CCNA Design Cost-Optimized Architectures Questions

Multi-Selectmedium

A startup runs a 24/7 web tier on Amazon EC2 with a stable baseline of 8 instances and a nightly analytics batch job that can resume from checkpoints if interrupted. The company wants to minimize monthly compute cost without hurting the always-on web tier. Which two actions should it take? Select two.

Select 2 answers

A.Buy a Compute Savings Plan for the steady web tier baseline.

B.Buy Standard Reserved Instances only for the nightly analytics batch job.

C.Run the batch job on Spot Instances and checkpoint progress frequently.

D.Move the entire workload to On-Demand Instances for maximum flexibility.

E.Use Dedicated Hosts for the batch job so the fleet is isolated.

AnswersA, C

A Compute Savings Plan reduces cost for the predictable baseline while preserving flexibility across instance families and Regions. That fits a 24/7 web tier that is expected to run continuously. It is cheaper than On-Demand for the committed portion and avoids overcommitting to a specific instance family.

Why this answer

A Compute Savings Plan offers the largest discount (up to 66%) in exchange for a 1- or 3-year hourly spend commitment, and it automatically applies to any EC2 instance family, size, or region. For the stable 8-instance web tier that runs 24/7, this plan provides significant cost savings while maintaining full flexibility to change instance types or even move to containers or Lambda, without affecting the always-on requirement.

Exam trap

The trap here is that candidates often assume Reserved Instances are always the best choice for any steady workload, but for a part-time batch job, a Savings Plan or Spot is more cost-effective, and they may overlook that Spot Instances with checkpointing are ideal for fault-tolerant, interruptible workloads.

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Multi-Selectmedium

A solutions architect is designing a cost-optimized data storage solution for a large dataset that is accessed infrequently but must be retained for compliance for 7 years. Which three actions should the architect take to minimize costs? (Choose three.)

Select 3 answers

.Store the data in Amazon S3 Glacier Deep Archive immediately after creation.

.Use Amazon S3 lifecycle policies to transition data from S3 Standard to S3 Glacier Deep Archive after 30 days.

.Enable S3 Intelligent-Tiering to automatically move data between access tiers based on usage patterns.

.Store all data in Amazon EBS gp2 volumes attached to an EC2 instance for low-latency access.

.Use S3 Object Lock in compliance mode to prevent data deletion during the retention period.

.Replicate all data to a second AWS Region using S3 Cross-Region Replication to ensure durability.

Why this answer

Amazon S3 lifecycle policies allow you to define rules that automatically transition objects to colder storage tiers like S3 Glacier Deep Archive after a specified period. This approach minimizes costs by keeping data in S3 Standard only for the initial 30 days when it might be accessed, then moving it to the lowest-cost storage class for the remaining compliance period. S3 Intelligent-Tiering automatically optimizes costs by monitoring access patterns and moving data between frequent, infrequent, and archive access tiers without manual intervention.

S3 Object Lock in compliance mode prevents any user, including the root user, from deleting or overwriting objects during the retention period, ensuring regulatory compliance.

Exam trap

The trap here is that candidates may think immediate archiving to Glacier Deep Archive is the cheapest option, but they overlook the need for lifecycle policies to balance initial access needs with long-term cost savings, and they may confuse durability (which S3 already provides) with compliance retention, leading them to select unnecessary replication.

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MCQmedium

An S3 bucket stores user-uploaded images. Access patterns are unpredictable: some objects are never read again, while others are occasionally retrieved months later. The team wants to reduce storage cost without having to manually track access frequency or run periodic analyses. Which S3 storage and lifecycle approach is the best fit?

A.Enable S3 Intelligent-Tiering so objects can automatically move between access tiers based on observed access patterns.

B.Use S3 Glacier Instant Retrieval for all objects immediately to minimize storage cost.

C.Create a lifecycle rule that transitions objects to Standard-IA after a fixed 30 days, regardless of access.

D.Keep all objects in S3 Standard and reduce costs by enabling server access logging compression.

AnswerA

S3 Intelligent-Tiering is designed for unknown or changing access patterns. It monitors access and automatically moves objects between tiers (for example, between frequent-access and infrequent-access tiers) based on actual usage, which avoids the need to manually decide transition schedules. This directly meets the requirement to reduce storage cost while eliminating ongoing manual tracking or periodic analysis.

Why this answer

S3 Intelligent-Tiering is the best fit because it automatically moves objects between access tiers (frequent, infrequent, archive instant, archive) based on changing access patterns, eliminating the need for manual tracking or lifecycle rules. This optimizes storage costs for unpredictable access patterns without requiring you to define fixed time-based transitions or perform periodic analyses.

Exam trap

The trap here is that candidates often choose a fixed lifecycle rule (Option C) thinking it is simpler, but they overlook the retrieval fees and inefficiency of applying a rigid time-based policy to unpredictable access patterns, whereas Intelligent-Tiering adapts dynamically without manual tuning.

How to eliminate wrong answers

Option B is wrong because storing all objects immediately in S3 Glacier Instant Retrieval incurs higher retrieval costs and minimum storage charges (90 days) for objects that may never be accessed again, and it does not adapt to unpredictable patterns. Option C is wrong because a fixed 30-day transition to Standard-IA does not account for objects that are accessed frequently after 30 days, leading to retrieval fees, and it fails to optimize for objects that are never accessed again. Option D is wrong because enabling server access logging compression does not reduce storage costs for the objects themselves; it only reduces log storage size, and keeping all objects in S3 Standard is more expensive than using Intelligent-Tiering for unpredictable access.

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MCQmedium

A batch analytics job has unpredictable DynamoDB traffic with long idle periods and occasional spikes. Which capacity mode should minimize operational overhead and avoid paying for idle provisioned capacity?

A.DynamoDB on-demand capacity mode

B.Reserved capacity for maximum daily traffic

C.Provisioned capacity set for peak traffic

D.Global tables in every Region

AnswerA

On-demand capacity is suitable for unpredictable workloads and charges per request without capacity planning.

Why this answer

DynamoDB on-demand capacity mode automatically scales to handle unpredictable traffic spikes and idle periods, charging only for the reads and writes you perform. This eliminates the need to provision capacity for peak traffic, avoiding costs during long idle periods and reducing operational overhead from capacity management.

Exam trap

The trap here is that candidates may confuse 'Reserved capacity' with DynamoDB's reserved capacity option (which does not exist) or think provisioned capacity is always cheaper, ignoring the cost of idle provisioned throughput during unpredictable workloads.

How to eliminate wrong answers

Option B is wrong because Reserved capacity is not a DynamoDB pricing model; it applies to Amazon EC2 and RDS, not DynamoDB, and would still require provisioning for peak traffic. Option C is wrong because Provisioned capacity set for peak traffic would incur costs for idle periods when traffic is low, as you pay for the provisioned capacity regardless of actual usage. Option D is wrong because Global tables are a replication feature for multi-Region active-active setups, not a capacity mode; they do not address cost optimization for unpredictable traffic and add complexity and cost.

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MCQmedium

A SaaS company uses an S3 bucket for database backups created daily. Backups are rarely restored; the company’s documented RTO is 24 hours, and the compliance policy requires backups be kept for 90 days. The team currently stores all backups in S3 Standard, which is costly. Which single lifecycle policy change is most cost-optimized while still meeting the 24-hour RTO and 90-day retention?

A.Add a lifecycle rule to transition backups older than 1 day to S3 Glacier Flexible Retrieval, and keep them until day 90.

B.Add a lifecycle rule to transition backups older than 1 day to S3 Glacier Instant Retrieval, and keep them until day 90.

C.Add a lifecycle rule to transition backups older than 1 day to S3 Glacier Deep Archive, and keep them until day 90 with no restore configuration.

D.Add a lifecycle rule to transition backups older than 1 day to S3 One Zone-IA, and delete them after 7 days.

AnswerA

Glacier Flexible Retrieval is intended for backups with infrequent access and supports restores within an RTO measured in hours.

Why this answer

S3 Glacier Flexible Retrieval offers retrieval times ranging from minutes to hours, which comfortably meets the 24-hour RTO, while providing significant cost savings over S3 Standard for data that is rarely accessed. Transitioning backups older than 1 day to this storage class reduces costs without compromising the 90-day retention requirement.

Exam trap

The trap here is that candidates may choose S3 Glacier Deep Archive for maximum cost savings without considering that its standard retrieval time (12 hours) could fail to meet the 24-hour RTO under load or without expedited retrieval, which adds cost and complexity.

Why the other options are wrong

Glacier Instant Retrieval has a higher storage cost than Glacier Flexible Retrieval and does not provide significant cost savings for backups that are rarely restored, making it less cost-optimized for this scenario.

Glacier Deep Archive has a retrieval time of 12-48 hours, which exceeds the 24-hour RTO, making it unsuitable for this requirement.

S3 One Zone-IA does not meet the 90-day retention requirement because the rule deletes objects after 7 days. Additionally, One Zone-IA is not resilient to AZ failures, which could risk backup availability within the 24-hour RTO.

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MCQeasy

CloudWatch metrics show your EC2 instances have average CPU utilization around 10% with stable performance over several weeks. The application does not require additional headroom right now. What is the most effective cost-optimization action?

A.Right-size the instances to a smaller size that matches the observed utilization

B.Increase the Auto Scaling desired capacity to add more instances

C.Switch to Spot Instances immediately even though interruptions would impact users

D.Disable detailed monitoring to reduce CPU usage from the monitoring agent

AnswerA

Right sizing reduces cost by matching instance capacity to actual demand. If average CPU is consistently low (around 10%) and performance is stable, it strongly indicates overprovisioning. Moving to a smaller instance (or a smaller capability within the same family) typically lowers hourly cost while maintaining sufficient capacity for the workload.

Why this answer

Right-sizing EC2 instances to match observed utilization is the most effective cost-optimization action because the current instances are over-provisioned (average CPU at 10%). By selecting a smaller instance type that aligns with the actual workload, you reduce hourly costs without impacting performance, as the application has stable behavior and no need for headroom.

Exam trap

The trap here is that candidates may think increasing capacity (Option B) or switching to Spot Instances (Option C) is always cost-effective, but they fail to recognize that right-sizing is the foundational first step before scaling or using Spot, especially when current utilization is low and stable.

Why the other options are wrong

Increasing Auto Scaling desired capacity adds more instances, which increases cost without addressing the existing over-provisioning. The question states CPU utilization is low and stable, so adding instances would waste resources.

Switching to Spot Instances immediately would risk interruptions that impact users, which is unacceptable for a production application requiring stable performance. The question states the application does not require additional headroom, but it does not indicate tolerance for interruptions.

Disabling detailed monitoring does not reduce CPU usage from the monitoring agent; it only reduces the frequency of metric data sent to CloudWatch, which has negligible impact on CPU. The question focuses on cost optimization, and detailed monitoring costs extra, but the primary issue is that the instances are over-provisioned, not that monitoring costs are significant.

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Multi-Selectmedium

A marketing site serves versioned JavaScript and CSS files from Amazon S3 through CloudFront. The origin bill is rising because CloudFront keeps fetching the same files too often, and the application never changes a file at the same URL once it is published. Which two changes should you make? Select two.

Select 2 answers

A.Set long-lived Cache-Control headers, such as a high max-age and immutable policy, on the versioned assets.

B.Configure the CloudFront cache policy to avoid forwarding unnecessary query strings, headers, and cookies.

C.Move the static assets to an EC2 web server behind an Application Load Balancer.

D.Disable CloudFront caching so every request always reaches the origin.

E.Add more viewer-facing headers to the cache key so each browser variation gets a unique cached object.

AnswersA, B

Versioned assets are ideal for long cache lifetimes because their URLs change when the content changes. Strong Cache-Control headers let CloudFront serve more requests from edge locations instead of repeatedly fetching the same files from S3.

Why this answer

Setting long-lived Cache-Control headers (e.g., `max-age=31536000` and `immutable`) on versioned assets tells CloudFront and browsers to cache the files aggressively. Since the application never changes a file at the same URL, this eliminates redundant origin fetches, directly reducing the origin bill.

Exam trap

The trap here is that candidates may think disabling caching (Option D) or adding more cache key variations (Option E) will improve performance, but both increase origin load and costs, while the correct approach is to leverage versioned URLs with aggressive caching headers.

Why the other options are wrong

Moving assets to EC2 behind an ALB increases cost and complexity without addressing the root cause of excessive origin fetches; CloudFront already caches from S3, and the issue is cache hit ratio, not origin type.

Disabling CloudFront caching would force every request to go to the S3 origin, increasing origin load and costs, which is the opposite of the goal to reduce origin fetches.

Adding more viewer-facing headers to the cache key increases cache fragmentation, reducing cache hit ratio and causing more origin fetches, which is the opposite of the desired outcome.

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MCQhard

A risk simulation workload generates analytics files that are accessed unpredictably. Some files become hot again months later. The team wants automatic storage cost optimisation without retrieval delays. What should be used? The design must avoid adding custom operational scripts.

A.Manual monthly review and object copying

B.S3 Glacier Flexible Retrieval for all files

C.S3 Intelligent-Tiering

D.EFS One Zone for analytics files

AnswerC

Intelligent-Tiering automatically moves objects between access tiers based on usage while preserving low-latency access.

Why this answer

S3 Intelligent-Tiering automatically moves objects between access tiers (frequent, infrequent, and archive instant access) based on changing access patterns, with no retrieval delays for hot objects and no operational overhead. This matches the unpredictable access pattern where files become hot again months later, as Intelligent-Tiering monitors access at the object level and adjusts storage class without manual intervention or custom scripts.

Exam trap

The trap here is that candidates may choose S3 Glacier Flexible Retrieval because it is cheaper for cold data, but they overlook the 'no retrieval delays' requirement, as Glacier Flexible Retrieval has a retrieval time of minutes to hours, making it unsuitable for files that become hot again unpredictably.

How to eliminate wrong answers

Option A is wrong because manual monthly review and object copying introduces operational overhead and potential retrieval delays, violating the requirement to avoid custom operational scripts and automatic cost optimisation. Option B is wrong because S3 Glacier Flexible Retrieval has retrieval delays (minutes to hours) for files that become hot again, which violates the 'no retrieval delays' requirement. Option D is wrong because EFS One Zone is a file system, not an object storage service, and does not provide automatic storage class tiering based on access patterns; it also incurs costs for all data regardless of access frequency.

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MCQmedium

A development team expects their EC2 utilization to average about 40% of capacity across the next year. They want to lower costs but need flexibility to change instance families and sizes as requirements evolve (for example, moving from compute-optimized to memory-optimized instances). Which AWS purchasing commitment best meets the goal of reducing cost while keeping flexibility?

A.Compute Savings Plans, sized to the expected average usage, because they provide savings across instance families and usage types.

B.All Upfront EC2 Instance Reserved Instances for a single instance family to maximize discount.

C.Spot Instances for the entire workload so they can avoid commitments entirely.

D.On-Demand Instances with increased Auto Scaling to match the peak month only.

AnswerA

Compute Savings Plans provide a discount for a consistent amount of EC2 (and related covered usage) in a region while allowing flexibility to change instance families and sizes within the covered scope. Because the team’s requirements may evolve and they primarily need to manage average utilization (40% baseline), Compute Savings Plans match both the cost-reduction goal and the flexibility requirement better than instance-specific commitments.

Why this answer

Compute Savings Plans offer the best balance of cost reduction and flexibility for this scenario. They provide up to 66% savings in exchange for a commitment to a consistent amount of compute usage (measured in $/hour), but unlike Reserved Instances, they automatically apply to any EC2 instance family, size, OS, or region (within a given AWS region). This allows the team to switch from compute-optimized to memory-optimized instances as needs evolve without losing the discount, directly meeting the requirement for flexibility while lowering costs.

Exam trap

The trap here is that candidates often confuse Reserved Instances (which lock to a specific instance family) with Savings Plans (which offer cross-family flexibility), leading them to choose Option B for the higher discount without considering the flexibility requirement.

How to eliminate wrong answers

Option B is wrong because All Upfront EC2 Instance Reserved Instances lock the team into a single instance family (e.g., C5) and size, which eliminates the flexibility to change instance families as requirements evolve. Option C is wrong because Spot Instances can be terminated by AWS with only a 2-minute warning if capacity is reclaimed, making them unsuitable for a steady-state workload that expects 40% average utilization across the year; they also do not provide a guaranteed cost commitment. Option D is wrong because On-Demand Instances with increased Auto Scaling to match the peak month only does not reduce costs for the average 40% utilization; it actually increases costs by paying full On-Demand rates for all usage, and Auto Scaling alone does not provide a discount.

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MCQmedium

A log archive serves infrequently accessed user documents that must be available immediately when requested. Which S3 storage class is likely the best cost fit?

A.Instance store volumes

B.S3 Standard-IA or S3 One Zone-IA depending on resilience requirements

C.S3 Standard for all objects

D.S3 Glacier Deep Archive

AnswerB

Infrequent Access classes reduce storage cost while keeping millisecond retrieval.

Why this answer

S3 Standard-IA or S3 One Zone-IA is the best cost fit because the workload involves infrequently accessed data that requires immediate retrieval (millisecond latency). Standard-IA offers lower storage cost than S3 Standard while maintaining high durability and low-latency access, and One Zone-IA provides even lower cost for data that can tolerate a single-AZ failure. Both classes meet the 'available immediately' requirement, unlike Glacier tiers which have retrieval delays.

Exam trap

The trap here is that candidates often confuse 'infrequently accessed' with 'archival' and choose Glacier Deep Archive, forgetting that the requirement for immediate availability eliminates any Glacier tier due to its retrieval delays.

How to eliminate wrong answers

Option A is wrong because instance store volumes are ephemeral block storage attached to EC2 instances, not an S3 storage class, and they lose data on instance stop/termination, making them unsuitable for durable log archives. Option C is wrong because S3 Standard is designed for frequently accessed data with higher storage cost per GB, leading to unnecessary expense for infrequently accessed logs. Option D is wrong because S3 Glacier Deep Archive has retrieval times of 12–48 hours, which violates the 'available immediately' requirement.

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MCQeasy

A company stores user uploads in an S3 bucket. Objects are accessed rarely after upload, but when an object is accessed, it must be retrievable quickly (minutes to a few hours). Objects must be retained for at least 18 months. The team wants to reduce storage cost while meeting these requirements. Which lifecycle configuration best fits these requirements?

A.Keep all objects in S3 Standard permanently to avoid lifecycle transition fees.

B.After 30 days, transition objects to S3 Glacier Instant Retrieval, and after 18 months, expire (delete) the objects.

C.After 30 days, transition objects to S3 Intelligent-Tiering, and set expiration to 12 months.

D.After 30 days, transition objects to S3 Glacier Deep Archive, and set expiration to 18 months.

AnswerB

The prompt requires (1) cost reduction for data that becomes infrequently accessed and (2) quick retrieval when accessed again, and (3) a minimum retention of at least 18 months. Glacier Instant Retrieval is intended for data that is accessed occasionally and needs fast retrieval. Transitioning after 30 days moves the long-term, rarely accessed portion of the data to a cheaper class, while expiring at 18 months satisfies the explicit retention requirement (the objects remain for at least 18 months).

Why this answer

It transitions objects to S3 Glacier Instant Retrieval after 30 days, which provides millisecond retrieval for rarely accessed data, meeting the quick retrieval requirement. The 18-month expiration ensures compliance with the retention policy while minimizing storage costs compared to keeping data in S3 Standard.

Exam trap

The trap here is that candidates may confuse retrieval time requirements: S3 Glacier Deep Archive is cheaper but has retrieval times of hours, not minutes, and S3 Intelligent-Tiering is for unpredictable access, not for data that is rarely accessed after upload.

How to eliminate wrong answers

Option A is wrong because keeping all objects in S3 Standard permanently ignores the cost-saving opportunity of lifecycle transitions; S3 Standard is more expensive for rarely accessed data, and there are no lifecycle transition fees for moving to colder storage classes. Option C is wrong because S3 Intelligent-Tiering is designed for unpredictable access patterns, not for data that is rarely accessed after upload, and setting expiration to 12 months violates the 18-month retention requirement. Option D is wrong because S3 Glacier Deep Archive has retrieval times of 12-48 hours, which does not meet the requirement of retrievable within minutes to a few hours.

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Multi-Selecthard

A photo studio stores original project archives in Amazon S3. Objects are read heavily for 14 days after upload, occasionally during the next 11 months, and almost never after one year. The team wants the lowest storage cost while keeping retrieval within minutes during the first year. Which three actions are best? Select three.

Select 3 answers

A.Keep new objects in S3 Standard for the first 14 days.

B.Transition objects to S3 Standard-IA after 14 days.

C.Transition objects to S3 Glacier Flexible Retrieval after 14 days.

D.Transition objects to S3 Glacier Deep Archive after one year.

E.Disable versioning to make the lifecycle rules work correctly.

AnswersA, B, D

Correct. Standard is appropriate for the initial hot-access period because the data is read frequently and needs immediate performance. Using a cheaper archive tier too early would increase retrieval latency and likely access costs.

Why this answer

A is correct because S3 Standard is designed for frequently accessed data with low latency and high throughput, making it ideal for the first 14 days when objects are read heavily. After this period, transitioning to S3 Standard-IA reduces storage costs while still providing millisecond retrieval for occasional access during the next 11 months.

Exam trap

The trap here is that candidates might choose Glacier Flexible Retrieval for the 14-day transition, overlooking that its retrieval time (minutes to hours) does not meet the 'within minutes' requirement for the first year, whereas Standard-IA provides both cost savings and instant retrieval.

Why the other options are wrong

Versioning does not affect lifecycle rules; lifecycle rules work independently of versioning status. Disabling versioning is unnecessary and does not help achieve the lowest storage cost.

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MCQmedium

A media company runs a nightly batch job that processes video thumbnails. The batch can be interrupted at any time, and workers can resume automatically from checkpoints (a termination does not corrupt progress). The business goal is the lowest possible compute cost, and occasional interruptions are acceptable as long as the job continues automatically. Which approach is most cost-optimized?

A.Run the job on On-Demand EC2 instances to avoid interruptions

B.Use EC2 Spot Instances and implement interruption handling with checkpoint-based restarts

C.Buy Reserved Instances for the entire job window because interruptions are acceptable anyway

D.Use Savings Plans but schedule the job only during business hours to reduce the commit cost

AnswerB

Spot Instances are designed for workloads that can handle interruptions. With checkpoint-based restarts, the application can tolerate Spot termination events and still complete the batch, while capturing Spot’s lower compute pricing.

Why this answer

Spot Instances offer the lowest compute cost (up to 90% discount vs. On-Demand) and the checkpoint-based design ensures that interruptions are handled gracefully without data loss. The job can resume automatically from the last checkpoint, making Spot Instances ideal for fault-tolerant, interruptible batch workloads.

Exam trap

The trap here is that candidates assume Reserved Instances or Savings Plans are always cheaper for predictable workloads, but they overlook that Spot Instances can be even cheaper and are perfectly suited for fault-tolerant, interruptible batch jobs without any upfront commitment.

How to eliminate wrong answers

Option A is wrong because On-Demand instances are significantly more expensive than Spot Instances, and the business explicitly accepts occasional interruptions, so paying a premium for uninterrupted compute is not cost-optimized. Option C is wrong because Reserved Instances require a 1- or 3-year commitment and are designed for steady-state workloads, not for a nightly batch job that can be interrupted; the cost savings are less than Spot and the commitment is unnecessary. Option D is wrong because Savings Plans also require a commitment (1 or 3 years) and scheduling the job only during business hours does not reduce the commit cost; the job runs nightly, so this approach would either waste committed spend or require overprovisioning, making it less cost-effective than Spot.

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MCQmedium

A data engineering team runs a nightly ETL job on EC2. The job can be checkpointed every 5 minutes and can be retried from the last checkpoint if the instance terminates. The job runtime varies from 2 to 4 hours, and the team has no need for a specific instance type, as long as it completes before 7:00 AM local time. They currently run the job on On-Demand EC2, leading to high monthly compute cost. Which change best reduces cost while maintaining the business deadline?

A.Use Spot Instances for the ETL workload, and configure the job to checkpoint frequently and restart on interruption.

B.Use Reserved Instances with a 1-year term to lower costs, since reservations provide discounts for any usage.

C.Switch to On-Demand but enable Auto Scaling so the job finishes faster during peak hours.

D.Use Spot Instances but disable checkpointing to simplify the application.

AnswerA

Spot can significantly reduce costs, and checkpointing plus retries mitigate interruption risk.

Why this answer

Spot Instances offer significant cost savings (up to 90%) compared to On-Demand, and the ETL job's ability to checkpoint every 5 minutes and restart from the last checkpoint makes it resilient to Spot interruptions. This allows the team to meet the 7:00 AM deadline while drastically reducing compute costs, as the job can be retried on new Spot capacity if interrupted.

Exam trap

The trap here is that candidates may overlook the checkpointing requirement and choose Reserved Instances (B) thinking they always reduce costs, or disable checkpointing (D) assuming simplicity is better, without realizing that Spot Instances require fault tolerance to be cost-effective.

Why the other options are wrong

Reserved Instances require a 1-year commitment and are cost-effective only for steady-state, predictable workloads. The nightly ETL job runs only 2-4 hours per day, so the discount does not offset the cost of paying for 24/7 reserved capacity, making it more expensive than Spot Instances.

Auto Scaling does not reduce cost; it adds more instances, increasing cost. The job already runs within the deadline, so scaling out is unnecessary and more expensive.

Disabling checkpointing removes the ability to resume from the last checkpoint on interruption, which is critical for Spot Instances that can be terminated at any time. Without checkpointing, the job would have to restart from scratch, likely missing the 7:00 AM deadline.

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MCQeasy

A company has a steady, predictable workload that must run continuously (24/7) in a single AWS Region. The team wants the lowest cost option available for this steady usage, but also expects they may choose different EC2 instance families in the future (without re-buying compute discounts). Which AWS purchase option best meets these goals?

A.On-Demand Instances only, because they automatically adjust to future needs

B.Compute Savings Plans, committed for a 1- to 3-year term in the Region

C.Standard Reserved Instances tied to a single instance type and Availability Zone

D.EC2 Spot Instances, because they are always cheaper than savings programs

AnswerB

Compute Savings Plans provide discounted pricing in exchange for committing to a consistent hourly spend (scoped to a Region). They apply to EC2 usage and are flexible enough that you can change EC2 instance families over time while still receiving the Savings Plans discount within the commitment scope.

Why this answer

Compute Savings Plans offer the lowest cost for steady, predictable workloads while providing instance family flexibility within a Region. Unlike Reserved Instances, they automatically apply discounts to any EC2 instance family (and even Fargate/Lambda) in the chosen Region, so the company can switch instance families in the future without losing the discount. A 1- or 3-year commitment yields significant savings (up to 66%) compared to On-Demand, making it the optimal choice for this scenario.

Exam trap

The trap here is that candidates often confuse Reserved Instances (which lock instance family and AZ) with Savings Plans (which offer regional flexibility), leading them to choose Standard Reserved Instances despite the stated requirement for future instance family changes.

Why the other options are wrong

On-Demand Instances are the most expensive option for steady, 24/7 workloads, as they lack the discounts of committed-use plans. The question specifically asks for the lowest cost, so On-Demand does not meet that requirement.

Standard Reserved Instances lock you into a specific instance type and Availability Zone, which contradicts the requirement to choose different instance families in the future without re-buying compute discounts.

Spot Instances can be interrupted with a 2-minute notice, making them unsuitable for a steady, continuous 24/7 workload that must run without interruption.

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MCQeasy

A company keeps daily database backups in an S3 bucket. They may restore from backups during the first 30 days if there is an issue. After 30 days, backups are rarely restored, but must be retained for 2 years. Which lifecycle strategy most cost-effectively meets these requirements?

A.Delete backups after 30 days to avoid storage costs, since restores are rare.

B.Keep all backups in S3 Standard for the entire 2-year retention period.

C.Use an S3 lifecycle policy to keep backups in S3 Standard for 30 days, then transition them to S3 Glacier Deep Archive for the remainder of the 2-year retention period.

D.Move backups to S3 Glacier Deep Archive immediately after creation, even for the first 30 days.

AnswerC

A lifecycle transition after the initial restore window reduces cost while still meeting the 2-year retention requirement.

Why this answer

It uses an S3 lifecycle policy to store backups in S3 Standard for the first 30 days when restores are likely, then transitions them to S3 Glacier Deep Archive for the remaining retention period. S3 Glacier Deep Archive offers the lowest storage cost for long-term, rarely accessed data, making this the most cost-effective strategy while meeting the 2-year retention requirement.

Exam trap

The trap here is that candidates may choose Option A, thinking that deleting old backups saves money, but they overlook the explicit retention requirement, or they may choose Option D, assuming immediate archiving is always cheapest, without considering the need for quick access during the first 30 days.

How to eliminate wrong answers

Option A is wrong because deleting backups after 30 days violates the requirement to retain backups for 2 years. Option B is wrong because keeping all backups in S3 Standard for the entire 2 years incurs unnecessary high storage costs for data that is rarely accessed after 30 days. Option D is wrong because moving backups immediately to S3 Glacier Deep Archive would incur retrieval costs and delays (typically 12-48 hours) during the first 30 days when restores may be needed, and does not optimize for the access pattern.

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Multi-Selecthard

A media company runs a 24/7 ingestion API on EC2 behind an Application Load Balancer and a nightly transcoding job that can resume from checkpoints. The API fleet runs at roughly 65 percent CPU all day, while the batch workers sit idle most of the time. The company wants to cut compute cost without risking the API. Which two changes should they make? Select two.

Select 2 answers

A.Purchase a Compute Savings Plan for the always-on API fleet.

B.Move the transcoding workers to EC2 Spot Instances and checkpoint progress.

C.Replace the API fleet with Dedicated Hosts to lock in lower rates.

D.Buy Standard Reserved Instances for the batch workers and keep them running 24/7.

E.Increase the worker Auto Scaling minimum to prevent Spot interruptions.

AnswersA, B

Correct. Compute Savings Plans discount steady usage across EC2 and other compute services without forcing a specific instance family. The API has predictable 24/7 demand, so a commitment fits the usage pattern and lowers cost safely.

Why this answer

A is correct because a Compute Savings Plan offers the largest discount (up to 66%) in exchange for a 1- or 3-year commitment to a consistent amount of compute usage (measured in $/hour), which perfectly matches the always-on API fleet that runs at a steady 65% CPU utilization. This plan applies to any EC2 instance family, region, or compute service (including Fargate and Lambda), giving flexibility while reducing costs for the predictable baseline load.

Exam trap

The trap here is that candidates often confuse Savings Plans with Reserved Instances, or assume Dedicated Hosts are a cost-saving measure, when in fact they are a premium isolation feature; the key is recognizing that Spot Instances are ideal for fault-tolerant, checkpointable batch workloads, while a Compute Savings Plan covers the predictable baseline without locking into a specific instance type.

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MCQeasy

A startup has a stable production web service that runs continuously (24/7) on AWS. They have consistent compute requirements for the next 1 year, but the instance size and family might change as they optimize performance. To reduce cost while maintaining flexibility across instance types, which purchasing option should they consider?

A.Compute Savings Plans

B.Reserved Instances with a fixed instance type

C.Spot Instances

D.On-Demand Instances

AnswerA

Compute Savings Plans discount compute usage while allowing flexibility across instance families, sizes, and even some services.

Why this answer

Compute Savings Plans offer the lowest prices for EC2 compute usage (up to 66% off On-Demand) while allowing flexibility to change instance family, size, OS, and region (within a region). This matches the startup's need for consistent 1-year compute requirements with potential instance type changes during performance optimization.

Exam trap

The trap here is that candidates often choose Reserved Instances with a fixed instance type because they see a 1-year commitment, but they overlook the requirement for flexibility across instance types, which only Compute Savings Plans provide.

How to eliminate wrong answers

Option B is wrong because Reserved Instances with a fixed instance type lock you into a specific instance family and size, which contradicts the requirement for flexibility across instance types. Option C is wrong because Spot Instances are designed for fault-tolerant, interruptible workloads and are not suitable for a stable production web service that must run continuously 24/7. Option D is wrong because On-Demand Instances provide no cost savings (they are the most expensive option) and do not offer a discount for a 1-year commitment.

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MCQmedium

A marketing site has EC2 instances that are oversized based on CPU, memory, and network utilisation. Which AWS service should identify rightsizing recommendations?

A.AWS Shield

B.AWS Compute Optimizer

C.AWS DataSync

D.AWS Artifact

AnswerB

Compute Optimizer analyses utilisation metrics and recommends rightsizing for supported resources.

Why this answer

AWS Compute Optimizer analyzes historical utilization metrics (CPU, memory, network, and storage) from CloudWatch and uses machine learning to identify over-provisioned or under-provisioned EC2 instances. It generates actionable rightsizing recommendations, including instance type changes, to optimize cost and performance. This directly addresses the scenario of oversized EC2 instances.

Exam trap

The trap here is confusing AWS Compute Optimizer with AWS Trusted Advisor, which also provides cost optimization checks but does not offer the same ML-driven, granular rightsizing recommendations for EC2 instances.

How to eliminate wrong answers

Option A is wrong because AWS Shield is a managed DDoS protection service, not a resource optimization or rightsizing tool. Option C is wrong because AWS DataSync is a data transfer service for moving large datasets between on-premises storage and AWS, not for analyzing instance utilization or making rightsizing recommendations. Option D is wrong because AWS Artifact is a self-service portal for downloading compliance reports and agreements (e.g., SOC, PCI), not a cost optimization or rightsizing service.

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MCQhard

Based on the exhibit, the company stores application logs in Amazon S3 for 400 days. The logs are read heavily for the first 30 days, occasionally for the next 90 days, and very rarely after that. Retrieval after day 120 can take up to several hours, but the data must remain available until day 400. Which lifecycle policy is the most cost-effective fit?

A.Keep all logs in S3 Standard for 400 days and enable requester pays to reduce the company's bill.

B.Transition logs to S3 Standard-IA after 30 days, then to S3 Glacier Flexible Retrieval after 120 days, and expire them at 400 days.

C.Transition logs directly from S3 Standard to S3 Glacier Deep Archive after 30 days and expire them at 400 days.

D.Move logs to S3 Intelligent-Tiering only and disable lifecycle transitions because access is unpredictable.

AnswerB

This follows the access pattern and the retrieval-time requirement. S3 Standard fits the heavy-read period in the first 30 days. Standard-IA is a lower-cost choice for the next 90 days when access is only occasional, and Glacier Flexible Retrieval is appropriate after day 120 because the logs are rarely read and can tolerate retrieval in hours. Expiration at day 400 satisfies the retention requirement exactly.

Why this answer

It aligns the storage class transitions with the access patterns: S3 Standard for the first 30 days (heavy reads), S3 Standard-IA for the next 90 days (occasional reads), and S3 Glacier Flexible Retrieval for the remaining period (rare access, with retrieval up to several hours acceptable). This minimizes storage costs while ensuring data availability until day 400, where lifecycle expiration removes the objects.

Exam trap

The trap here is that candidates may choose Option C (S3 Glacier Deep Archive) because it is the cheapest storage class, but they overlook the occasional access requirement between days 30 and 120 and the retrieval time constraints, which make S3 Glacier Flexible Retrieval the correct choice for the final tier.

How to eliminate wrong answers

Option A is wrong because keeping all logs in S3 Standard for 400 days is the most expensive option, and enabling requester pays does not reduce the company's bill for storage costs—it only shifts the cost of data retrieval to the requester, which is irrelevant here as the company owns the data. Option C is wrong because transitioning directly from S3 Standard to S3 Glacier Deep Archive after 30 days ignores the occasional access needs between days 30 and 120; Deep Archive has a retrieval time of 12–48 hours and is not suitable for data that may be accessed occasionally, plus it incurs a minimum storage charge of 180 days. Option D is wrong because S3 Intelligent-Tiering is designed for unpredictable access patterns, but here the access pattern is predictable (heavy, occasional, rare), and disabling lifecycle transitions would prevent automatic cost optimization, leading to higher costs than a tailored lifecycle policy.

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Multi-Selecthard

A company processes product-image uploads in bursts. Each transform takes up to ten minutes, and every job can be retried safely from the beginning. The current EC2 worker fleet is idle most of the day. Which two changes most reduce cost and idle capacity? Select two.

Select 2 answers

A.Buffer jobs in Amazon SQS and let workers scale from queue depth.

B.Run the workers on AWS Fargate Spot, since interruptions are acceptable.

C.Keep a fixed fleet of m6i.large instances in an Auto Scaling group with a higher minimum.

D.Use Reserved Instances for the workers even though demand is highly bursty.

E.Process uploads only during a nightly window so the fleet looks busier.

AnswersA, B

Correct. SQS decouples uploads from processing and smooths bursty demand. Queue depth is a practical scaling signal, so the company avoids paying for idle workers while still absorbing traffic spikes.

Why this answer

Amazon SQS decouples the bursty upload workload from the worker fleet. By using SQS queue depth as the metric for an Auto Scaling policy, workers scale up only when jobs are waiting and scale down to zero during idle periods, eliminating wasted capacity. This directly reduces cost by matching compute resources to actual demand.

Exam trap

The trap here is that candidates may think a fixed fleet or Reserved Instances are cheaper for predictable workloads, but they overlook that bursty, idle-heavy patterns require elastic scaling and spot pricing to truly minimize cost.

Why the other options are wrong

Keeping a fixed fleet with a higher minimum increases idle capacity and cost, as workers are idle most of the day. The goal is to reduce idle capacity, not increase it.

Reserved Instances require a 1- or 3-year commitment and are cost-effective only for steady-state workloads. The bursty, idle-most-day pattern means RIs would be wasted during idle periods, increasing cost without reducing idle capacity.

Processing uploads only during a nightly window does not reduce cost or idle capacity; it simply shifts the workload to a specific time, leaving the fleet idle for the rest of the day and potentially requiring larger capacity to handle the burst.

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MCQeasy

A company stores compliance reports in Amazon S3. Objects are written once and rarely accessed. They need to keep the data for 3 years. When retrieval is needed for an audit, the reports can be restored within hours (not minutes). What storage class should the company use for new objects, assuming minimal operational overhead?

A.S3 Standard

B.S3 Glacier Flexible Retrieval

C.S3 Intelligent-Tiering

D.S3 Glacier Deep Archive

AnswerB

Glacier Flexible Retrieval is designed for infrequent access with retrieval typically on the order of hours.

Why this answer

S3 Glacier Flexible Retrieval is the correct choice because it offers retrieval times of minutes to hours (typically 1–5 minutes for expedited, 3–5 hours for standard), which aligns with the 'within hours' requirement. It is designed for data that is rarely accessed but must be retained for long periods (3 years), and it provides a low-cost storage class with minimal operational overhead since objects can be transitioned via lifecycle policies or stored directly.

Exam trap

The trap here is that candidates often confuse 'Glacier Deep Archive' as the cheapest option for long-term storage, but fail to consider the retrieval time constraint of 12–48 hours, which violates the 'within hours' requirement, making S3 Glacier Flexible Retrieval the correct balance of cost and retrieval speed.

How to eliminate wrong answers

Option A is wrong because S3 Standard is optimized for frequently accessed data with millisecond retrieval, which is unnecessary and cost-inefficient for rarely accessed compliance reports stored for 3 years. Option C is wrong because S3 Intelligent-Tiering automatically moves objects between access tiers based on usage patterns, but it incurs a monthly monitoring fee per object and is not cost-optimal for data that is written once and never accessed again, as it would remain in the infrequent access tier without savings over Glacier Flexible Retrieval. Option D is wrong because S3 Glacier Deep Archive has a retrieval time of 12–48 hours, which exceeds the 'within hours' requirement and would not meet the audit retrieval window.

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MCQmedium

A batch analytics job runs for several hours each night and can be interrupted and restarted. Which EC2 purchasing option should minimize cost? The architecture review board prefers a managed AWS-native control.

A.On-Demand Instances only

B.Dedicated Hosts

C.Spot Instances

D.Provisioned IOPS volumes

AnswerC

Spot Instances offer deep discounts for interruptible workloads.

Why this answer

Spot Instances are correct because the batch job is fault-tolerant (can be interrupted and restarted) and runs for several hours each night, making it an ideal candidate for Spot Instances, which offer up to 90% cost savings compared to On-Demand. AWS-managed services like EC2 Auto Scaling or Amazon EMR can automatically handle Spot Instance interruptions by replacing instances or checkpointing the job, aligning with the architecture review board's preference for a managed AWS-native control.

Exam trap

The trap here is that candidates may choose On-Demand Instances (Option A) due to a misconception that Spot Instances are unreliable for any workload, failing to recognize that fault-tolerant, interruptible jobs like batch processing are exactly the use case for which Spot Instances are designed and recommended for cost optimization.

How to eliminate wrong answers

Option A is wrong because On-Demand Instances provide no interruption but are significantly more expensive than Spot Instances for fault-tolerant workloads, failing to minimize cost. Option B is wrong because Dedicated Hosts are designed for licensing or compliance requirements (e.g., per-socket or per-core licensing) and are the most expensive option, not cost-optimal for a batch job that can tolerate interruptions. Option D is wrong because Provisioned IOPS volumes are a storage type (EBS), not an EC2 purchasing option, and thus irrelevant to the question of minimizing compute cost.

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MCQmedium

A.Add a lifecycle rule to transition backups older than 1 day to S3 Glacier Flexible Retrieval, and keep them until day 90.

B.Add a lifecycle rule to transition backups older than 1 day to S3 Glacier Instant Retrieval, and keep them until day 90.

C.Add a lifecycle rule to transition backups older than 1 day to S3 Glacier Deep Archive, and keep them until day 90 with no restore configuration.

D.Add a lifecycle rule to transition backups older than 1 day to S3 One Zone-IA, and delete them after 7 days.

AnswerA

This option correctly leverages S3 Lifecycle rules to transition older, less frequently accessed backups to S3 Glacier Flexible Retrieval. This storage class provides significant cost savings compared to S3 Standard or S3-IA, while still supporting retrieval times measured in hours, which comfortably meets a 24-hour Recovery Time Objective (RTO). Maintaining retention until day 90 also satisfies the long-term data retention requirement efficiently.

Why this answer

S3 Glacier Flexible Retrieval provides retrieval times from minutes to hours, which meets the 24-hour RTO, and offers significant cost savings over S3 Standard for data that is rarely accessed. Transitioning backups older than 1 day to this storage class reduces costs while retaining them for the required 90-day compliance period.

Exam trap

The trap here is that candidates may choose S3 Glacier Deep Archive for maximum cost savings without verifying that its retrieval time (12–48 hours) can exceed the 24-hour RTO, or they may overlook that S3 Glacier Instant Retrieval is not the most cost-effective option for data that is restored only rarely.

How to eliminate wrong answers

Option B is wrong because S3 Glacier Instant Retrieval is designed for data accessed once a quarter with millisecond retrieval, but it is more expensive than S3 Glacier Flexible Retrieval and not the most cost-optimized choice for backups restored only rarely within a 24-hour RTO. Option C is wrong because S3 Glacier Deep Archive has a retrieval time of 12–48 hours, which may exceed the 24-hour RTO, and the option lacks a restore configuration, making it non-compliant with the RTO requirement. Option D is wrong because S3 One Zone-IA does not provide the durability or availability needed for critical backups, and deleting backups after 7 days violates the 90-day retention policy.

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Multi-Selecthard

A internal reporting portal has old unattached EBS volumes and many stale snapshots. Which two actions reduce storage cost without affecting running instances? The design must avoid adding custom operational scripts.

Select 2 answers

A.Disable CloudTrail logging

B.Stop all EC2 instances in the account

C.Delete unattached EBS volumes after verifying they are no longer needed

D.Apply snapshot lifecycle policies to expire obsolete snapshots

AnswersC, D

Unattached volumes continue to incur charges until deleted.

Why this answer

Deleting unattached EBS volumes directly reduces storage costs without impacting running instances, as these volumes are not in use. Option D is correct because snapshot lifecycle policies automate the deletion of obsolete snapshots, eliminating manual cleanup and reducing storage costs without custom scripts.

Exam trap

The trap here is that candidates might think stopping instances or disabling CloudTrail saves costs, but these actions either disrupt operations or target unrelated services, while the real savings come from cleaning up orphaned storage resources.

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MCQmedium

A marketing site runs on x86 EC2 instances and uses open-source software with no architecture-specific licensing restriction. What should be evaluated to reduce compute cost? The design must avoid adding custom operational scripts.

A.Cross-Region data replication for all data

B.io2 Block Express volumes for all instances

C.AWS Graviton-based instances after performance testing

D.Dedicated Hosts by default

AnswerC

Graviton instances often provide better price performance for compatible workloads.

Why this answer

AWS Graviton-based instances (ARM architecture) offer up to 40% better price-performance compared to comparable x86 instances for many workloads. Since the marketing site uses open-source software with no architecture-specific licensing restrictions, migrating to Graviton after performance testing can significantly reduce compute costs without requiring custom operational scripts, as the OS and software can be recompiled for ARM natively.

Exam trap

The trap here is that candidates may assume Dedicated Hosts (Option D) are a cost-saving measure, but they actually increase costs unless you have specific licensing needs, and they violate the 'no custom operational scripts' constraint by requiring manual host management.

How to eliminate wrong answers

Option A is wrong because Cross-Region data replication increases data transfer and storage costs, and it does not reduce compute costs; it is a disaster recovery or latency optimization strategy, not a cost-saving measure for compute. Option B is wrong because io2 Block Express volumes are high-performance, high-cost SSD volumes designed for latency-sensitive workloads like databases, not for reducing compute costs; they would increase storage costs without affecting compute efficiency. Option D is wrong because Dedicated Hosts are a licensing option that incurs additional per-host charges and are only cost-effective for specific scenarios like bring-your-own-license (BYOL) software with socket/core restrictions; they do not reduce compute costs for open-source software and would increase operational overhead.

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MCQmedium

A risk simulation workload uses CloudWatch Logs heavily. Retaining all debug logs forever is increasing costs. What should be configured?

A.CloudWatch Logs retention policies per log group

B.AWS Config aggregation

C.CloudWatch detailed monitoring on all instances

D.Route 53 health checks

AnswerA

Retention policies automatically delete older logs after the required period.

Why this answer

CloudWatch Logs retention policies allow you to set per-log-group expiration rules (e.g., 30 days, 90 days) to automatically delete old log events, directly reducing storage costs for debug logs that are no longer needed. This is the most cost-effective and targeted solution for managing log lifecycle without affecting other monitoring or configuration services.

Exam trap

The trap here is that candidates may confuse log retention with monitoring frequency or configuration management, mistakenly thinking that reducing metric collection (detailed monitoring) or using Config aggregation will lower log storage costs.

How to eliminate wrong answers

Option B is wrong because AWS Config aggregation is used to collect and centrally view configuration and compliance data from multiple accounts/regions, not to manage log retention or storage costs. Option C is wrong because CloudWatch detailed monitoring on all instances increases metric frequency (1-minute intervals) and incurs additional costs, doing nothing to control log retention or delete old debug logs. Option D is wrong because Route 53 health checks monitor endpoint availability and DNS routing, not log storage or retention policies.

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Multi-Selectmedium

A company is migrating its on-premises workloads to AWS and wants to optimize costs. Which three strategies should the company implement to achieve a cost-optimized architecture? (Choose three.)

Select 3 answers

.Use Reserved Instances or Savings Plans for predictable workloads to reduce costs compared to On-Demand pricing.

.Provision additional EC2 instances to handle peak load at all times, ensuring maximum performance.

.Implement auto scaling to match capacity with demand, avoiding over-provisioning and reducing waste.

.Use Spot Instances for fault-tolerant, flexible workloads to achieve significant cost savings.

.Store all data in Amazon S3 Standard storage class to avoid any data retrieval costs.

.Deploy all resources in a single Availability Zone to minimize data transfer costs.

Why this answer

Reserved Instances or Savings Plans provide significant discounts (up to 72%) over On-Demand pricing for predictable workloads by committing to a specific usage term (1 or 3 years). This directly reduces compute costs for steady-state applications, making it a core cost-optimization strategy.

Exam trap

The trap here is that candidates often confuse 'maximizing performance' with 'cost optimization' and select the option to provision extra instances for peak load, failing to recognize that auto scaling and right-sizing are the correct approaches to balance cost and performance.

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MCQmedium

A company runs an application on EC2 instances in private subnets. The instances must access Amazon S3, and the team currently routes all outbound traffic to the internet through a NAT Gateway. Monthly NAT Gateway charges increased significantly, even though the application only needs to call S3 (not access other public internet services). Which change will most directly reduce NAT Gateway charges while keeping S3 access working?

A.Create a gateway VPC endpoint for S3 and update the private route tables so S3 traffic uses the endpoint instead of the NAT Gateway.

B.Enable S3 Transfer Acceleration on the bucket to reduce the number of S3 calls that go through the NAT Gateway.

C.Switch the EC2 instances to public subnets so S3 calls can use direct internet routing without NAT.

D.Increase the NAT Gateway TCP idle timeout so fewer connections are billed separately for S3 traffic.

AnswerA

A gateway VPC endpoint for S3 keeps S3 traffic within the AWS network. After you add the S3 gateway endpoint and update the private subnet route tables for the S3 prefix list to target the endpoint, S3 API calls from the private subnets no longer traverse the NAT Gateway. This directly reduces both NAT Gateway per-hour charges and NAT data-processing charges associated with S3 traffic. If the application truly only needs S3, you can remove the NAT route for those S3 destinations and rely on the endpoint for S3 connectivity.

Why this answer

A gateway VPC endpoint for S3 allows instances in private subnets to access S3 over the AWS network without traversing the internet. By updating the private route tables to direct S3 traffic to the endpoint, the NAT Gateway is bypassed, eliminating the per-GB data processing charges and hourly NAT Gateway fees for that traffic. This directly reduces costs while maintaining secure, private access to S3.

Exam trap

The trap here is that candidates may think S3 Transfer Acceleration or increasing NAT Gateway timeouts will reduce costs, but they fail to recognize that a gateway VPC endpoint eliminates the NAT Gateway entirely for S3 traffic, directly addressing the cost issue without compromising security.

How to eliminate wrong answers

Option B is wrong because S3 Transfer Acceleration speeds up uploads over long distances using AWS edge locations, but it does not reduce the amount of traffic going through the NAT Gateway; it actually adds additional costs per GB transferred and still requires internet routing. Option C is wrong because moving EC2 instances to public subnets exposes them directly to the internet, violating the requirement for private subnets and introducing security risks; it also does not reduce NAT Gateway charges since the NAT Gateway is no longer used, but the question asks for a change that reduces NAT Gateway charges while keeping S3 access working, not for a security redesign. Option D is wrong because increasing the TCP idle timeout does not reduce NAT Gateway charges; it may actually increase costs by keeping connections open longer, and NAT Gateway billing is based on data processing and hourly usage, not per-connection billing.

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MCQmedium

A marketing team runs a report-generation process that must execute once per day at 02:00 UTC. It usually completes in 10315 minutes, but sometimes takes up to 45 minutes due to varying data volumes. They currently run the workload on an EC2 instance that is always on, which wastes money during off-hours. The team wants to minimize operational overhead and pay mainly for actual execution time. What is the best architecture choice?

A.Use a scheduled Amazon EC2 Auto Scaling group that keeps a minimum of one instance running at all times.

B.Use an EventBridge schedule to run the report as an Amazon ECS task on AWS Fargate and write results to S3.

C.Use AWS Lambda triggered by an EventBridge schedule at 02:00 UTC and write results to S3.

D.Use an EMR cluster provisioned daily with manual teardown to ensure the instance is always available before 02:00.

AnswerB

Fargate allows the containerized job to run only when scheduled, so the team pays for task runtime instead of keeping an EC2 instance always on.

Why this answer

Amazon ECS on AWS Fargate is the best choice because it eliminates the need to manage servers, scales automatically, and charges only for the vCPU and memory resources consumed during task execution. The EventBridge schedule triggers the Fargate task at 02:00 UTC, and the report is written to S3, which provides durable, cost-effective storage. This architecture minimizes operational overhead and cost by avoiding an always-on EC2 instance.

Exam trap

The trap here is that candidates may choose AWS Lambda without considering its 15-minute execution timeout, which cannot handle the 45-minute maximum runtime of this report-generation process.

Why the other options are wrong

This option keeps an instance running at all times, which wastes money during off-hours and does not minimize operational overhead or pay mainly for actual execution time.

AWS Lambda has a maximum execution timeout of 15 minutes, but the report-generation process can take up to 45 minutes, so Lambda cannot handle the entire workload.

Provisioning an EMR cluster daily with manual teardown introduces significant operational overhead, which contradicts the requirement to minimize operational overhead. Additionally, EMR is designed for big data processing (e.g., Spark, Hive) and is overkill for a simple report-generation task, leading to higher costs and complexity.

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Multi-Selecthard

A SaaS vendor has a steady 24/7 control plane on ECS and several small event-driven tasks that currently run on a separate always-on service. Management wants the billing discount that applies across both ECS and Lambda usage without committing to a specific instance family. Which two actions are best? Select two.

Select 2 answers

A.Buy a Compute Savings Plan for the predictable baseline usage.

B.Move the event-driven tasks to AWS Lambda instead of keeping a separate always-on service.

C.Buy an EC2 Instance Savings Plan tied to one instance family for all workloads.

D.Use Spot Instances for the control plane because it is the largest bill.

E.Increase the ECS desired count so Lambda can be removed.

AnswersA, B

Correct. A Compute Savings Plan discounts predictable compute spend across ECS and Lambda without binding the team to one instance family. That flexibility matches a mixed compute estate and avoids overcommitting.

Why this answer

A Compute Savings Plan offers the largest discount (up to 66%) across both ECS and Lambda usage without committing to a specific instance family, which matches the requirement to cover both services flexibly. It applies to any EC2 instance, including those used by ECS, and to AWS Lambda compute, making it ideal for a mixed workload with a predictable baseline.

Exam trap

The trap here is that candidates confuse Savings Plans with Reserved Instances or Spot Instances, assuming a specific instance family commitment is required, or they think Spot Instances can replace a billing discount mechanism for a steady workload.

Why the other options are wrong

An EC2 Instance Savings Plan is tied to a specific instance family and region, which does not cover Lambda usage. The question requires a discount that applies across both ECS and Lambda, so a Compute Savings Plan is needed instead.

The control plane runs 24/7 and is steady, so it is not suitable for Spot Instances, which can be interrupted. The question asks for a discount covering both ECS and Lambda, but Spot Instances only apply to EC2, not Lambda.

Increasing ECS desired count does not provide a billing discount across ECS and Lambda usage; it only increases ECS costs and does not eliminate the need for Lambda or provide a savings plan.

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MCQmedium

A test environment runs on x86 EC2 instances and uses open-source software with no architecture-specific licensing restriction. What should be evaluated to reduce compute cost? The design must avoid adding custom operational scripts.

A.Cross-Region data replication for all data

B.AWS Graviton-based instances after performance testing

C.io2 Block Express volumes for all instances

D.Dedicated Hosts by default

AnswerB

Graviton instances often provide better price performance for compatible workloads.

Why this answer

AWS Graviton-based instances (ARM architecture) offer up to 40% better price-performance compared to x86 instances for many workloads. Since the environment uses open-source software with no architecture-specific licensing restrictions, migrating to Graviton after performance testing can significantly reduce compute costs without requiring custom operational scripts, as AWS provides native support for ARM-based instances.

Exam trap

The trap here is that candidates may confuse cost optimization with performance improvement or licensing requirements, leading them to select Dedicated Hosts or high-performance storage options that actually increase costs.

How to eliminate wrong answers

Option A is wrong because cross-region data replication increases data transfer and storage costs, and it does not directly address compute cost reduction. Option C is wrong because io2 Block Express volumes are high-performance, high-cost EBS volumes designed for I/O-intensive workloads, not for reducing compute costs, and they would increase storage costs unnecessarily. Option D is wrong because Dedicated Hosts incur additional per-host charges and are used for licensing or compliance requirements, not for cost optimization; they would increase compute costs rather than reduce them.

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Multi-Selectmedium

A company is running a production web application on Amazon EC2 instances behind an Application Load Balancer (ALB). The workload has predictable traffic spikes during business hours and low traffic at night. The current architecture uses On-Demand EC2 instances, leading to high costs. The company wants to reduce costs without sacrificing availability or performance. Which three of the following strategies would help achieve this goal? (Choose three.)

Select 3 answers

.Purchase Reserved Instances for the baseline capacity that runs 24/7.

.Add Spot Instances for the entire workload during peak hours.

.Use Auto Scaling with a mixed instances policy that includes On-Demand and Spot Instances.

.Migrate to AWS Lambda for all web application traffic.

.Implement a scheduled scaling action to increase capacity before business hours and decrease after.

.Consolidate all instances into a single larger instance to reduce overhead.

Why this answer

Purchasing Reserved Instances for the baseline 24/7 capacity provides a significant discount (up to 72%) compared to On-Demand pricing, directly reducing costs for the always-running portion of the workload. This strategy is correct because it matches the predictable, steady-state traffic component without sacrificing availability or performance.

Exam trap

The trap here is that candidates may think Spot Instances can be used for the entire workload during peak hours, but they overlook the interruption risk and the requirement for the workload to be fault-tolerant, which a production web application behind an ALB typically is not without careful design.

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Multi-Selecthard

A product catalog system uses a relational database for orders and a simple key-value profile store for shopping carts. Traffic is unpredictable, and the company wants to avoid paying for large idle database instances. Which two choices are best? Select two.

Select 2 answers

A.Use Aurora Serverless v2 for the relational order system.

B.Use DynamoDB on-demand capacity for the shopping-cart profile store.

C.Keep both workloads on large provisioned RDS instances and add read replicas for the cart store.

D.Use DynamoDB provisioned capacity with a fixed minimum despite the unpredictable traffic.

E.Replace the relational order system with a wide-column table to reduce SQL licensing.

AnswersA, B

Correct. Aurora Serverless v2 is designed for variable relational workloads because capacity can scale without constantly paying for a large fixed instance. It preserves SQL features while reducing idle overprovisioning.

Why this answer

Aurora Serverless v2 automatically scales compute capacity up and down based on demand, so you only pay for the resources you use. This eliminates the need to provision for peak traffic and avoids paying for large idle database instances, making it cost-optimized for unpredictable workloads.

Exam trap

The trap here is that candidates may think provisioned capacity with a minimum is acceptable for unpredictable traffic, but the question explicitly requires avoiding paying for idle capacity, so on-demand or serverless options are the only correct choices.

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Multi-Selecthard

An application stores user-uploaded binaries in S3. Access is unpredictable for the first month, then most objects become cold. The team wants the cheapest approach that avoids manually guessing access patterns. Which two actions are best? Select two.

Select 2 answers

A.Enable S3 Intelligent-Tiering on the bucket.

B.Keep all objects in S3 Standard because lifecycle transitions add too much management.

C.Add a lifecycle rule to move very old objects to S3 Glacier Deep Archive when minute-level retrieval is no longer required.

D.Copy all binaries to Amazon EFS so retrieval is faster.

E.Disable versioning because S3 Intelligent-Tiering needs it to work.

AnswersA, C

Correct. Intelligent-Tiering is designed for objects with uncertain or changing access patterns. It automatically moves data between access tiers, reducing the need for manual guessing and avoiding overpaying for standard storage.

Why this answer

A is correct because S3 Intelligent-Tiering automatically moves objects between access tiers based on changing access patterns, eliminating the need to manually guess or configure lifecycle rules. It charges a small monthly monitoring fee per object but avoids the higher cost of keeping cold data in S3 Standard, making it the cheapest hands-off approach for unpredictable access followed by cold storage.

Exam trap

The trap here is assuming that lifecycle rules require manual guessing of access patterns, when S3 Intelligent-Tiering automates this without upfront configuration, and that versioning is a prerequisite for Intelligent-Tiering, which it is not.

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MCQmedium

A media company runs a 24/7 recommendation engine on EC2 in one AWS Region. The workload is interruption-intolerant, and the team expects steady usage but may change instance families and sizes during planned optimizations. Compared to the current On-Demand setup, they want the lowest cost while avoiding the rigidity of locking to a specific instance type. What should the solutions architect recommend?

A.Switch the instances to Spot Instances and use interruption handling because it is the largest discount.

B.Purchase a Compute Savings Plan for the expected steady hourly usage in that Region.

C.Purchase a Standard Reserved Instance tied to a single specific instance type for the next 3 years.

D.Keep On-Demand and rely on Auto Scaling to reduce capacity when utilization is low.

AnswerB

Compute Savings Plans discount the usage while allowing flexibility across instance families and sizes in the Region.

Why this answer

A Compute Savings Plan offers the lowest cost for steady-state usage without locking to a specific instance type, providing up to 66% discount over On-Demand while allowing flexibility to change instance families, sizes, OS, or tenancy within a Region. This matches the requirement for cost savings with instance flexibility during planned optimizations.

Exam trap

The trap here is that candidates often confuse Reserved Instances with Savings Plans, assuming a Standard Reserved Instance is the only way to get significant discounts, but the question explicitly requires flexibility to change instance families, which a Compute Savings Plan provides while a Standard Reserved Instance does not.

How to eliminate wrong answers

Option A is wrong because Spot Instances can be interrupted with a 2-minute warning, making them unsuitable for an interruption-intolerant workload that runs 24/7. Option C is wrong because a Standard Reserved Instance locks to a specific instance type in a specific AZ, which contradicts the requirement to avoid rigidity and change instance families during optimizations. Option D is wrong because keeping On-Demand provides no cost savings, and Auto Scaling reduces capacity only when utilization is low, not addressing the need for lowest cost on steady usage.

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MCQmedium

A company hosts an application on EC2 instances in private subnets. The instances must (1) read objects from Amazon S3 and (2) retrieve secrets from AWS Secrets Manager. The team currently sends all outbound traffic through a NAT gateway to reach both services. They want to reduce monthly cost while keeping traffic private (no internet egress) and without changing application logic. Which change is the most cost-effective?

A.Create a Gateway VPC endpoint for S3 and an Interface VPC endpoint for Secrets Manager, and ensure the subnet route tables / endpoint routing directs those service calls to the endpoints instead of the NAT gateway.

B.Keep the NAT gateway, but add AWS WAF rules to block non-service outbound requests to reduce NAT usage.

C.Disable IPv4 on the VPC subnets and rely on IPv6-only egress to reduce NAT gateway costs.

D.Replace the NAT gateway with a VPC firewall appliance instance to proxy outbound calls and reduce NAT fees.

AnswerA

This is the most cost-effective change because it removes the need to traverse the NAT gateway for those AWS service calls. S3 uses a Gateway VPC endpoint (route-table-based) for traffic to the S3 prefix list, so requests to S3 stay on the AWS network. Secrets Manager uses an Interface VPC endpoint (ENIs with private DNS), so requests to Secrets Manager stay private within the VPC/VPC endpoint network path. Because the application still calls the same AWS APIs, there is no logic change, and NAT data-processing charges drop to near zero for S3/Secrets Manager traffic.

Why this answer

Gateway VPC Endpoints for S3 and Interface VPC Endpoints for Secrets Manager allow private connectivity to these AWS services without traversing the internet or a NAT gateway. This eliminates NAT gateway hourly charges and data processing fees, reducing costs while keeping traffic within the AWS network. The application logic remains unchanged as the endpoints are accessed via the same DNS names, with route tables directing traffic to the endpoints instead of the NAT gateway.

Exam trap

The trap here is that candidates may assume NAT gateways are the only way to provide private subnet internet access, overlooking that VPC endpoints can provide private, cost-effective connectivity to specific AWS services without internet egress.

How to eliminate wrong answers

Option B is wrong because AWS WAF is a web application firewall for HTTP/HTTPS traffic, not a mechanism to reduce NAT gateway costs; it does not eliminate the NAT gateway's hourly and per-GB data processing fees. Option C is wrong because disabling IPv4 and relying on IPv6-only egress would require the application to use IPv6 addresses, which changes the application logic and may not be supported by all services; additionally, NAT gateways are not used for IPv6 traffic (egress-only internet gateways are used), so this does not address the cost of the NAT gateway for IPv4 traffic. Option D is wrong because replacing the NAT gateway with a VPC firewall appliance instance still incurs instance costs and management overhead, and it does not eliminate the need for internet egress to reach S3 and Secrets Manager unless endpoints are used; it is not more cost-effective than using VPC endpoints.

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MCQmedium

A log archive serves infrequently accessed user documents that must be available immediately when requested. Which S3 storage class is likely the best cost fit? The design must avoid adding custom operational scripts.

A.Instance store volumes

B.S3 Standard-IA or S3 One Zone-IA depending on resilience requirements

C.S3 Standard for all objects

D.S3 Glacier Deep Archive

AnswerB

Infrequent Access classes reduce storage cost while keeping millisecond retrieval.

Why this answer

S3 Standard-IA or S3 One Zone-IA is the best cost fit because the workload involves infrequently accessed documents that require immediate retrieval. These storage classes offer lower storage costs than S3 Standard while maintaining low-latency access (milliseconds), and they avoid custom operational scripts since retrieval is automatic via standard S3 GET requests. The choice between Standard-IA and One Zone-IA depends on whether the data requires multi-AZ resilience or can tolerate a single-AZ failure.

Exam trap

AWS often tests the misconception that 'infrequently accessed' automatically means Glacier or Deep Archive, but the key differentiator is the 'immediate availability' requirement, which eliminates any cold storage class with retrieval delays.

How to eliminate wrong answers

Option A is wrong because instance store volumes are ephemeral block storage attached to EC2 instances, not a durable S3 storage class, and they lose data on instance stop/termination, making them unsuitable for long-term log archives. Option C is wrong because S3 Standard is designed for frequently accessed data with higher storage costs, making it cost-inefficient for infrequently accessed documents, even though it provides immediate availability. Option D is wrong because S3 Glacier Deep Archive has retrieval times of 12-48 hours (not immediate), which violates the requirement for documents to be available immediately when requested.

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Multi-Selecthard

A startup has three sandbox accounts and one production account. The CTO wants lower cost and operational overhead while keeping central purchasing and spend visibility. Which two actions are best? Select two.

Select 2 answers

A.Enable consolidated billing under AWS Organizations so discounts and shared purchasing apply across accounts.

B.Move each sandbox to its own payer account to isolate spend from the rest.

C.Use managed services such as Amazon RDS or Amazon S3 instead of self-managed EC2-based databases and file servers where practical.

D.Buy Dedicated Hosts for sandbox workloads to get a lower blended rate.

E.Disable AWS Budgets because consolidated billing already solves visibility.

AnswersA, C

Correct. Consolidated billing centralizes purchasing and can improve discount usage across linked accounts. It also gives the company one payer view, which simplifies governance and visibility.

Why this answer

Enabling consolidated billing under AWS Organizations aggregates usage across all accounts, allowing the startup to benefit from volume discounts, Reserved Instance sharing, and Savings Plans across the sandbox and production accounts. This reduces operational overhead by centralizing payment and provides a single view of spend, meeting the CTO's requirements for cost and visibility.

Exam trap

The trap here is that candidates might think Dedicated Hosts (Option D) reduce costs for sandbox workloads, but they actually increase costs due to per-host billing and are intended for specific licensing scenarios, not general cost optimization.

Why the other options are wrong

Moving each sandbox to its own payer account increases operational overhead and reduces cost visibility, contradicting the goal of lowering cost and overhead while maintaining central purchasing and spend visibility.

Dedicated Hosts increase cost and operational overhead, contradicting the goal of lowering cost and overhead. They are not needed for sandbox workloads and do not provide a lower blended rate compared to Reserved Instances or Savings Plans under consolidated billing.

Disabling AWS Budgets removes spend visibility, which the CTO explicitly wants to maintain. Consolidated billing does not automatically provide visibility; budgets and alerts are still needed.

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MCQmedium

An Auto Scaling group for a background worker runs EC2 instances continuously. Over the last 30 days, CloudWatch shows sustained CPU utilization around 6% with no memory pressure, and queue processing latency meets all SLAs. The team wants to lower monthly cost with minimal risk. What is the best next action?

A.Increase the instance size to reduce CPU throttling risk

B.Perform right sizing by downsizing to a smaller instance family/size and validate SLAs

C.Switch the group to Spot Instances to reduce cost without changing instance sizing

D.Buy Reserved Instances with a long term commitment before making any sizing changes

AnswerB

Right sizing uses actual utilization to remove overprovisioning. With low CPU and no memory pressure and SLAs already met, downsizing (while validating under load and during a controlled rollout) is the safest way to reduce waste.

Why this answer

The current instance type is over-provisioned, as sustained CPU utilization is only 6% with no memory pressure and all SLAs are met. Right-sizing to a smaller instance family or size directly reduces compute cost while maintaining performance, making it the lowest-risk, cost-optimization action. This aligns with the AWS Well-Architected Framework's cost optimization pillar, which recommends matching instance capacity to actual workload requirements.

Exam trap

The trap here is that candidates may assume Spot Instances are always the cheapest option, but they ignore the risk of interruption for a continuously running workload where SLAs must be met, making right-sizing the safer and more appropriate first step.

How to eliminate wrong answers

Option A is wrong because increasing instance size would raise costs and is unnecessary given the low CPU utilization and no performance issues. Option C is wrong because switching to Spot Instances introduces the risk of interruption, which is not minimal risk for a continuously running background worker that must meet SLAs. Option D is wrong because buying Reserved Instances before right-sizing locks in a commitment for an over-provisioned instance type, increasing cost without addressing the root cause of waste.

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MCQeasy

An internal team runs a report-generation job once per day. It typically finishes in a few minutes, and even on its slowest days it still completes in under 15 minutes. The team wants to reduce operational overhead and pay primarily for actual runtime instead of keeping servers running 24/7. Which AWS approach best matches these goals?

A.Deploy the job on EC2 instances and keep them running continuously for the daily schedule.

B.Use AWS Lambda triggered by a schedule (for example, EventBridge) to run the report at the required time.

C.Run the job in an RDS database using stored procedures scheduled by the database engine.

D.Use an Auto Scaling group with a fixed minimum size of one instance and disable scaling.

AnswerB

Lambda runs on demand and charges for execution time, aligning spend with actual job runtime and reducing ops.

Why this answer

AWS Lambda, triggered by Amazon EventBridge (CloudWatch Events), is ideal for short-lived, infrequent jobs like this daily report. It eliminates idle server costs by running only when invoked, and the 15-minute execution timeout comfortably covers the job's maximum runtime. This serverless approach directly reduces operational overhead and aligns with a pay-per-use cost model.

Exam trap

The trap here is that candidates may assume EC2 or Auto Scaling is needed for any scheduled job, overlooking that Lambda's 15-minute timeout and serverless pricing perfectly suit short, infrequent tasks, while the 'pay primarily for actual runtime' requirement explicitly points away from always-on compute.

Why the other options are wrong

Keeping EC2 instances running 24/7 incurs costs for idle time, contradicting the goal of paying primarily for actual runtime when the job completes in under 15 minutes daily.

Running the job as stored procedures in RDS would still require a running database instance 24/7, incurring costs for idle time, and does not align with the goal of paying primarily for actual runtime.

An Auto Scaling group with a fixed minimum size of one instance keeps an EC2 instance running 24/7, which incurs costs for idle time and does not reduce operational overhead or pay-per-use runtime.

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MCQhard

A dev sandbox currently uses two NAT gateways in each of three Availability Zones, but only one private subnet per AZ needs outbound internet access. What should the architect review first? The design must avoid adding custom operational scripts.

A.Disabling route tables

B.Replacing every NAT gateway with an internet gateway attached to private subnets

C.Moving all workloads to public subnets

D.Whether one NAT gateway per AZ is sufficient for the required private subnets

AnswerD

NAT gateways are normally deployed per AZ for resilience; duplicate NAT gateways in the same AZ may be unnecessary.

Why this answer

The question asks what the architect should review first to optimize costs while maintaining functionality. Using two NAT gateways per AZ when only one private subnet per AZ needs outbound internet access is redundant; a single NAT gateway per AZ can handle the traffic for all private subnets in that AZ. The design must avoid custom operational scripts, so the simplest review is to check if one NAT gateway per AZ is sufficient, which would reduce costs without breaking connectivity.

Exam trap

The trap here is that candidates may assume more NAT gateways are always better for high availability, but the question asks for a cost-optimization review first, and the current setup is over-provisioned for the stated requirement.

How to eliminate wrong answers

Option A is wrong because disabling route tables would break all routing, not just optimize NAT gateway usage, and it would require custom scripts to restore functionality, violating the design constraint. Option B is wrong because internet gateways cannot be attached to private subnets; they are used for public subnets and would expose instances directly to the internet, breaking the private subnet isolation requirement. Option C is wrong because moving all workloads to public subnets would expose them to the internet, which is not suitable for a dev sandbox that likely requires private subnets for security, and it does not address the NAT gateway cost issue.

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Multi-Selectmedium

A startup runs two EC2-based workloads in the same AWS Region. Its customer-facing API is always on, and its nightly video transcoding fleet can restart jobs from checkpoints if an instance is interrupted. The finance team wants the lowest monthly compute cost without changing the application design. Which two actions should the team take? Select two.

Select 2 answers

A.Purchase an All Upfront Reserved Instance for the transcoding fleet only.

B.Buy a Compute Savings Plan to cover the always-on API baseline usage.

C.Run the transcoding fleet on Spot Instances because interrupted jobs can resume from checkpoints.

D.Increase the API instance size so CPU utilization stays below 30 percent.

E.Move the API tier to Dedicated Hosts to improve isolation and lower spend.

AnswersB, C

Savings Plans reduce cost for consistent compute usage and are well suited to the always-on API.

Why this answer

A Compute Savings Plan offers the lowest cost for steady-state workloads like the always-on API, providing up to 66% savings over On-Demand in exchange for a 1- or 3-year commitment. It applies to any EC2 instance family within a Region, making it flexible and cost-effective for the baseline usage. Option C is correct because Spot Instances can be up to 90% cheaper than On-Demand and are ideal for fault-tolerant workloads like the transcoding fleet, which can resume from checkpoints if interrupted.

Exam trap

The trap here is that candidates often assume Reserved Instances are always the cheapest option, but for interruptible workloads like transcoding, Spot Instances provide far greater savings, and a Savings Plan better covers the steady-state API usage without locking into a specific instance family.

Why the other options are wrong

The transcoding fleet can handle interruptions, so Spot Instances are cheaper than Reserved Instances. Purchasing All Upfront Reserved Instances for the transcoding fleet would lock in higher costs unnecessarily.

Increasing instance size to keep CPU below 30% wastes compute capacity and increases cost, contradicting the goal of lowest monthly compute cost. The question explicitly states not to change application design, and this action changes the instance type.

Dedicated Hosts increase cost due to per-host billing and do not lower spend; they are used for licensing or compliance, not cost savings. The question asks for lowest compute cost, so this option is counterproductive.

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MCQeasy

An EC2 workload runs in one region on a single instance type. For the last month, CloudWatch metrics show average CPU utilization of 12% and no sustained memory pressure. The team wants to reduce cost while maintaining the current performance level. What is the best first step?

A.Use AWS Compute Optimizer to get recommendations for instance type and size changes.

B.Increase the instance size to reduce the risk of performance regression.

C.Switch to Spot Instances immediately to reduce cost regardless of utilization.

D.Disable detailed monitoring to lower CloudWatch charges.

AnswerA

AWS Compute Optimizer analyzes historical metrics (such as CPU and memory utilization) and recommends instance type and size changes to improve cost-effectiveness while targeting performance. Given sustained low CPU and no sustained memory pressure, this is the most direct first step to identify a smaller/fewer-overprovisioned instance configuration that can maintain performance.

Why this answer

AWS Compute Optimizer analyzes historical utilization metrics (CPU, memory, I/O) and provides actionable recommendations for right-sizing instances. Given the average CPU utilization of only 12% and no memory pressure, Compute Optimizer will likely recommend a smaller instance type or family that matches the workload's actual resource needs, reducing cost without affecting performance.

Exam trap

The trap here is that candidates may think increasing instance size (Option B) is a safe 'performance buffer' move, but the question explicitly asks to reduce cost while maintaining current performance, making right-sizing via Compute Optimizer the logical first step.

How to eliminate wrong answers

Option B is wrong because increasing instance size would raise costs unnecessarily when utilization is already low, and it does not address the goal of cost reduction. Option C is wrong because switching to Spot Instances without first analyzing workload suitability risks interruption and potential performance degradation; Spot Instances are not a guaranteed cost-reduction strategy for all workloads. Option D is wrong because disabling detailed monitoring (1-minute metrics) saves only a trivial amount and does not address the primary cost driver—compute instance charges—while losing granular visibility needed for right-sizing decisions.

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MCQeasy

A media company runs a batch job that processes image thumbnails. The job can be restarted from checkpoints and does not have user-facing SLAs. The batch capacity can tolerate interruptions. Which EC2 purchasing option is the best cost optimization choice?

A.Use On-Demand Instances because interruptions are not allowed for production workloads.

B.Use EC2 Spot Instances, accepting the possibility of interruptions and using checkpoints to resume.

C.Purchase Reserved Instances because they provide a discount regardless of the workload timing.

D.Buy Savings Plans because they guarantee capacity and remove the risk of interruptions entirely.

AnswerB

Spot Instances are typically the cheapest option for workloads that can tolerate interruptions with recovery.

Why this answer

Spot Instances offer significant cost savings (up to 90% compared to On-Demand) and are ideal for fault-tolerant, stateless, or checkpointable workloads like batch image thumbnail processing. Since the job can resume from checkpoints and tolerates interruptions, Spot Instances provide the best cost optimization without compromising functionality.

Exam trap

The trap here is that candidates may assume production workloads require On-Demand or Reserved Instances, but the question explicitly states the job has no user-facing SLAs and tolerates interruptions, making Spot Instances the correct cost-optimized choice despite the 'production' label.

How to eliminate wrong answers

Option A is wrong because On-Demand Instances are not cost-optimized for workloads that can tolerate interruptions; they are priced higher and provide no interruption risk, which is unnecessary here. Option C is wrong because Reserved Instances require a 1- or 3-year commitment and are designed for steady-state, predictable workloads, not for batch jobs that can be interrupted and resumed. Option D is wrong because Savings Plans offer discounted rates in exchange for a commitment to a consistent amount of compute usage (measured in $/hour), but they do not guarantee capacity or remove interruption risk; Spot Instances can still be interrupted under Savings Plans, and the question asks for the best cost optimization choice, not a capacity guarantee.

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MCQeasy

A team runs an Amazon NLB in a VPC with targets registered in multiple Availability Zones (AZs). Their bill shows high inter-AZ data transfer charges. They want to reduce unnecessary cross-AZ traffic costs while still maintaining healthy targets per AZ. What change is most likely to reduce inter-AZ charges?

A.Disable cross-zone load balancing on the NLB so each client is routed to targets in the same AZ when possible.

B.Enable cross-zone load balancing so all targets receive traffic from every AZ.

C.Move the NLB to a different Region so traffic is always kept local.

D.Replace the NLB with a NAT gateway to reduce data charges between AZs.

AnswerA

Disabling cross-zone load balancing helps keep traffic within the same AZ, reducing inter-AZ data transfer charges.

Why this answer

Disabling cross-zone load balancing on an NLB ensures that each client is routed only to targets within the same Availability Zone as the NLB node that receives the traffic. This eliminates inter-AZ data transfer charges because traffic never leaves the AZ boundary. The NLB still maintains healthy targets per AZ by distributing traffic only among healthy targets within that AZ.

Exam trap

The trap here is that candidates often assume enabling cross-zone load balancing always reduces costs or improves performance, but for NLB it actually increases inter-AZ data transfer charges, and the question specifically asks for cost reduction, not high availability.

Why the other options are wrong

Enabling cross-zone load balancing would increase inter-AZ traffic because the NLB would distribute requests across all AZs, incurring higher data transfer charges, which is the opposite of the goal to reduce costs.

Moving the NLB to a different Region does not reduce inter-AZ data transfer charges; it would increase costs due to cross-Region traffic and latency, and does not address the issue of cross-AZ traffic within the original VPC.

A NAT Gateway is used for outbound internet traffic from private subnets, not for load balancing traffic between AZs. Replacing an NLB with a NAT Gateway would not reduce inter-AZ data charges and would break the load balancing functionality.

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MCQmedium

A test environment stores logs in S3. Logs are queried for 30 days, rarely accessed for one year, and then retained for compliance. What should reduce storage cost? The design must avoid adding custom operational scripts.

A.Keep all logs in S3 Standard indefinitely

B.Move all logs immediately to S3 Glacier Deep Archive

C.S3 lifecycle policy that transitions objects to lower-cost storage classes over time

D.Use EBS snapshots for the logs

AnswerC

Lifecycle rules automate transitions based on age, matching storage cost to access patterns.

Why this answer

S3 lifecycle policies automate the transition of objects between storage classes based on age, allowing logs to move from S3 Standard (for frequent querying) to S3 Standard-IA or S3 One Zone-IA (for rare access), and eventually to S3 Glacier Deep Archive (for long-term compliance retention). This reduces storage cost without custom scripts, aligning with the requirement to avoid operational overhead.

Exam trap

The trap here is that candidates may choose Option B (immediate move to Glacier Deep Archive) thinking it minimizes cost, but they overlook the 30-day query requirement, which makes S3 Standard necessary for fast retrieval, and fail to recognize that lifecycle policies provide a graduated, automated approach.

How to eliminate wrong answers

Option A is wrong because keeping all logs in S3 Standard indefinitely incurs the highest storage cost, ignoring the cost savings from transitioning to lower-cost classes for rarely accessed and compliance-retained data. Option B is wrong because moving all logs immediately to S3 Glacier Deep Archive prevents the 30-day querying requirement, as retrieval times are hours and costs are high for frequent access, violating the design need for queryability. Option D is wrong because EBS snapshots are block-level backups for EC2 instances, not designed for log storage in S3, and would introduce unnecessary complexity and cost without addressing the tiered access pattern.

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MCQmedium

A media company uploads raw video thumbnails to an S3 bucket every hour. The application needs these thumbnails for active browsing for the first 7 days. After day 7, access becomes rare. Requirements: - Objects must remain available in S3 for at least 180 days total. - After day 7, the team can tolerate retrieval latency in the range of minutes to hours. - They want to minimize storage cost while keeping the ability to read objects (no application changes required). Which storage strategy is the most cost-optimized fit?

A.Use a bucket-level lifecycle rule to transition objects to S3 Standard-IA on day 7 and then expire them after day 180.

B.Use a lifecycle rule to transition objects to S3 Glacier Flexible Retrieval after day 7 and expire them after day 180.

C.Keep all objects in S3 Standard for 180 days, and enable S3 Intelligent-Tiering only if the bucket’s access frequency is above a threshold.

D.Use a lifecycle rule to transition objects to S3 Glacier Instant Retrieval after day 7 and expire them after day 180.

AnswerB

Glacier Flexible Retrieval is designed for infrequent access and supports restore times compatible with minutes to hours. Transitioning after day 7 reduces storage cost for the long period where access is rare, while expiring at day 180 satisfies the 180-day retention requirement. The application can still use S3 GetObject; retrieval simply takes longer due to the archival tier.

Why this answer

S3 Glacier Flexible Retrieval provides retrieval times from minutes to hours, which matches the tolerance for rare access after day 7, and offers the lowest storage cost among the options for data that is rarely accessed. A lifecycle rule transitions objects from S3 Standard (used for the first 7 days of active browsing) to Glacier Flexible Retrieval on day 7, then expires them after day 180, meeting the 180-day retention requirement without application changes.

Exam trap

The trap here is that candidates often choose S3 Glacier Instant Retrieval (Option D) because of the word 'Instant,' overlooking that the requirement explicitly tolerates minutes-to-hours latency, making the cheaper Glacier Flexible Retrieval the better cost-optimized choice.

How to eliminate wrong answers

Option A is wrong because S3 Standard-IA is designed for infrequent access but still incurs higher storage costs than Glacier Flexible Retrieval for data that is accessed rarely (minutes-to-hours latency is acceptable), and it does not provide the lowest cost for this use case. Option C is wrong because keeping all objects in S3 Standard for 180 days is significantly more expensive than transitioning to a colder storage class, and S3 Intelligent-Tiering is not cost-optimized for a predictable access pattern (active for 7 days, then rarely accessed) as it adds monitoring costs and may not move objects to the cheapest tier quickly enough. Option D is wrong because S3 Glacier Instant Retrieval is designed for millisecond retrieval, which is unnecessary and more expensive than Glacier Flexible Retrieval when minutes-to-hours latency is acceptable, thus not the most cost-optimized choice.

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Multi-Selecthard

Multiple teams share one AWS Organization. Finance wants chargeback by project, alerts before overspend, and monthly views by account without manually opening each account. Which three actions best fit? Select three.

Select 3 answers

A.Enforce cost allocation tags on resources and activate them for billing reports.

B.Use AWS Budgets to create alerts and budget actions for each project.

C.Use Cost Explorer or Cost and Usage Reports to analyze spend by account, tag, and service.

D.Put every team in a separate AWS account and ignore tagging.

E.Use CloudTrail trails to estimate spend by resource because it records API calls.

AnswersA, B, C

Correct. Cost allocation tags are the foundation for project-level chargeback. Once activated for billing, they let finance group spend by business unit, application, or environment.

Why this answer

Cost allocation tags, when activated for billing reports, allow you to tag resources with project-specific metadata (e.g., 'Project:Alpha'). AWS then includes these tags in the Cost and Usage Reports (CUR) and Cost Explorer, enabling Finance to filter and allocate costs by project without manual account inspection. This directly supports chargeback by project and monthly views by account and tag.

Exam trap

The trap here is that candidates may confuse CloudTrail (which records API calls) with AWS Cost Explorer or CUR (which provide actual cost data), leading them to incorrectly select option E for cost estimation.

Why the other options are wrong

Putting teams in separate accounts without tagging prevents chargeback by project and requires manual account access for monthly views, failing to meet the requirements for cost allocation and automated reporting.

CloudTrail records API calls for auditing, not cost allocation. It does not provide cost or usage data by resource, tag, or project, so it cannot support chargeback, alerts, or monthly views by account.

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Multi-Selecthard

A retailer runs a reporting-heavy relational app on Amazon RDS MySQL. Peak dashboard traffic lasts only three hours each day, but the database is sized for the peak all day. The business wants lower cost without rewriting the application. Which three actions are best? Select three.

Select 3 answers

A.Right-size the writer based on actual utilization instead of peak guesses.

B.Add read replicas and direct dashboard traffic away from the writer.

C.Evaluate Aurora MySQL if the current replica-heavy design would be cheaper there.

D.Migrate to DynamoDB immediately because every relational workload is more expensive.

E.Increase provisioned IOPS permanently so the monthly bill drops.

AnswersA, B, C

Correct. Right-sizing removes waste from the always-on primary instance. If the writer is sized for real load rather than a worst-case assumption, the company pays for less unused compute.

Why this answer

Right-sizing the RDS instance based on actual utilization metrics (e.g., CPU, memory, connections) rather than peak guesses directly reduces compute and memory costs. Since the peak dashboard traffic lasts only three hours, the database can be scaled down for the remaining 21 hours, avoiding over-provisioning. This is a fundamental cost-optimization strategy for RDS without requiring application changes.

Exam trap

The trap here is that candidates assume DynamoDB is always cheaper for any workload, ignoring the need for application rewrites and the relational reporting requirements, while also overlooking that increasing IOPS always raises costs rather than lowering them.

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Multi-Selectmedium

A line-of-business application runs on EC2 instances 24/7 with predictable usage for the next year. The application will stay in the same Region, and the team does not want to manage capacity interruptions. Which two purchase options can reduce cost compared with pure On-Demand pricing? Select two.

Select 2 answers

A.Buy Compute Savings Plans for the expected steady usage.

B.Purchase Standard Reserved Instances for the EC2 fleet.

C.Move the fleet to Spot Instances.

D.Use Dedicated Hosts to reserve physical servers for the application.

E.Stay entirely on On-Demand Instances because they are already the cheapest option.

AnswersA, B

Compute Savings Plans reduce the hourly cost of predictable usage while preserving flexibility across supported compute services. They are a strong fit when the workload is steady and the team wants savings without interruption risk.

Why this answer

Compute Savings Plans (A) offer a flexible discount (up to 66%) in exchange for a 1- or 3-year commitment to a consistent amount of compute usage (measured in $/hour), automatically applying to any EC2 instance family, region, or even AWS Fargate/Lambda. This reduces cost compared to On-Demand while avoiding capacity interruptions, as the commitment covers the predictable steady-state usage. Standard Reserved Instances (B) provide a similar discount (up to 72%) for a specific instance family in a specific region, also with a 1- or 3-year term, and guarantee capacity for the specified AZ if you choose a zonal reservation, ensuring no interruptions.

Exam trap

The trap here is that candidates may think Spot Instances are always cheaper and safe for steady workloads, but they forget the interruption risk, or they may confuse Dedicated Hosts with Reserved Instances as a cost-saving measure, when Dedicated Hosts actually increase cost for physical isolation.

Why the other options are wrong

Spot Instances can be interrupted with a 2-minute notice, which violates the requirement to 'not manage capacity interruptions' for a 24/7 predictable workload.

Dedicated Hosts provide physical servers dedicated for your use, but they are significantly more expensive than On-Demand instances and do not offer cost savings over Reserved Instances or Savings Plans for predictable workloads.

On-Demand Instances are the most expensive option; the question explicitly asks for purchase options that reduce cost compared to pure On-Demand pricing, so staying entirely on On-Demand does not reduce cost.

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MCQmedium

A production log archive runs continuously on EC2 with predictable usage for the next three years. The team wants a discount while retaining some instance-family flexibility. What should they buy?

A.S3 Intelligent-Tiering

B.Dedicated Instances

C.Compute Savings Plan

D.Spot Instances only

AnswerC

Compute Savings Plans provide discounts for a committed spend while allowing flexibility across instance families, sizes, Regions, and compute services.

Why this answer

The Compute Savings Plan (C) is correct because it offers a discount (up to 66%) in exchange for a commitment to a consistent amount of compute usage (measured in $/hour) for a 1- or 3-year term, while allowing flexibility to change instance families, sizes, OS, tenancy, and even regions within EC2, Fargate, and Lambda. This matches the requirement of predictable usage for three years with instance-family flexibility, unlike Reserved Instances which lock to a specific instance family.

Exam trap

The trap here is that candidates often confuse Compute Savings Plans with Reserved Instances, assuming that any long-term discount requires locking into a specific instance family, but Compute Savings Plans provide both the discount and the flexibility to change instance families, which is the key differentiator tested in this question.

How to eliminate wrong answers

Option A is wrong because S3 Intelligent-Tiering is a storage class for objects in Amazon S3 that optimizes costs by moving data between access tiers based on changing access patterns; it has nothing to do with EC2 compute discounts or instance-family flexibility. Option B is wrong because Dedicated Instances are EC2 instances that run on hardware dedicated to a single customer, providing physical isolation but no discount or flexibility benefit; they are a billing/tenancy option, not a discount program. Option D is wrong because Spot Instances only offer significant discounts but are interruptible with a 2-minute termination notice, making them unsuitable for a production log archive that must run continuously for three years without interruption.

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MCQmedium

A media company runs a fleet of EC2 instances using Auto Scaling across multiple instance families (for example, m-series and c-series) in a single region. The business wants to commit to steady usage for one year to reduce cost, but the application team must retain flexibility to switch instance families and scale up/down as demand changes. They need the cost-reduction approach that best matches this flexibility. Which option is the best fit?

A.Purchase Standard Reserved Instances tied to a specific instance family and region, so the application can only run on the selected family.

B.Purchase Compute Savings Plans so the commitment applies regardless of instance family changes within the selected scope.

C.Purchase Spot Instances for all capacity and disable On-Demand fallback to guarantee the lowest cost.

D.Rely only on On-Demand and reduce cost by using a CloudFront-only approach for all dynamic content.

AnswerB

Compute Savings Plans provide discounted pricing in exchange for a 1-year or 3-year commitment, while allowing flexibility across instance families/attributes within the scope (for example, region/account and covered usage). This aligns with Auto Scaling that may shift between instance families while maintaining steady overall compute usage.

Why this answer

Compute Savings Plans provide the most flexibility because they apply to any EC2 instance family (including m-series and c-series) within a region, automatically adjusting to instance family changes and scaling. This matches the requirement to commit to steady usage for one year while retaining the ability to switch families and scale up/down, offering up to 66% savings over On-Demand without locking the application to a specific instance type.

Exam trap

The trap here is that candidates often confuse Reserved Instances (which lock to a specific family) with Savings Plans (which offer family flexibility), leading them to choose Option A despite the requirement for instance family switching.

How to eliminate wrong answers

Option A is wrong because Standard Reserved Instances are tied to a specific instance family (e.g., m5.large) and region, which would prevent the application from switching to a different instance family (e.g., c-series) without incurring additional On-Demand costs or modification fees. Option C is wrong because Spot Instances can be interrupted with a 2-minute warning, making them unsuitable as the sole capacity source for a production workload that requires reliability; disabling On-Demand fallback would risk application downtime during Spot reclaimations. Option D is wrong because CloudFront is a content delivery network that caches static and dynamic content at edge locations, but it does not reduce the cost of running EC2 instances for compute workloads; relying solely on On-Demand without a commitment discount would not achieve the desired cost reduction.

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MCQmedium

A company stores application logs in an S3 bucket. They retain logs for 180 days. Compliance requires that the logs be immutable once written, but the business only reviews logs about once per month. Currently, the team stores everything in S3 Standard, and their monthly S3 bill is too high. They want to reduce storage cost without changing the requirement to keep logs for 180 days. Which lifecycle approach best meets the goal?

A.Use a lifecycle policy to transition objects older than 30 days to S3 Standard-IA, and keep them there until day 180.

B.Use a lifecycle policy to transition objects older than 30 days to S3 Glacier Deep Archive and delete after 30 days.

C.Use a lifecycle policy to transition objects older than 30 days to S3 Intelligent-Tiering with no minimum storage duration.

D.Disable lifecycle management and instead lower costs by deleting objects immediately after they are written.

AnswerA

Logs accessed about monthly match Standard-IA economics and still provide fast retrieval.

Why this answer

It transitions logs older than 30 days to S3 Standard-IA, which offers lower storage costs than S3 Standard while still providing low-latency access for monthly reviews. The lifecycle policy keeps the objects in S3 Standard-IA until day 180, meeting the 180-day retention requirement without incurring the higher cost of S3 Standard for the entire period. S3 Standard-IA has a minimum storage duration of 30 days, which is satisfied by the 30-day transition threshold, and the objects remain immutable as S3 Object Lock is not affected by lifecycle transitions.

Exam trap

The trap here is that candidates may choose S3 Intelligent-Tiering (Option C) thinking it automatically optimizes cost for all access patterns, but for logs accessed only once per month, S3 Standard-IA is more cost-effective because Intelligent-Tiering incurs monitoring and automation overhead and may not move objects to the cheapest tier quickly enough for this specific use case.

Why the other options are wrong

Option B deletes objects after 30 days, failing the requirement to retain logs for 180 days. Additionally, Glacier Deep Archive is not suitable for logs reviewed monthly due to retrieval times of 12-48 hours.

S3 Intelligent-Tiering has a minimum storage duration charge of 30 days for objects moved to the infrequent access tiers, and it does not guarantee immutability; it is designed for unpredictable access patterns, not for reducing costs on logs that are rarely accessed after 30 days but must be retained for 180 days.

Deleting objects immediately violates the compliance requirement that logs be immutable once written and retained for 180 days.

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MCQmedium

A media processing pipeline runs batch jobs on EC2. The jobs can tolerate interruptions because they checkpoint progress to durable storage and can restart. The total workload is variable week-to-week, and there is no need to guarantee capacity at specific times. To reduce compute cost while maintaining correctness, what EC2 purchase option and approach is the best fit?

A.Use EC2 Spot Instances with interruption handling and restart from checkpoints.

B.Use All Upfront Reserved Instances sized for the average weekly workload to minimize cost.

C.Use On-Demand Instances and scale only during business hours to reduce idle time.

D.Use Savings Plans with a fixed hourly commitment to ensure capacity for the entire year.

AnswerA

Spot capacity is typically the lowest-cost EC2 option and can be reclaimed by AWS with interruption notices. Because the workload is explicitly restartable and checkpoints to durable storage, interruptions do not break correctness. Since there is no requirement to reserve capacity, the variable workload aligns well with Spot’s spare-capacity model.

Why this answer

Spot Instances offer up to 90% cost savings compared to On-Demand and are ideal for fault-tolerant, stateless workloads that can checkpoint progress to durable storage. Since the batch jobs can tolerate interruptions and restart from checkpoints, Spot Instances provide the lowest compute cost while maintaining correctness. No other purchase option achieves the same level of cost reduction for this variable, interruption-tolerant workload.

Exam trap

The trap here is that candidates often choose Reserved Instances or Savings Plans thinking they always provide the best cost savings, but they fail to recognize that Spot Instances are significantly cheaper and perfectly suited for fault-tolerant, checkpointed batch workloads that do not require guaranteed capacity.

How to eliminate wrong answers

Option B is wrong because All Upfront Reserved Instances require a 1- or 3-year commitment and are sized for a fixed capacity, which does not match the variable week-to-week workload and would lead to over-provisioning or under-utilization, increasing cost. Option C is wrong because On-Demand Instances are the most expensive per-hour option and scaling only during business hours ignores the fact that the workload can run at any time; this approach does not minimize cost compared to Spot. Option D is wrong because Savings Plans with a fixed hourly commitment lock in a baseline spend and do not provide the deep discounts of Spot Instances; they also guarantee capacity only up to the committed amount, which is unnecessary for a workload that does not need guaranteed capacity.

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MCQmedium

A marketing site stores logs in S3. Logs are queried for 30 days, rarely accessed for one year, and then retained for compliance. What should reduce storage cost? The design must avoid adding custom operational scripts.

A.S3 lifecycle policy that transitions objects to lower-cost storage classes over time

B.Keep all logs in S3 Standard indefinitely

C.Use EBS snapshots for the logs

D.Move all logs immediately to S3 Glacier Deep Archive

AnswerA

Lifecycle rules automate transitions based on age, matching storage cost to access patterns.

Why this answer

S3 Lifecycle policies allow you to automatically transition objects from S3 Standard to lower-cost storage classes like S3 Standard-IA (Infrequent Access) after 30 days, then to S3 Glacier Deep Archive after one year, without custom scripts. This matches the access pattern: frequent queries for 30 days, rare access for a year, then long-term retention for compliance. The policy automates cost reduction by moving data to progressively cheaper storage as access frequency decreases.

Exam trap

The trap here is that candidates might choose Option D, thinking immediate archiving is cheapest, but they overlook the 30-day query requirement and the fact that S3 Glacier Deep Archive has retrieval times of 12+ hours, making it unsuitable for frequent access.

How to eliminate wrong answers

Option B is wrong because keeping all logs in S3 Standard indefinitely incurs the highest storage cost, ignoring the infrequent access and long-term retention requirements. Option C is wrong because EBS snapshots are designed for block-level backups of EC2 volumes, not for storing S3 log data, and would require custom scripts to move logs from S3 to EBS, violating the 'no custom operational scripts' constraint. Option D is wrong because moving all logs immediately to S3 Glacier Deep Archive would make them inaccessible for the first 30 days of frequent queries (retrieval takes 12 hours or more), and the cost of early deletion fees or retrieval requests would outweigh savings.

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Multi-Selecthard

A fleet of test servers is rebuilt every week from AMIs. EBS volumes are often left behind after termination, and the team creates daily snapshots of every volume even when nothing changes. Which three actions most reduce storage cost while preserving recovery options? Select three.

Select 3 answers

A.Use gp3 for new EBS volumes instead of gp2 when similar performance is enough.

B.Automate snapshot creation and deletion with Amazon Data Lifecycle Manager.

C.Move old snapshots to the EBS Snapshot Archive tier once they are rarely restored.

D.Keep unattached volumes around for troubleshooting after instance termination.

E.Raise provisioned IOPS on every volume so snapshot restore time feels faster.

AnswersA, B, C

Correct. gp3 decouples baseline performance from volume size, which commonly lowers cost for workloads that do not need gp2's hidden throughput coupling. It is a practical right-sizing move for many general-purpose volumes.

Why this answer

Gp3 volumes offer a baseline performance that is often sufficient for test server workloads, and they are typically more cost-effective than gp2 volumes when similar performance is adequate. By using gp3, you avoid paying for provisioned IOPS that you do not need, directly reducing storage costs without sacrificing recovery options.

Exam trap

The trap here is that candidates may think keeping unattached volumes is a valid recovery option, but it is more cost-effective to snapshot and delete them, and they may overlook that raising IOPS does not accelerate snapshot restore times.

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MCQeasy

A.Deploy the job on EC2 instances and keep them running continuously for the daily schedule.

B.Use AWS Lambda triggered by a schedule (for example, EventBridge) to run the report at the required time.

C.Run the job in an RDS database using stored procedures scheduled by the database engine.

D.Use an Auto Scaling group with a fixed minimum size of one instance and disable scaling.

AnswerB

Lambda runs on demand and charges for execution time, aligning spend with actual job runtime and reducing ops.

Why this answer

AWS Lambda is the ideal choice because it is a serverless compute service that runs code only when triggered, aligning with the requirement to pay primarily for actual runtime. By using Amazon EventBridge (CloudWatch Events) to invoke the Lambda function on a daily schedule, the team eliminates the need to provision or manage servers, and the job's typical runtime of a few minutes (under 15 minutes, Lambda's maximum execution timeout) fits perfectly within Lambda's constraints.

Exam trap

The trap here is that candidates may overlook Lambda's 15-minute timeout limit and assume any short-duration job is suitable, or they may mistakenly think that RDS stored procedures (Option C) are a cost-effective compute alternative, when in fact they are not designed for general-purpose application logic and still require a running database instance.

How to eliminate wrong answers

Option A is wrong because keeping EC2 instances running continuously incurs costs for idle time, which directly contradicts the goal of paying primarily for actual runtime and reducing operational overhead. Option C is wrong because RDS stored procedures are designed for database-level logic and are not a general-purpose compute solution for running report-generation jobs; they also incur costs for the RDS instance running 24/7 and lack the flexibility of a dedicated compute service. Option D is wrong because an Auto Scaling group with a fixed minimum size of one instance still keeps a server running 24/7, resulting in the same cost and operational overhead as Option A, and does not achieve the goal of paying only for runtime.

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MCQhard

A media processing workflow in private subnets downloads large amounts of data from S3 through a NAT gateway. NAT data processing charges are high. What should the architect use to reduce cost? The architecture review board prefers a managed AWS-native control.

A.S3 Object Lambda

B.AWS Shield Advanced

C.Gateway VPC endpoint for Amazon S3

D.A larger NAT gateway

AnswerC

A gateway endpoint routes S3 traffic privately without NAT gateway data processing charges.

Why this answer

A Gateway VPC endpoint for Amazon S3 allows instances in private subnets to access S3 directly over the AWS network without traversing a NAT gateway, eliminating NAT data processing charges. This is a managed AWS-native control that meets the architecture review board's preference, as it uses AWS PrivateLink and does not require any changes to the S3 bucket or client configuration beyond route table updates.

Exam trap

The trap here is that candidates may confuse Gateway VPC endpoints with Interface VPC endpoints, assuming both incur hourly charges, when in fact Gateway endpoints are free and only incur standard S3 data transfer costs, making them the optimal choice for reducing NAT-related expenses.

How to eliminate wrong answers

Option A is wrong because S3 Object Lambda is used to transform data on the fly during S3 GET requests, not to reduce data transfer costs from S3 to a VPC; it adds processing overhead and does not address NAT gateway charges. Option B is wrong because AWS Shield Advanced is a DDoS protection service that does not reduce data transfer costs or replace the need for a NAT gateway; it is unrelated to S3 access cost optimization. Option D is wrong because a larger NAT gateway would increase, not decrease, costs, as it still incurs per-GB data processing charges for all traffic through it, and does not eliminate the need for NAT traversal.

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