Amazon AWS SAA-C03 Cost-Optimized Compute, Purchasing Models, Rightsizing, and Elasticity Practice Test 2

 

Topic 18 Practice Test 2 covers Cost-Optimized Compute, Purchasing Models, Rightsizing, and Elasticity for AWS SAA-C03. For broader exam preparation, review the AWS SAA-C03 Exam Dumps. Every option includes focused technical reasoning explaining both the AWS architecture concept and its fit to the scenario.

Question 1

A fleet of manually sized EC2 servers has six weeks of CloudWatch history. Several instances appear mostly idle, but the team wants data-backed size recommendations before changing them. Which change most directly allows the workload to identify lower-cost EC2 sizes from measured utilization? Choose ONE.

1. Right-size EC2 instance size
2. AWS Compute Optimizer EC2 rightsizing
3. Cost Explorer Savings Plans recommendations
4. AWS Cost and Usage Report

Correct Answer(s)

 

B

Rationale

1. Right-size EC2 instance size adjusts provisioned EC2 resources to the capacity the workload actually consumes. It is appropriate when reliable metrics show a sustained mismatch between allocated and needed resources. This scenario prioritizes rightsizing confidence: the design must identify lower-cost EC2 sizes from measured utilization. The mismatch makes it less suitable.
2. AWS Compute Optimizer EC2 rightsizing analyzes utilization metrics and recommends better-sized EC2 instance options. Compute Optimizer evaluates resource metrics to recommend rightsizing candidates, providing evidence before the team changes production instance shapes. It meets the need to identify lower-cost EC2 sizes from measured utilization and improves rightsizing confidence.
3. Cost Explorer Savings Plans recommendations estimates commitment levels from eligible historical compute usage and preferences. It is appropriate when an organization wants data-driven Savings Plans purchase guidance. This scenario prioritizes rightsizing confidence: the design must identify lower-cost EC2 sizes from measured utilization. The mismatch makes it less suitable.
4. AWS Cost and Usage Report exports detailed billing and usage line items for granular cost analysis. It is appropriate when teams need raw resource-level charge data for custom analysis or allocation. This scenario prioritizes rightsizing confidence: the design must identify lower-cost EC2 sizes from measured utilization. The mismatch makes it less suitable.

 

Question 2

An EC2 Auto Scaling group scales correctly with demand, but each instance may be larger than necessary. The team wants supported group-level rightsizing recommendations. Which cost-optimization decision best meets the requirement to evaluate the Auto Scaling group instance size for cost efficiency? Choose ONE.

1. AWS Compute Optimizer EC2 rightsizing
2. Minimum viable Auto Scaling capacity
3. Right-size EC2 instance size
4. AWS Compute Optimizer Auto Scaling rightsizing

Correct Answer(s)

 

D

Rationale

1. AWS Compute Optimizer EC2 rightsizing analyzes utilization metrics and recommends better-sized EC2 instance options. It is appropriate when historical workload metrics exist and instances may be over or under provisioned. This scenario prioritizes group compute efficiency: the design must evaluate the Auto Scaling group instance size for cost efficiency. The mismatch makes it less suitable.
2. Minimum viable Auto Scaling capacity keeps only the smallest always-needed baseline while elasticity handles demand. It is appropriate when steady minimum traffic is low and excess idle baseline instances create waste. This scenario prioritizes group compute efficiency: the design must evaluate the Auto Scaling group instance size for cost efficiency. The mismatch makes it less suitable.
3. Right-size EC2 instance size changes an EC2 instance shape so provisioned CPU, memory, and network capacity better match measured demand. It is appropriate when utilization data shows the current instance has persistent excess or resource pressure. This scenario prioritizes group compute efficiency: the design must evaluate the Auto Scaling group instance size for cost efficiency. The mismatch makes it less suitable.
4. AWS Compute Optimizer Auto Scaling rightsizing recommends instance sizing improvements for supported EC2 Auto Scaling groups. The group-specific analysis considers supported Auto Scaling configurations and can identify an oversized instance type even when the scaling policy itself is working. It meets the need to evaluate the Auto Scaling group instance size for cost efficiency and improves group compute efficiency.

 

Question 3

A high-volume Lambda function has stable behavior and enough invocation history. The team wants an evidence-based memory setting that balances duration and cost. The architecture must obtain a recommended Lambda memory configuration from observed execution data. Which option is most cost-effective? Choose ONE.

1. AWS Compute Optimizer Lambda recommendations
2. Lambda arm64 architecture
3. Compute Savings Plans
4. AWS Lambda pay-per-use compute

Correct Answer(s)

 

A

Rationale

1. AWS Compute Optimizer Lambda recommendations recommends Lambda memory settings from observed function performance and cost data. Compute Optimizer can recommend memory settings for supported Lambda functions from observed performance and cost, directly matching the tuning request. It meets the need to obtain a recommended Lambda memory configuration from observed execution data and improves Lambda price performance.
2. Lambda arm64 architecture runs compatible Lambda functions on Arm-based Graviton processors at lower compute pricing. It is appropriate when function code and dependencies support arm64 without emulation. This scenario prioritizes Lambda price performance: the design must obtain a recommended Lambda memory configuration from observed execution data. The mismatch makes it less suitable.
3. Compute Savings Plans apply a committed-rate discount across qualifying EC2 usage and eligible serverless or container compute. It is appropriate when the organization wants one commitment to follow changing compute choices. This scenario prioritizes Lambda price performance: the design must obtain a recommended Lambda memory configuration from observed execution data. The mismatch makes it less suitable.
4. AWS Lambda pay-per-use compute runs event-driven code without paying for idle server capacity between invocations. It is appropriate when work arrives intermittently and fits Lambda execution constraints. This scenario prioritizes Lambda price performance: the design must obtain a recommended Lambda memory configuration from observed execution data. The mismatch makes it less suitable.

 

Question 4

An ECS service on Fargate has run steadily for weeks. Tasks request far more CPU and memory than monitoring shows they use. An architect needs to identify lower task CPU and memory settings from historical usage. What should be selected? Choose ONE.

1. ECS on AWS Fargate
2. Fargate Spot
3. AWS Compute Optimizer ECS Fargate rightsizing
4. Consolidate workloads onto fewer right-sized hosts

Correct Answer(s)

 

C

Rationale

1. ECS on AWS Fargate charges container tasks for requested compute while removing EC2 host management. It is appropriate when container demand varies and avoiding continuously provisioned hosts is valuable. This scenario prioritizes Fargate task efficiency: the design must identify lower task CPU and memory settings from historical usage. The mismatch makes it less suitable.
2. Fargate Spot runs interruption-tolerant ECS tasks on discounted spare Fargate capacity. It is appropriate when container tasks can tolerate a two-minute interruption notice and restart elsewhere. This scenario prioritizes Fargate task efficiency: the design must identify lower task CPU and memory settings from historical usage. The mismatch makes it less suitable.
3. AWS Compute Optimizer ECS Fargate rightsizing recommends task CPU and memory values for eligible ECS services on Fargate. The recommendation targets Fargate task CPU and memory requests, which are the billed dimensions that appear oversized in this service. It meets the need to identify lower task CPU and memory settings from historical usage and improves Fargate task efficiency.
4. Consolidate workloads onto fewer right-sized hosts raises utilization by reducing the number of persistently underused EC2 hosts. It is appropriate when several compatible always-on workloads leave substantial idle CPU and memory. This scenario prioritizes Fargate task efficiency: the design must identify lower task CPU and memory settings from historical usage. The mismatch makes it less suitable.

 

Question 5

A single EC2 application averages 12 percent CPU, uses less than half its memory, and shows low network throughput for a month. Which change most directly allows the workload to reduce persistent overprovisioning while retaining the same deployment model? Choose ONE.

1. Graviton-based EC2 instances
2. EC2 Instance Savings Plans
3. Right-size EC2 instance size
4. Minimum viable Auto Scaling capacity

Correct Answer(s)

 

C

Rationale

1. Graviton-based EC2 instances use Arm-based AWS processors with strong price performance for compatible workloads. It is appropriate when software and dependencies support Arm and cost per unit of work matters. This scenario prioritizes instance utilization efficiency: the design must reduce persistent overprovisioning while retaining the same deployment model. The mismatch makes it less suitable.
2. EC2 Instance Savings Plans discount usage within one EC2 instance family in a selected Region. It is appropriate when steady EC2 use stays in one family and Region while size may change. This scenario prioritizes instance utilization efficiency: the design must reduce persistent overprovisioning while retaining the same deployment model. The mismatch makes it less suitable.
3. Right-size EC2 instance size changes an EC2 instance shape so provisioned CPU, memory, and network capacity better match measured demand. Measured sustained headroom indicates the current shape is oversized, so reducing instance size lowers recurring cost without changing the application architecture. It meets the need to reduce persistent overprovisioning while retaining the same deployment model and improves instance utilization efficiency.
4. Minimum viable Auto Scaling capacity keeps only the smallest always-needed baseline while elasticity handles demand. It is appropriate when steady minimum traffic is low and excess idle baseline instances create waste. This scenario prioritizes instance utilization efficiency: the design must reduce persistent overprovisioning while retaining the same deployment model. The mismatch makes it less suitable.

 

Question 6

A development EC2 server uses EBS-backed storage, is needed only from 08:00 to 18:00 on weekdays, and must preserve its disk state overnight. Which cost-optimization decision best meets the requirement to eliminate compute charges during predictable off-hours while keeping the server state? Choose ONE.

1. Scheduled stop and start for nonproduction EC2
2. Scheduled Auto Scaling to zero
3. Spot Instances
4. On-Demand Instances

Correct Answer(s)

 

A

Rationale

1. Scheduled stop and start for nonproduction EC2 removes EC2 compute charges while stopped outside known working hours. Stopping an EBS-backed instance removes compute charges while preserving its volumes, matching a single persistent server that can be offline overnight. It meets the need to eliminate compute charges during predictable off-hours while keeping the server state and improves nonproduction idle cost.
2. Scheduled Auto Scaling to zero sets nonproduction group capacity to zero during known idle periods. It is appropriate when a stateless environment is unnecessary outside a predictable schedule. This scenario prioritizes nonproduction idle cost: the design must eliminate compute charges during predictable off-hours while keeping the server state. The mismatch makes it less suitable.
3. Spot Instances lower EC2 compute price by accepting reclaimable spare-capacity instances. It is appropriate when the application is designed to survive instance interruption without losing critical state. This scenario prioritizes nonproduction idle cost: the design must eliminate compute charges during predictable off-hours while keeping the server state. The mismatch makes it less suitable.
4. On-Demand Instances provide noninterruptible EC2 usage with no one- or three-year spend obligation. It is appropriate when future demand is unclear and purchase flexibility is more valuable than commitment discounts. This scenario prioritizes nonproduction idle cost: the design must eliminate compute charges during predictable off-hours while keeping the server state. The mismatch makes it less suitable.

 

Question 7

A stateless test environment is an Auto Scaling group and must be completely absent outside business hours. It can be recreated automatically each morning. The architecture must remove all group compute capacity during predictable idle periods. Which option is most cost-effective? Choose ONE.

1. Scheduled stop and start for nonproduction EC2
2. Minimum viable Auto Scaling capacity
3. Spot Instances
4. Scheduled Auto Scaling to zero

Correct Answer(s)

 

D

Rationale

1. Scheduled stop and start for nonproduction EC2 removes EC2 compute charges while stopped outside known working hours. It is appropriate when EBS-backed development servers are idle on a predictable schedule and may be offline. This scenario prioritizes test environment idle cost: the design must remove all group compute capacity during predictable idle periods. The mismatch makes it less suitable.
2. Minimum viable Auto Scaling capacity keeps only the smallest always-needed baseline while elasticity handles demand. It is appropriate when steady minimum traffic is low and excess idle baseline instances create waste. This scenario prioritizes test environment idle cost: the design must remove all group compute capacity during predictable idle periods. The mismatch makes it less suitable.
3. Spot Instances supply substantially discounted EC2 capacity in exchange for interruption tolerance. It is appropriate when queued or distributed jobs can resume elsewhere when capacity is reclaimed. This scenario prioritizes test environment idle cost: the design must remove all group compute capacity during predictable idle periods. The mismatch makes it less suitable.
4. Scheduled Auto Scaling to zero sets nonproduction group capacity to zero during known idle periods. A scheduled zero-capacity window eliminates predictable idle instances while retaining the Auto Scaling configuration for automatic recreation later. It meets the need to remove all group compute capacity during predictable idle periods and improves test environment idle cost.

 

Question 8

An API requires two instances even at the quietest hour, but the Auto Scaling group minimum is eight because of an old launch estimate. An architect needs to lower the always-on baseline while retaining elastic scale-out for peaks. What should be selected? Choose ONE.

1. Right-size EC2 instance size
2. Minimum viable Auto Scaling capacity
3. Delete obsolete Auto Scaling capacity
4. Scheduled Auto Scaling to zero

Correct Answer(s)

 

B

Rationale

1. Right-size EC2 instance size changes an EC2 instance shape so provisioned CPU, memory, and network capacity better match measured demand. It is appropriate when utilization data shows the current instance has persistent excess or resource pressure. This scenario prioritizes baseline idle capacity: the design must lower the always-on baseline while retaining elastic scale-out for peaks. The mismatch makes it less suitable.
2. Minimum viable Auto Scaling capacity keeps only the smallest always-needed baseline while elasticity handles demand. The group can still scale when demand rises, so lowering an unnecessarily high minimum removes idle baseline instances without weakening peak elasticity. It meets the need to lower the always-on baseline while retaining elastic scale-out for peaks and improves baseline idle capacity.
3. Delete obsolete Auto Scaling capacity removes unused desired capacity after a workload has been retired or migrated. It is appropriate when metrics and ownership confirm instances no longer serve production demand. This scenario prioritizes baseline idle capacity: the design must lower the always-on baseline while retaining elastic scale-out for peaks. The mismatch makes it less suitable.
4. Scheduled Auto Scaling to zero sets nonproduction group capacity to zero during known idle periods. It is appropriate when a stateless environment is unnecessary outside a predictable schedule. This scenario prioritizes baseline idle capacity: the design must lower the always-on baseline while retaining elastic scale-out for peaks. The mismatch makes it less suitable.

 

Question 9

Four small internal services each run on separate EC2 hosts that average under 10 percent CPU and 20 percent memory. Their security and operating requirements are compatible. Which change most directly allows the workload to reduce host count by increasing safe utilization of each remaining host? Choose ONE.

1. Consolidate workloads onto fewer right-sized hosts
2. Right-size EC2 instance size
3. Spot Instances
4. Compute Savings Plans

Correct Answer(s)

 

A

Rationale

1. Consolidate workloads onto fewer right-sized hosts raises utilization by reducing the number of persistently underused EC2 hosts. Consolidation removes duplicated idle headroom across separate hosts, reducing total instance count while preserving measured resource capacity for the services. It meets the need to reduce host count by increasing safe utilization of each remaining host and improves fleet utilization.
2. Right-size EC2 instance size aligns an EC2 instance type or size with observed workload requirements instead of historical guesses. It is appropriate when monitoring demonstrates that the current shape is consistently over- or under-provisioned. This scenario prioritizes fleet utilization: the design must reduce host count by increasing safe utilization of each remaining host. The mismatch makes it less suitable.
3. Spot Instances lower EC2 compute price by accepting reclaimable spare-capacity instances. It is appropriate when the application is designed to survive instance interruption without losing critical state. This scenario prioritizes fleet utilization: the design must reduce host count by increasing safe utilization of each remaining host. The mismatch makes it less suitable.
4. Compute Savings Plans apply a committed-rate discount across qualifying EC2 usage and eligible serverless or container compute. It is appropriate when the organization wants one commitment to follow changing compute choices. This scenario prioritizes fleet utilization: the design must reduce host count by increasing safe utilization of each remaining host. The mismatch makes it less suitable.

 

Question 10

A product was migrated to SaaS, but its old Auto Scaling group still maintains six instances with nearly zero traffic and no remaining consumers. Which cost-optimization decision best meets the requirement to remove retired compute capacity after ownership confirms it is unused? Choose ONE.

1. Minimum viable Auto Scaling capacity
2. Right-size EC2 instance size
3. Delete obsolete Auto Scaling capacity
4. Scheduled Auto Scaling to zero

Correct Answer(s)

 

C

Rationale

1. Minimum viable Auto Scaling capacity keeps only the smallest always-needed baseline while elasticity handles demand. It is appropriate when steady minimum traffic is low and excess idle baseline instances create waste. This scenario prioritizes retired workload spend: the design must remove retired compute capacity after ownership confirms it is unused. The mismatch makes it less suitable.
2. Right-size EC2 instance size adjusts provisioned EC2 resources to the capacity the workload actually consumes. It is appropriate when reliable metrics show a sustained mismatch between allocated and needed resources. This scenario prioritizes retired workload spend: the design must remove retired compute capacity after ownership confirms it is unused. The mismatch makes it less suitable.
3. Delete obsolete Auto Scaling capacity removes unused desired capacity after a workload has been retired or migrated. The workload no longer provides a service, so any retained desired capacity is pure waste; rightsizing would merely make unnecessary infrastructure cheaper. It meets the need to remove retired compute capacity after ownership confirms it is unused and improves retired workload spend.
4. Scheduled Auto Scaling to zero sets nonproduction group capacity to zero during known idle periods. It is appropriate when a stateless environment is unnecessary outside a predictable schedule. This scenario prioritizes retired workload spend: the design must remove retired compute capacity after ownership confirms it is unused. The mismatch makes it less suitable.

 

Question 11

A build farm is interruption tolerant and can run on several equivalent EC2 families. Spot launches sometimes fail because the group lists only one instance type. The architecture must increase access to discounted Spot capacity pools without changing job semantics. Which option is most cost-effective? Choose ONE.

1. Price-capacity-optimized Spot allocation
2. Spot Instances
3. Attribute-based instance type selection
4. Flexible EC2 instance types in a Spot group

Correct Answer(s)

 

D

Rationale

1. Price-capacity-optimized Spot allocation balances Spot price with pool capacity to reduce interruption exposure. It is appropriate when a flexible Spot fleet needs both savings and practical availability. This scenario prioritizes Spot capacity reach: the design must increase access to discounted Spot capacity pools without changing job semantics. The mismatch makes it less suitable.
2. Spot Instances use discounted spare EC2 capacity that AWS may reclaim with interruption notice. It is appropriate when workers are fault tolerant and can retry, checkpoint, or redistribute unfinished work. This scenario prioritizes Spot capacity reach: the design must increase access to discounted Spot capacity pools without changing job semantics. The mismatch makes it less suitable.
3. Attribute-based instance type selection lets Auto Scaling select EC2 instance types that meet declared resource attributes instead of a fixed type list. It is appropriate when a flexible fleet should use many equivalent instance types without manually maintaining every compatible type. This scenario prioritizes Spot capacity reach: the design must increase access to discounted Spot capacity pools without changing job semantics. The mismatch makes it less suitable.
4. Flexible EC2 instance types in a Spot group expands eligible Spot capacity pools by allowing several equivalent instance types. More eligible types expand the set of Spot pools the fleet can use, improving the chance of finding discounted capacity for flexible workers. It meets the need to increase access to discounted Spot capacity pools without changing job semantics and improves Spot capacity reach.

 

Question 12

A support platform runs short event-driven transformations a few dozen times per hour. An always-on EC2 instance is idle more than 95 percent of the day. An architect needs to align compute charges with actual invocation time rather than server uptime. What should be selected? Choose ONE.

1. On-Demand Instances
2. AWS Lambda pay-per-use compute
3. ECS on AWS Fargate
4. Scheduled stop and start for nonproduction EC2

Correct Answer(s)

 

B

Rationale

1. On-Demand Instances provide noninterruptible EC2 usage with no one- or three-year spend obligation. It is appropriate when future demand is unclear and purchase flexibility is more valuable than commitment discounts. This scenario prioritizes paid idle time: the design must align compute charges with actual invocation time rather than server uptime. The mismatch makes it less suitable.
2. AWS Lambda pay-per-use compute runs event-driven code without paying for idle server capacity between invocations. Lambda removes continuous server billing between sparse events, making it a better cost model for brief invocations than a mostly idle EC2 host. It meets the need to align compute charges with actual invocation time rather than server uptime and improves paid idle time.
3. ECS on AWS Fargate charges container tasks for requested compute while removing EC2 host management. It is appropriate when container demand varies and avoiding continuously provisioned hosts is valuable. This scenario prioritizes paid idle time: the design must align compute charges with actual invocation time rather than server uptime. The mismatch makes it less suitable.
4. Scheduled stop and start for nonproduction EC2 removes EC2 compute charges while stopped outside known working hours. It is appropriate when EBS-backed development servers are idle on a predictable schedule and may be offline. This scenario prioritizes paid idle time: the design must align compute charges with actual invocation time rather than server uptime. The mismatch makes it less suitable.

 

Question 13

A containerized nightly report runs for 25 minutes, then no containers run for the rest of the day. The team does not need host customization. Which change most directly allows the workload to avoid keeping an EC2 container host alive between short task runs? Choose ONE.

1. ECS on EC2 with committed pricing
2. Fargate Spot
3. ECS on AWS Fargate
4. AWS Lambda pay-per-use compute

Correct Answer(s)

 

C

Rationale

1. ECS on EC2 with committed pricing runs containers on customer-sized EC2 capacity that can receive EC2 commitment discounts. It is appropriate when container demand is consistently high enough to keep hosts well utilized. This scenario prioritizes container idle infrastructure: the design must avoid keeping an EC2 container host alive between short task runs. The mismatch makes it less suitable.
2. Fargate Spot runs interruption-tolerant ECS tasks on discounted spare Fargate capacity. It is appropriate when container tasks can tolerate a two-minute interruption notice and restart elsewhere. This scenario prioritizes container idle infrastructure: the design must avoid keeping an EC2 container host alive between short task runs. The mismatch makes it less suitable.
3. ECS on AWS Fargate charges container tasks for requested compute while removing EC2 host management. Fargate provisions task compute only while the container runs, avoiding the idle-host cost of a dedicated EC2 container fleet between reports. It meets the need to avoid keeping an EC2 container host alive between short task runs and improves container idle infrastructure.
4. AWS Lambda pay-per-use compute runs event-driven code without paying for idle server capacity between invocations. It is appropriate when work arrives intermittently and fits Lambda execution constraints. This scenario prioritizes container idle infrastructure: the design must avoid keeping an EC2 container host alive between short task runs. The mismatch makes it less suitable.

 

Question 14

A latency-sensitive container platform runs a constant large workload with predictable CPU and memory needs. Hosts remain above 85 percent utilized and the team already manages EC2. Which cost-optimization decision best meets the requirement to use committed highly utilized hosts instead of paying a serverless convenience premium? Choose ONE.

1. ECS on AWS Fargate
2. Fargate Spot
3. On-Demand Instances
4. ECS on EC2 with committed pricing

Correct Answer(s)

 

D

Rationale

1. ECS on AWS Fargate charges container tasks for requested compute while removing EC2 host management. It is appropriate when container demand varies and avoiding continuously provisioned hosts is valuable. This scenario prioritizes steady-state container cost: the design must use committed highly utilized hosts instead of paying a serverless convenience premium. The mismatch makes it less suitable.
2. Fargate Spot runs interruption-tolerant ECS tasks on discounted spare Fargate capacity. It is appropriate when container tasks can tolerate a two-minute interruption notice and restart elsewhere. This scenario prioritizes steady-state container cost: the design must use committed highly utilized hosts instead of paying a serverless convenience premium. The mismatch makes it less suitable.
3. On-Demand Instances bill EC2 capacity as it is consumed without requiring a multi-year pricing commitment. It is appropriate when the workload is temporary, uncertain, or cannot accept Spot interruption. This scenario prioritizes steady-state container cost: the design must use committed highly utilized hosts instead of paying a serverless convenience premium. The mismatch makes it less suitable.
4. ECS on EC2 with committed pricing runs containers on customer-sized EC2 capacity that can receive EC2 commitment discounts. High sustained utilization lets the platform amortize EC2 host cost efficiently, and commitment pricing can further reduce the durable baseline rate. It meets the need to use committed highly utilized hosts instead of paying a serverless convenience premium and improves steady-state container cost.

 

Question 15

An x86 compute service has mature CI tests and its dependencies are available for Arm. Benchmarking shows Graviton completes the same workload in the required time at lower cost. The architecture must reduce price per completed unit of EC2 work. Which option is most cost-effective? Choose ONE.

1. Right-size EC2 instance size
2. Graviton-based EC2 instances
3. Spot Instances
4. Compute Savings Plans

Correct Answer(s)

 

B

Rationale

1. Right-size EC2 instance size aligns an EC2 instance type or size with observed workload requirements instead of historical guesses. It is appropriate when monitoring demonstrates that the current shape is consistently over- or under-provisioned. This scenario prioritizes cost per completed job: the design must reduce price per completed unit of EC2 work. The mismatch makes it less suitable.
2. Graviton-based EC2 instances use Arm-based AWS processors with strong price performance for compatible workloads. The benchmark proves compatibility and acceptable performance, so moving to Graviton targets price performance rather than relying only on billing discounts. It meets the need to reduce price per completed unit of EC2 work and improves cost per completed job.
3. Spot Instances lower EC2 compute price by accepting reclaimable spare-capacity instances. It is appropriate when the application is designed to survive instance interruption without losing critical state. This scenario prioritizes cost per completed job: the design must reduce price per completed unit of EC2 work. The mismatch makes it less suitable.
4. Compute Savings Plans apply a committed-rate discount across qualifying EC2 usage and eligible serverless or container compute. It is appropriate when the organization wants one commitment to follow changing compute choices. This scenario prioritizes cost per completed job: the design must reduce price per completed unit of EC2 work. The mismatch makes it less suitable.

 

Question 16

Finance wants to attribute shared AWS compute charges to application owners in Cost Explorer and the Cost and Usage Report. An architect needs to make application ownership a reportable cost dimension. What should be selected? Choose ONE.

1. Cost allocation tags
2. AWS Budgets
3. AWS Cost and Usage Report
4. Cost Explorer Savings Plans recommendations

Correct Answer(s)

 

A

Rationale

1. Cost allocation tags label resources so activated tag values can be grouped in cost reporting. Activated cost allocation tags let billing tools group resource charges by the organization-defined ownership key, enabling chargeback or showback. It meets the need to make application ownership a reportable cost dimension and improves cost attribution quality.
2. AWS Budgets tracks cost or usage against thresholds and can notify or invoke budget actions. It is appropriate when owners need proactive warning when spending approaches an agreed limit. This scenario prioritizes cost attribution quality: the design must make application ownership a reportable cost dimension. The mismatch makes it less suitable.
3. AWS Cost and Usage Report exports detailed billing and usage line items for granular cost analysis. It is appropriate when teams need raw resource-level charge data for custom analysis or allocation. This scenario prioritizes cost attribution quality: the design must make application ownership a reportable cost dimension. The mismatch makes it less suitable.
4. Cost Explorer Savings Plans recommendations estimates commitment levels from eligible historical compute usage and preferences. It is appropriate when an organization wants data-driven Savings Plans purchase guidance. This scenario prioritizes cost attribution quality: the design must make application ownership a reportable cost dimension. The mismatch makes it less suitable.

 

Question 17

A FinOps team needs raw line-item data with resource identifiers and detailed usage fields for custom SQL analysis in its data warehouse. Which change most directly allows the workload to export the most granular AWS billing and usage dataset for custom analysis? Choose ONE.

1. Cost allocation tags
2. AWS Budgets
3. Cost Explorer Savings Plans recommendations
4. AWS Cost and Usage Report

Correct Answer(s)

 

D

Rationale

1. Cost allocation tags label resources so activated tag values can be grouped in cost reporting. It is appropriate when shared billing must be attributed to teams applications or environments. This scenario prioritizes billing data granularity: the design must export the most granular AWS billing and usage dataset for custom analysis. The mismatch makes it less suitable.
2. AWS Budgets tracks cost or usage against thresholds and can notify or invoke budget actions. It is appropriate when owners need proactive warning when spending approaches an agreed limit. This scenario prioritizes billing data granularity: the design must export the most granular AWS billing and usage dataset for custom analysis. The mismatch makes it less suitable.
3. Cost Explorer Savings Plans recommendations estimates commitment levels from eligible historical compute usage and preferences. It is appropriate when an organization wants data-driven Savings Plans purchase guidance. This scenario prioritizes billing data granularity: the design must export the most granular AWS billing and usage dataset for custom analysis. The mismatch makes it less suitable.
4. AWS Cost and Usage Report exports detailed billing and usage line items for granular cost analysis. The Cost and Usage Report exposes detailed billing records suitable for custom analysis, whereas dashboards and alerts do not provide the same raw line-item dataset. It meets the need to export the most granular AWS billing and usage dataset for custom analysis and improves billing data granularity.

 

Question 18

A project owner must receive a warning before monthly AWS spend crosses an agreed threshold. No architecture change should occur automatically. Which cost-optimization decision best meets the requirement to monitor spending against a defined threshold and notify stakeholders? Choose ONE.

1. AWS Budgets
2. Cost allocation tags
3. AWS Cost and Usage Report
4. Cost Explorer Savings Plans recommendations

Correct Answer(s)

 

A

Rationale

1. AWS Budgets tracks cost or usage against thresholds and can notify or invoke budget actions. Budgets continuously compares tracked cost or usage with configured limits and can notify owners before the project exceeds its financial guardrail. It meets the need to monitor spending against a defined threshold and notify stakeholders and improves spend threshold visibility.
2. Cost allocation tags label resources so activated tag values can be grouped in cost reporting. It is appropriate when shared billing must be attributed to teams applications or environments. This scenario prioritizes spend threshold visibility: the design must monitor spending against a defined threshold and notify stakeholders. The mismatch makes it less suitable.
3. AWS Cost and Usage Report exports detailed billing and usage line items for granular cost analysis. It is appropriate when teams need raw resource-level charge data for custom analysis or allocation. This scenario prioritizes spend threshold visibility: the design must monitor spending against a defined threshold and notify stakeholders. The mismatch makes it less suitable.
4. Cost Explorer Savings Plans recommendations estimates commitment levels from eligible historical compute usage and preferences. It is appropriate when an organization wants data-driven Savings Plans purchase guidance. This scenario prioritizes spend threshold visibility: the design must monitor spending against a defined threshold and notify stakeholders. The mismatch makes it less suitable.

 

Question 19

A company has a stable compute floor but is unsure whether a one-year or three-year commitment and different payment options are sensible. The architecture must compare Savings Plans recommendations under selected term and payment assumptions. Which option is most cost-effective? Choose ONE.

1. Compute Savings Plans
2. AWS Budgets
3. Cost Explorer Savings Plans recommendations
4. AWS Cost and Usage Report

Correct Answer(s)

 

C

Rationale

1. Compute Savings Plans trade an hourly usage commitment for broad compute discounts spanning EC2, Fargate, and Lambda. It is appropriate when long-lived compute has a stable floor but workload placement can change. This scenario prioritizes commitment planning: the design must compare Savings Plans recommendations under selected term and payment assumptions. The mismatch makes it less suitable.
2. AWS Budgets tracks cost or usage against thresholds and can notify or invoke budget actions. It is appropriate when owners need proactive warning when spending approaches an agreed limit. This scenario prioritizes commitment planning: the design must compare Savings Plans recommendations under selected term and payment assumptions. The mismatch makes it less suitable.
3. Cost Explorer Savings Plans recommendations estimates commitment levels from eligible historical compute usage and preferences. The recommendation workflow models historical eligible usage under purchase preferences, making it the appropriate planning tool before selecting a commitment amount. It meets the need to compare Savings Plans recommendations under selected term and payment assumptions and improves commitment planning.
4. AWS Cost and Usage Report exports detailed billing and usage line items for granular cost analysis. It is appropriate when teams need raw resource-level charge data for custom analysis or allocation. This scenario prioritizes commitment planning: the design must compare Savings Plans recommendations under selected term and payment assumptions. The mismatch makes it less suitable.

 

Question 20

A shared services account owns a lightly utilized Compute Savings Plan while application accounts incur eligible On-Demand compute charges under the same payer. An architect needs to increase use of an existing commitment across linked account workloads. What should be selected? Choose ONE.

1. Cost allocation tags
2. Savings Plans sharing in consolidated billing
3. Compute Savings Plans
4. AWS Cost and Usage Report

Correct Answer(s)

 

B

Rationale

1. Cost allocation tags label resources so activated tag values can be grouped in cost reporting. It is appropriate when shared billing must be attributed to teams applications or environments. This scenario prioritizes shared discount utilization: the design must increase use of an existing commitment across linked account workloads. The mismatch makes it less suitable.
2. Savings Plans sharing in consolidated billing allows eligible organization accounts to benefit from unused Savings Plans coverage. Consolidated-billing sharing can apply unused Savings Plan coverage to qualifying usage in other linked accounts, improving utilization of a commitment already purchased. It meets the need to increase use of an existing commitment across linked account workloads and improves shared discount utilization.
3. Compute Savings Plans reduce eligible EC2, Fargate, and Lambda charges through a flexible hourly spend commitment. It is appropriate when baseline compute spend is predictable while the exact service, family, or Region can vary. This scenario prioritizes shared discount utilization: the design must increase use of an existing commitment across linked account workloads. The mismatch makes it less suitable.
4. AWS Cost and Usage Report exports detailed billing and usage line items for granular cost analysis. It is appropriate when teams need raw resource-level charge data for custom analysis or allocation. This scenario prioritizes shared discount utilization: the design must increase use of an existing commitment across linked account workloads. The mismatch makes it less suitable.

• < Amazon AWS SAA-C03 Cost-Optimized Compute, Purchasing Models, Rightsizing, and Elasticity Practice Test 1
• Amazon AWS SAA-C03 Cost-Optimized Compute, Purchasing Models, Rightsizing, and Elasticity Practice Test 3 >