count and Sessions percentage, which help operators spot connection leaks, pool pressure, and client behavior that can affect availability. Azure SQL monitoring intermediate 5 commands Aliases: database active sessions, SQL sessions count, database connection count Quick peek Open full term page

Integration premium Advanced event filter Advanced event filter is an Event Grid subscription filter that matches event fields and data values using advanced operators. In everyday Azure work, teams use it to route only the events that a handler actually needs, without creating separate topics for every condition. The useful evidence is event subscription, key path, operator type, values, event Event Grid intermediate 5 commands Aliases: Event Grid advanced filter, advanced filtering, event subscription advanced filter Quick peek Open full term page

Databases premium Azure SQL automatic tuning Azure SQL automatic tuning monitors query performance and can apply tuning actions such as plan correction and index recommendations. Azure SQL Database fundamentals 5 commands Aliases: Azure SQL automatic tuning, Azure SQL tuning recommendations, SQL automatic tuning, automatic tuning Quick peek Open full term page

Databases premium Azure SQL Business Critical tier Azure SQL Business Critical tier is a vCore service tier for OLTP workloads that need high transaction rates, low-latency I/O, and high resilience through isolated replicas. Azure SQL Database fundamentals 5 commands Aliases: Azure SQL Business Critical tier, Business Critical tier, BusinessCritical, Premium-like vCore tier, SQL Business Critical Quick peek Open full term page

Databases premium Azure SQL Database DTU model Azure SQL Database DTU model is a purchasing model that bundles compute, storage, and I/O resources into Database Transaction Units for Basic, Standard, and Premium tiers. Azure SQL Database fundamentals 5 commands Aliases: Azure SQL Database DTU model, DTU model, DTU-based purchasing model, Database Transaction Unit, eDTU Quick peek Open full term page

Databases premium Azure SQL elastic job Azure SQL elastic jobs schedule and run Transact-SQL scripts across one or many Azure SQL databases, including target groups across servers, pools, and subscriptions. Azure SQL Database fundamentals 5 commands Aliases: Azure Elastic Jobs, Azure SQL elastic job, SQL elastic job agent, elastic job agent, elastic jobs Quick peek Open full term page

Databases premium Azure SQL elastic pool Azure SQL elastic pool lets multiple Azure SQL databases on one logical server share a set of resources at a set price for variable usage patterns. Azure SQL Database fundamentals 5 commands Aliases: Azure SQL elastic pool, SQL elastic pool, eDTU pool, elastic pool, pooled databases Quick peek Open full term page

Databases premium Azure SQL General Purpose tier Azure SQL General Purpose tier is a vCore service tier for common workloads that need balanced compute and storage at budget-oriented pricing. Azure SQL Database fundamentals 5 commands Aliases: Azure SQL General Purpose tier, GP tier, General Purpose tier, GeneralPurpose, SQL General Purpose Quick peek Open full term page

Databases premium Azure SQL geo-restore Azure SQL geo-restore uses geo-replicated backups to restore a database to any logical server in any Azure region when primary-region access is unavailable. Azure SQL Database fundamentals 5 commands Aliases: Azure SQL geo-restore, SQL geo restore, geo-replicated backup restore, geo-restore, regional backup restore Quick peek Open full term page

Storage premium Backup item A backup item is a protected data source or backup instance in Azure Backup that is associated with a vault, policy, retention settings, and recoverable restore points. Backup and recovery intermediate 5 commands Aliases: No aliases yet Quick peek Open full term page

DevOps premium Canary deployment Canary deployment is a release approach that sends a small portion of real traffic to a new version before rolling it out broadly. Deployment workflows intermediate 5 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning premium Confidence score a model-provided certainty value that helps teams judge whether extracted fields, text, tables, or classifications should be accepted automatically or reviewed by a person Document Intelligence fundamentals 5 commands Aliases: No aliases yet Quick peek Open full term page