AZ-104 scenario questions are rarely difficult because Azure has only one possible feature. They are difficult because several features can sound plausible until the exact requirement is isolated. A candidate might need to choose between RBAC and Azure Policy, between redundancy and backup, between an NSG and a route, or between scaling and availability. The right answer comes from identifying the layer and failure model first.<\/p>\n
The current 2026 blueprint supports this style of reasoning across identities and governance, storage, compute, virtual networking, monitoring, and recovery. Scenario practice should therefore train a repeatable decision process: identify the desired outcome, identify the scope, note the constraints, eliminate controls that solve a different problem, and choose the simplest option that satisfies all requirements.<\/p>\n
Use the AZ-104 exam<\/a> objectives to keep scenarios realistic. A good practice question should test an administrative decision that Microsoft explicitly measures, not an obscure feature outside the role.<\/p>\n Suppose a team needs permission to restart virtual machines in one resource group but should not manage storage accounts elsewhere. This is an authorization problem. The important facts are the required action and the scope. Azure RBAC is the natural control, and the assignment should be no broader than necessary.<\/p>\n Now change the requirement: every new resource in the subscription must include an approved tag, or deployment should be blocked in unapproved regions. That is a governance condition rather than a permission question. Azure Policy is designed to evaluate or enforce resource-state rules. A resource lock would not implement the same requirement.<\/p>\n Scenario practice around Azure RBAC<\/a> should therefore begin by asking, \u201cIs the problem about what an identity may do, or about what state the resource environment must maintain?\u201d<\/p>\n Storage scenarios often contain words such as \u201cresilient,\u201d \u201crecover,\u201d \u201creplicate,\u201d or \u201cprotect,\u201d but those words do not always point to the same feature. Storage redundancy determines how Azure maintains copies across hardware or locations. Soft delete and versioning protect against logical deletion or unwanted changes. Backup creates managed recovery points. Site Recovery supports workload continuity through replication and failover.<\/p>\n If a requirement is to recover a blob after a user accidentally deletes it, increasing geographic redundancy does not directly solve that logical deletion. If a requirement is to keep data durable through a datacenter failure, a local-only configuration may be insufficient. If a workload needs a defined restore point, backup semantics matter.<\/p>\n Working through Azure Storage protection<\/a> together with Azure Backup<\/a> helps candidates map each feature to the event it is intended to handle.<\/p>\n When a VM cannot reach another service, avoid jumping directly to the most familiar networking feature. Start with the path. What source address and subnet are involved? What destination should be reached? Which route applies? Which DNS name or IP address is being used? Which security rules evaluate the traffic? Is a private endpoint or service endpoint changing the access model?<\/p>\n An NSG can block traffic, but it cannot repair a wrong route. A user-defined route can change the next hop, but it does not authorize a port. DNS can point a client to the wrong endpoint even when routing and NSG rules are correct. A load balancer can have healthy configuration while its backend probe fails because the application is not listening.<\/p>\n Use virtual networks<\/a> and network security groups<\/a> as a paired mental model: routing determines path, security rules determine permission, and name resolution determines which destination the client attempts to reach.<\/p>\n A scenario may mention multiple virtual machines and high availability, which makes Azure Load Balancer tempting. But ask what the requirement says. If traffic must be distributed across healthy backend instances, load balancing fits. If the problem is that a single VM needs protection from a datacenter failure, availability zones or sets may be the more direct compute control. If capacity must expand and contract with demand, a scale set or service-specific scaling mechanism may be more important.<\/p>\n Azure Load Balancer<\/a> questions often hinge on health probes, frontend configuration, backend pools, rules, and whether the load balancer is internal or public. A probe that fails changes which instances receive traffic even when the VMs themselves are running.<\/p>\n Scenario discipline prevents a common error: selecting a valid Azure service that solves a neighboring problem rather than the requirement that was actually stated.<\/p>\n If a requirement needs full operating-system control, a virtual machine may be appropriate. If the requirement is to run a container without managing a VM, Azure Container Instances or Container Apps may fit. If the workload is a web application that benefits from managed scaling, TLS, custom domains, deployment slots, and platform operations, App Service may be a better answer.<\/p>\n The exam does not expect candidates to choose platforms based only on \u201cmodern\u201d versus \u201ctraditional.\u201d It expects them to respect requirements such as management overhead, scaling, networking, availability, deployment behavior, and administrative control.<\/p>\n For containers, Azure Container Instances<\/a> is useful to understand because it demonstrates the managed-container option without adding the cluster-administration concerns of Kubernetes.<\/p>\n Suppose users report intermittent connectivity. A scenario may offer configuration changes and diagnostic tools. If the cause is not yet known, the best administrative step may be to gather evidence with Azure Monitor, Network Watcher, Connection Monitor, effective routes, or effective security rules rather than immediately changing production settings.<\/p>\n Azure Monitor<\/a> scenarios should be read by signal type. Metrics provide numeric time-series behavior. Logs provide detailed searchable records. Alerts evaluate conditions and invoke action groups. Insights provide curated views for supported resource types. The requirement usually indicates which signal or action is needed.<\/p>\n A good rule is to separate detection, diagnosis, and remediation. An alert can detect. Logs and network tools can diagnose. A configuration change can remediate. The exam may ask for any one of those stages.<\/p>\n Words such as \u201call subscriptions,\u201d \u201cone resource group,\u201d \u201cnew resources,\u201d or \u201cmanagement group\u201d are rarely decorative. They define the scope where a role, policy, tag strategy, or budget should be applied. If the desired effect must cover several subscriptions, configuring each resource individually is usually a sign that the solution is being applied too low in the hierarchy.<\/p>\n The same principle works in reverse. If only one resource needs a special permission, a subscription-wide assignment is broader than necessary. AZ-104 frequently rewards candidates who choose the narrowest correct scope rather than the most powerful setting.<\/p>\n This scope awareness also supports cost management. Budgets, alerts, and Advisor recommendations are useful only when they are attached to the organizational level that matches the reporting or control requirement.<\/p>\n A restore requirement is different from a failover requirement. A backup policy can create recovery points for later restore. Site Recovery is designed around replicated workloads and failover. Availability zones keep running capacity across zone boundaries but do not provide historical restore points. Storage redundancy keeps platform copies but does not automatically produce application-consistent recovery across an entire workload.<\/p>\n In a scenario, look for recovery point objective, recovery time expectations, regional failure, accidental deletion, or the need to restore a specific object or workload. Those details point toward the correct protection model.<\/p>\n Also remember the operational side: the current blueprint includes backup reports and alerts. If the requirement is to know when protection fails, configuring backup alone is incomplete; monitoring the protection process is part of the solution.<\/p>\n For every scenario, classify the problem before reading answer choices too closely. Is this primarily identity, authorization, governance, storage access, data protection, compute placement, connectivity, traffic distribution, monitoring, or recovery? Then identify scope and constraints. Only after that should you choose the Azure feature.<\/p>\n This prevents answer choices from steering your reasoning. Microsoft often presents several legitimate services. Candidates who begin with service names can be distracted by familiarity. Candidates who begin with the operational requirement can eliminate attractive but mismatched choices.<\/p>\nSeparate authorization from governance before choosing a control<\/h3>\n
Distinguish data availability from data recovery<\/h3>\n
Trace network scenarios from source to destination<\/h3>\n
Choose load balancing only when the requirement is actually traffic distribution<\/h3>\n
Read compute scenarios for management model as well as workload type<\/h3>\n
Use monitoring scenarios to identify evidence before action<\/h3>\n
Watch for scope and inheritance clues in governance scenarios<\/h3>\n
Use recovery scenarios to identify the required recovery behavior<\/h3>\n
Build a decision tree that starts with the requirement, not the product<\/h3>\n