Question 370
A development team has 60 monthly Amazon EBS snapshots from one retired volume. Its finance model predicts that deleting the oldest 50 snapshots will save the entire sum of their apparent logical volume sizes. Compliance permits deletion but requires the newest 10 recovery points to remain restorable. Which cost calculation and cleanup method is technically defensible?
- Multiply the full provisioned volume size by fifty and promise that deleting those snapshots will remove those exact storage bytes regardless of later references.
- Delete the newest ten snapshots first and rely on older snapshots to recover each most recent write generation.
- Copy all retained snapshots to another Region while leaving originals intact, then count the copy as immediate elimination of source-region snapshot charges.
- Identify obsolete snapshots and their exclusively referenced changed blocks, delete only approved recovery points, and measure actual billed storage after retained snapshots continue referencing common blocks.
Explanation
Correct Answer
D:EBS snapshot deletion removes blocks exclusively referenced by deleted snapshots, while shared blocks needed by retained snapshots remain and may be billed against those later snapshots.
Incorrect Answers
A:EBS snapshots are incremental and share underlying block data; deleting an earlier snapshot does not remove blocks that later retained snapshots still reference.
B:Removing the newest required recovery points violates the retention objective; incremental snapshots remain independently restorable while retained, not interchangeable by age.
C:Cross-Region copies create additional stored recovery data; they do not erase original snapshot blocks until actual eligible deletion and reference accounting occur.
Question 371
A container-based API has only a few brief requests each day, but the team pays for three always-on EC2 servers solely to keep the HTTP service available. Each request is stateless and finishes within Lambda runtime limits. Which modernization may reduce idle compute cost?
- Replace the EC2 hosts with an ECS Fargate service configured to retain three always-running tasks at all hours.
- Move the service to a larger always-running EC2 Auto Scaling baseline and claim it has pay-per-request economics.
- Enable provisioned concurrency on a Lambda implementation but keep all original EC2 web servers operating 24 hours a day.
- Evaluate API Gateway with Lambda, sizing request charges and cold-start requirements against actual traffic.
Explanation
Correct Answer
D:Event-driven compute charges can eliminate continuously running application servers when request frequency is low and runtime semantics fit.
Incorrect Answers
A:Removing host administration does not eliminate idle compute charges when tasks are deliberately kept running despite only a few requests per day.
B:Fixed EC2 minimum capacity still accrues hourly costs even for zero incoming requests, which is the measured waste.
C:Preinitialized Lambda capacity can add charges; it does not remove the principal idle EC2 cost if the old server fleet remains running.
Question 372
A small-object S3 archive contains millions of 8-KB records with unpredictable and brief access. Finance proposes placing every item into Intelligent-Tiering, but the team has not considered monitoring thresholds or minimum object sizes. What analysis should be performed?
- Delete all old records before checking retention policy because small objects have no compliance obligations.
- Check that 8-KB objects cannot auto-tier in Intelligent-Tiering and are billed at the Frequent Access rate without monitoring fees; compare size-appropriate alternatives before changing classes.
- Assume each 8-KB object receives the same automatic colder-tier transitions and per-object monitoring fee as objects above 128 KB.
- Select Deep Archive for the entire collection without confirming whether its asynchronous restoration time fits the unpredictable retrieval deadlines.
Explanation
Correct Answer
B:S3 objects smaller than 128 KB can be stored in Intelligent-Tiering but are not monitored or automatically tiered and do not incur the monitoring/automation fee. Consequently the proposed class does not yield automatic cold-tier savings on these 8-KB items.
Incorrect Answers
A:Retention obligations are independent of object size, and premature deletion can cause data loss and noncompliance.
C:AWS does not auto-tier or charge the monitoring fee for objects under 128 KB, so neither the projected cold storage reduction nor monitoring assumption is sound.
D:Glacier Deep Archive might save storage charges if access tolerates restore latency, but the scenario has not established this precondition.
Question 373
A media publisher already has a healthy CloudFront cache hit ratio, so origin request amplification is not the remaining cost issue. Delivery from the most expensive edge regions drives the bill, and the business accepts modestly higher latency for a small set of viewers outside its priority markets. Which CloudFront distribution setting should the architect evaluate?
- Enable S3 Transfer Acceleration for writes to the origin bucket and treat its upload acceleration as control over the CloudFront viewer edge price class.
- Disable every edge cache so S3 origin requests take the place of delivery from expensive edge regions.
- Evaluate a CloudFront Price Class that excludes less essential high-cost edge regions while testing latency and availability for the affected viewers.
- Enable CloudFront Origin Shield to reduce repeated origin-fetch requests while keeping the same worldwide edge pricing footprint.
Explanation
Correct Answer
C:CloudFront Price Class can limit the distribution edge regions by cost, trading some end-user latency for lower price while preserving cache behavior.
Incorrect Answers
A:Transfer Acceleration addresses accelerated uploads to S3; it does not exclude high-priced CloudFront edge geographies.
B:Disabling caching increases origin load and fails to address the measured geographic edge delivery expense.
D:Origin Shield may reduce origin demand, but the scenario already has strong caching and identifies viewer edge-region transfer rates as the cost driver.
Question 374
A company performs frequent multipart uploads to S3, but many clients abandon an upload after creating several parts. Storage analytics reports growing charges for incomplete multipart upload parts that are not visible as completed objects. What lifecycle control reduces this waste?
- Increase the multipart part count for failed clients and never call AbortMultipartUpload.
- Enable Storage Lens reports on incomplete multipart parts and keep monitoring indefinitely without configuring abort cleanup.
- Configure an S3 lifecycle AbortIncompleteMultipartUpload action after an approved number of days and fix abandoned upload cleanup.
- Add only a completed-object Expiration action on a different prefix and assume it also aborts pending multipart upload IDs.
Explanation
Correct Answer
C:Incomplete multipart parts can continue incurring storage charges; aborting stale uploads removes them without deleting completed objects.
Incorrect Answers
A:More abandoned parts increase, rather than eliminate, billed incomplete upload data.
B:Storage Lens can reveal incomplete-upload waste but collecting metrics alone does not release the stored parts.
D:S3 object expiration and AbortIncompleteMultipartUpload are distinct lifecycle operations; only the latter targets unfinished uploads.
Question 375
A batch processing application runs a fixed, predictable number of AWS Glue jobs every night. DPU allocation remains high throughout each job even though most transformations use little memory and CPU outside peak stages. Which managed scaling feature should be evaluated?
- Enable Glue job bookmarks only and keep the same maximum DPU allocation throughout each step of every nightly run.
- Configure Glue job queuing to wait for capacity while leaving each running job at its fixed excessive maximum worker count.
- Evaluate AWS Glue Auto Scaling for supported job versions and measure actual DPU consumption and job duration.
- Choose one lower fixed DPU count for every phase without evaluating whether the peak transformations still meet completion and memory requirements.
Explanation
Correct Answer
C:Glue Auto Scaling can allocate supported worker capacity with job demand rather than maintaining an unnecessarily fixed maximum.
Incorrect Answers
A:Bookmarks can skip previously processed source state, but do not directly adapt allocated worker capacity to fluctuating intra-job demand.
B:Queueing affects when jobs start, not overprovisioned DPU usage inside an active job.
D:A smaller fixed count can save money but risks failing peak work; Auto Scaling tunes worker capacity as demand varies.
Question 376
A compute-intensive EMR on EC2 workflow retries individual tasks and uses durable S3 inputs and outputs. The core driver nodes require stable On-Demand capacity, but task nodes can be interrupted. What blended purchase strategy could lower cost?
- Use a stable On-Demand core where necessary and diversified Spot task capacity with managed scaling and interruption-aware processing.
- Place the only HDFS master and all irreplaceable state on Spot task nodes with no backup or recovery plan.
- Run the EMR primary and core nodes solely on Spot, without durable state protections, because task retrying guarantees critical control-plane availability.
- Buy a dedicated EC2 On-Demand Capacity Reservation for the entire transient task fleet rather than exploiting interruptible, retryable task work.
Explanation
Correct Answer
A:EMR task groups can use interruptible capacity for retryable work while critical cluster control remains on reliable capacity.
Incorrect Answers
B:Spot interruptions can remove at-risk capacity, so nonrecoverable cluster state should not depend on it.
C:Interruptible task capacity is different from crucial master/core placement; losing essential cluster state or leader capacity may disrupt the entire job.
D:Capacity Reservations reserve placement without directly providing the price advantage of diversified Spot capacity for disposable tasks.
Question 377
An S3 data lake uses Athena. Finance finds high per-query scan costs because users repeatedly run SELECT * against raw CSV data containing hundreds of unnecessary columns. Which data and query design change most directly reduces scan-based charges?
- Increase Athena query timeout and continue scanning every CSV field and partition on every query.
- Continue scanning the same wide CSV documents but create additional Glue partitions that are never included in query predicates.
- Run AWS Glue crawlers more often to discover the same CSV schema while leaving query projections and source file layout unchanged.
- Store optimized columnar Parquet files, compact small objects and use selective columns and partition predicates in Athena queries.
Explanation
Correct Answer
D:Athena charges are influenced by data scanned; compressed columnar formats and pruning reduce bytes read for selective analytics.
Incorrect Answers
A:Longer allowed runtime does not reduce unnecessary scan bytes or the corresponding charges.
B:Catalog partitions alone do not cut bytes read when users still SELECT * across unpruned, column-heavy CSV datasets.
C:Crawlers improve metadata discovery, not data scan economics when the input format and broad column selection remain the same.
Question 378
A startup runs DynamoDB workloads with stable, predictable request rates and has already used on-demand capacity during product launch. Financial models show provisioned autoscaled capacity could reduce cost without unacceptable throttling. What decision should it evaluate?
- Switch to fixed minimal provisioned capacity and disable autoscaling regardless of peak requests.
- Move live DynamoDB transaction records to Glacier Instant Retrieval object storage to get provisioned database capacity discounts.
- Compare measured on-demand request charges with provisioned capacity plus autoscaling policies and safe minimum and maximum limits.
- Assume the initial on-demand mode is always cheapest even after usage becomes stable and provisioned auto scaling is shown to be safe.
Explanation
Correct Answer
C:Known baseline demand can make provisioned capacity more economical, but burst handling and throttling need a realistic comparison.
Incorrect Answers
A:Underprovisioning can create throttling and violate throughput requirements.
B:An S3 archive class is not a DynamoDB read/write capacity billing mode and cannot replace transactional table operations.
D:The billing comparison changes with a predictable baseline; declining to evaluate provisioned autoscaling would ignore known savings evidence.
Question 379
A company logs detailed debug output from 900 Lambda functions. CloudWatch Logs charges dominate monitoring spend, and most debug events have no operational or regulatory value after 14 days. Which retention control should the team apply?
- Leave every log group at infinite retention and assume old events are automatically free after the first week.
- Disable all audit/security logs, including those required for incident response, to minimize monitoring cost.
- Purchase a Compute Savings Plan while retaining every debug log forever and expect it to reduce CloudWatch Logs storage and ingestion billing.
- Set appropriate CloudWatch Logs retention policies by log-group purpose and compliance needs, and reduce unnecessary debug volume at the source.
Explanation
Correct Answer
D:Reducing retained low-value logs and excessive ingestion directly targets two measured CloudWatch Logs cost drivers.
Incorrect Answers
A:Unbounded retention can continue accruing storage charges for unnecessary historical logs.
B:Indiscriminate deletion violates stated evidence requirements; retention should reflect data purpose.
C:Compute Savings Plans apply to eligible compute services, not the separate Log ingestion/retention costs identified by the review.
Question 380
A regulated application emits 80 TB of low-urgency diagnostic logs each year. Only an occasional forensic investigation queries the logs, and the workload does not use metric filters, subscriptions or other features unavailable in the cheaper CloudWatch Logs class. The next version can create fresh log groups, but changing existing group class in place is not supported. Which ingest-cost optimization should be tested?
- Switch the existing Standard log group in place to Infrequent Access without recreating it; AWS transparently changes the class when a tag is edited.
- Stop collecting the logs and assume auditors can reconstruct all past event details solely from Cost Explorer billing entries.
- Use CloudWatch Logs Infrequent Access class for new compatible log groups, comparing lower ingestion rates and feature limits while keeping required retention.
- Apply CloudWatch Logs sensitive-data masking to existing Standard log groups and assume masking converts billed ingestion to Infrequent Access pricing.
Explanation
Correct Answer
C:Infrequent Access has lower per-GB ingestion pricing for supported ad hoc log analysis; new groups are needed and feature gaps must be verified.
Incorrect Answers
A:Log group class is chosen at creation time and is immutable, so existing Standard groups cannot be reclassified in place.
B:Dropping required log data fails the stated audit purpose, and billing records are not a replacement for diagnostic event content.
D:Data protection helps privacy but does not change the immutable log class or its ingested GB charges.
AWS Certified Solutions Architect - Professional SAP-C02 Practice Tests