AZ-900 · Practice set 5 of 5
Cloud Economics and Serverless: 10 practice questions
10 free AZ-900 practice questions on Cloud Economics and Serverless, with an explanation for every answer. Untimed. The full mock exam and the timed version are in the app.
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Question 1 of 10
What defines the consumption-based cloud model?
- ACustomers retain every resource after demand decreases
- BCustomers pay for the IT resources they use
- CBuy maximum capacity before using it
- DCustomers pay for idle hardware kept permanently on-site
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Look at the word consumption. In this model, spending tracks real resource usage rather than a flat purchase order. You can rent resources when needed and remove unneeded capacity after demand drops. Allocated resources can still cost money while idle.
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Question 2 of 10
Which purchase is a capital expenditure?
- ACPU charges while a function executes
- BRecurring service spending that changes with workload use
- COngoing spending for cloud services as they are consumed
- DUpfront spending on servers and datacenter space
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An upfront purchase is the clue. You spend money on physical infrastructure, such as servers and datacenter space, before you use it. That makes the purchase capital expenditure. When you pay over time for services as you use them, that spending is operational expenditure.
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Question 3 of 10
What characterizes Azure Functions as a serverless compute option?
- ATeams maintain containers that remain provisioned while no events occur
- BCustomers must run and patch virtual machines for Azure Functions between events
- CDatacenter hardware must be purchased before a function can receive events
- DEvents trigger code without requiring virtual machine or container maintenance
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Focus on the two core conditions of serverless: event-driven execution and zero platform maintenance. Azure Functions runs code when triggered by requests, timers, or messages from other services. You focus purely on code without managing underlying virtual machines or customer-managed containers.
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Question 4 of 10
What is the risk of overestimating capacity in a traditional datacenter?
- AThe provider deallocates resources as soon as an event finishes
- BThe organization pays for infrastructure that remains idle
- CThe application degrades because too little hardware was purchased
- DExcess hardware is released from the site
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Identify the financial consequence of buying more capacity than needed. In a traditional datacenter, purchased servers stay on-site as owned assets. When you overestimate demand, that excess capacity sits idle, meaning you pay the full purchase price for infrastructure nobody uses.
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Question 5 of 10
Why is consumption-based cloud spending classified as operational expenditure?
- AIt is ongoing spending on services as they are used
- BCapacity stays fixed before workload use
- CIt requires ownership of datacenter space before service use
- DIt is an upfront purchase of physical servers and network hardware
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Apply the classification test: when the money is paid and what it buys. Operational expenditure pays for consumed services over time as they are used, like an hourly virtual machine. Capital expenditure buys physical servers upfront before anything runs, regardless of how payments are financed.
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Question 6 of 10
Which event can trigger an Azure Function according to the serverless model?
- AA hardware purchase before each request
- BA manual container restart required before every code execution
- CA timer, REST request, or message from another Azure service
- DA permanent allocation of idle virtual machines without an event
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Match the triggers named in the serverless model. Common examples include a REST request, a timer, or a message from another Azure service. Azure Functions executes code in response to these events, whether its hosting plan scales to zero or keeps instances allocated.
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Question 7 of 10
On a consumption-based Azure Functions hosting plan, how can resource use align with demand?
- AThe app cannot scale automatically and must keep a fixed instance count.
- BThe app requires customer-owned server hardware and an upfront purchase.
- CThe app must retain an always-ready instance and charges a fixed monthly amount.
- DThe app can scale to zero while idle, and charges follow executions and resource consumption.
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Look for the twin benefits of eligible consumption-based hosting: scaling to zero and consumption billing. When no events occur, the function app can scale to zero so idle capacity costs nothing. During activity, it scales automatically, and charges follow actual executions and resource consumption.
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Question 8 of 10
A retailer expects a brief seasonal demand spike and wants to avoid owning unused capacity afterward. Which approach fits?
- APurchase fixed maximum capacity and treat idle infrastructure as consumed capacity
- BUnderestimate peak demand and postpone hardware orders until performance degrades
- CBuy permanent datacenter capacity for the peak and keep it after demand falls
- DAdd cloud resources for the spike, then release them as demand falls
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Use the seasonal business example from consumption-based cloud economics. Spending tracks real usage rather than a flat purchase order. You add resources when demand peaks and release them when demand falls, so the bill follows the same curve and you avoid paying for idle capacity afterward.
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Question 9 of 10
A team needs short code execution when a service message arrives, with no resources provisioned between messages. Which option fits?
- AA customer-maintained container reserved while no messages arrive.
- BAn Azure Function on a dedicated plan that retains allocated instances.
- CAn on-site server purchased and left idle between messages.
- DAn Azure Function triggered by the message on a hosting plan that can scale to zero.
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The clues are a message trigger and a need to avoid allocated resources between messages. Azure Functions runs code when a message arrives from another Azure service. On an eligible consumption-based hosting plan, the app can scale to zero while idle, which fits that need.
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Question 10 of 10
A company underestimated demand for its traditional datacenter, and application performance is degrading. What remediation does that model require?
- AOrder, install, and provision additional hardware, power, and cooling
- BWait for a serverless trigger to deallocate the overloaded physical hosts
- CRelease cloud resources immediately and continue with less installed capacity
- DConvert the existing hardware purchase into usage-based CPU billing automatically
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When your traditional datacenter has too little capacity, the application can run slowly. To correct that underestimate, you must order, install, and provision more hardware, power, and cooling. This sequence takes weeks while the application keeps running slowly.
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