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Amazon AWS Certified Machine Learning Engineer - Associate MLA-C01 Practice Test 4
Question 30
After a planned change, the release team needs evidence of the expected outcome. The change is: Ingest events into Kinesis Data Streams with sufficient shards and retention for consumer replay. This relates to a situation where a fraud team needs to replay an ordered stream of card authorization events for a new consumer without asking the card processor to send the original events again. What outcome should the team look for if that change succeeds?
- Existing Kafka producers can send events to a managed Kafka infrastructure.
- New qualifying source objects trigger the downstream ingestion check automatically.
- Workers share a consistent POSIX file namespace throughout processing.
- Independent consumers can read retained stream records and reprocess events during the retention period.
Explanation
Correct Answer
D:This is the expected observable result: Independent consumers can read retained stream records and reprocess events during the retention period. It follows when engineers ingest events into Kinesis Data Streams with sufficient shards and retention for consumer replay. The team must still consider the limitation: Retention and shard capacity are bounded; a delivery-only destination is not a substitute for replayable streams.
Incorrect Answers
A:That result concerns an enterprise already uses Apache Kafka producers and requires managed Kafka brokers for an AWS-based ML event pipeline without rewriting those clients for Kinesis. It would not demonstrate that independent consumers can read retained stream records and reprocess events during the retention period.
B:That result concerns a finance lake receives one S3 object per nightly batch and wants ingestion validation to start when the specific input prefix receives a complete new object. It would not demonstrate that independent consumers can read retained stream records and reprocess events during the retention period.
C:That result concerns several SageMaker training workers require concurrent access to a POSIX directory tree containing many small training files instead of manually syncing copies into every container. It would not demonstrate that independent consumers can read retained stream records and reprocess events during the retention period.
Question 31
An implementation review needs the operational result of this step: Configure an Amazon Data Firehose stream with an S3 destination, suitable buffering, compression, and failure handling. This relates to a situation where a telemetry pipeline receives continuously arriving application events and must land compressed records in S3 without a custom long-running consumer service. What outcome should the team look for if that change succeeds?
- Workers share a consistent POSIX file namespace throughout processing.
- New qualifying source objects trigger the downstream ingestion check automatically.
- Buffered streaming records reach the target data lake as durable objects.
- Updated item attributes can flow into downstream feature processing with lower polling overhead.
Explanation
Correct Answer
C:This is the expected observable result: Buffered streaming records reach the target data lake as durable objects. It follows when engineers configure an Amazon Data Firehose stream with an S3 destination, suitable buffering, compression, and failure handling. The team must still consider the limitation: Firehose buffering adds latency and does not provide arbitrary replay of records already delivered.
Incorrect Answers
A:That result concerns several SageMaker training workers require concurrent access to a POSIX directory tree containing many small training files instead of manually syncing copies into every container. It would not demonstrate that buffered streaming records reach the target data lake as durable objects.
B:That result concerns a finance lake receives one S3 object per nightly batch and wants ingestion validation to start when the specific input prefix receives a complete new object. It would not demonstrate that buffered streaming records reach the target data lake as durable objects.
D:That result concerns a merchant needs downstream features updated when items in a DynamoDB inventory table change, without polling and scanning the entire table each minute. It would not demonstrate that buffered streaming records reach the target data lake as durable objects.
Question 32
A postdeployment test assesses this specific remediation: Enable S3 Transfer Acceleration for the eligible bucket and use its accelerated upload endpoint. This relates to a situation where a research partner uploads multi-gigabyte labeled video datasets to a distant AWS Region and the normal S3 transfer route underperforms. What outcome should the team look for if that change succeeds?
- The training host receives predictable block-storage performance within provisioned limits.
- Eligible remote uploads can use the optimized AWS edge network path to reach the bucket.
- Workers share a consistent POSIX file namespace throughout processing.
- Updated item attributes can flow into downstream feature processing with lower polling overhead.
Explanation
Correct Answer
B:This is the expected observable result: Eligible remote uploads can use the optimized AWS edge network path to reach the bucket. It follows when engineers enable S3 Transfer Acceleration for the eligible bucket and use its accelerated upload endpoint. The team must still consider the limitation: Transfer Acceleration has additional charges and is not a universal speedup for clients near the destination Region.
Incorrect Answers
A:That result concerns a GPU training instance repeatedly reads a random-access local index and standard EBS storage saturates on small I/O requests during preprocessing. It would not demonstrate that eligible remote uploads can use the optimized AWS edge network path to reach the bucket.
C:That result concerns several SageMaker training workers require concurrent access to a POSIX directory tree containing many small training files instead of manually syncing copies into every container. It would not demonstrate that eligible remote uploads can use the optimized AWS edge network path to reach the bucket.
D:That result concerns a merchant needs downstream features updated when items in a DynamoDB inventory table change, without polling and scanning the entire table each minute. It would not demonstrate that eligible remote uploads can use the optimized AWS edge network path to reach the bucket.
Question 33
After a planned change, the release team needs evidence of the expected outcome. The change is: Attach a supported EFS filesystem and mount the authorized shared directory in the training environment. This relates to a situation where several SageMaker training workers require concurrent access to a POSIX directory tree containing many small training files instead of manually syncing copies into every container. What outcome should the team look for if that change succeeds?
- Workers share a consistent POSIX file namespace throughout processing.
- Column pruning and compression reduce input read and query cost for the selected fields.
- New qualifying source objects trigger the downstream ingestion check automatically.
- Completed parts can be retried independently before finalizing the large object.
Explanation
Correct Answer
A:This is the expected observable result: Workers share a consistent POSIX file namespace throughout processing. It follows when engineers attach a supported EFS filesystem and mount the authorized shared directory in the training environment. The team must still consider the limitation: EFS throughput and mount access configuration must be sized and restricted for the actual workload.
Incorrect Answers
B:That result concerns an insurance company trains on years of wide structured claims data in Amazon S3, but analysts repeatedly scan only six columns and spend too much time reading CSV files. It would not demonstrate that workers share a consistent POSIX file namespace throughout processing.
C:That result concerns a finance lake receives one S3 object per nightly batch and wants ingestion validation to start when the specific input prefix receives a complete new object. It would not demonstrate that workers share a consistent POSIX file namespace throughout processing.
D:That result concerns a remote sensor network periodically uploads 30 GB compressed datasets, and a failed connection currently forces a full restart of each upload. It would not demonstrate that workers share a consistent POSIX file namespace throughout processing.
Question 34
An implementation review needs the operational result of this step: Use Amazon FSx for Lustre with an appropriate S3 data repository association and training access configuration. This relates to a situation where a vision team repeatedly reads millions of images from S3 during high-throughput distributed training and requires filesystem semantics with parallel read performance. What outcome should the team look for if that change succeeds?
- New qualifying source objects trigger the downstream ingestion check automatically.
- Updated item attributes can flow into downstream feature processing with lower polling overhead.
- Completed parts can be retried independently before finalizing the large object.
- Distributed workers can read cached or staged training files through a high-performance shared filesystem.
Explanation
Correct Answer
D:This is the expected observable result: Distributed workers can read cached or staged training files through a high-performance shared filesystem. It follows when engineers use Amazon FSx for Lustre with an appropriate S3 data repository association and training access configuration. The team must still consider the limitation: FSx for Lustre incurs filesystem capacity costs and must be managed after the training window.
Incorrect Answers
A:That result concerns a finance lake receives one S3 object per nightly batch and wants ingestion validation to start when the specific input prefix receives a complete new object. It would not demonstrate that distributed workers can read cached or staged training files through a high-performance shared filesystem.
B:That result concerns a merchant needs downstream features updated when items in a DynamoDB inventory table change, without polling and scanning the entire table each minute. It would not demonstrate that distributed workers can read cached or staged training files through a high-performance shared filesystem.
C:That result concerns a remote sensor network periodically uploads 30 GB compressed datasets, and a failed connection currently forces a full restart of each upload. It would not demonstrate that distributed workers can read cached or staged training files through a high-performance shared filesystem.
Question 35
A postdeployment test assesses this specific remediation: Enable S3 Versioning and record the exact source object version IDs in the experiment manifest. This relates to a situation where a data scientist discovers that yesterday's feature extraction changed the raw CSV underlying a model run and must recover the exact original S3 object revision. What outcome should the team look for if that change succeeds?
- Existing Kafka producers can send events to a managed Kafka infrastructure.
- A later experiment can retrieve the same immutable historical object revisions where retained.
- Workers share a consistent POSIX file namespace throughout processing.
- New qualifying source objects trigger the downstream ingestion check automatically.
Explanation
Correct Answer
B:This is the expected observable result: A later experiment can retrieve the same immutable historical object revisions where retained. It follows when engineers enable S3 Versioning and record the exact source object version IDs in the experiment manifest. The team must still consider the limitation: Versioning does not create a complete data catalog and lifecycle or delete-marker handling must be managed.
Incorrect Answers
A:That result concerns an enterprise already uses Apache Kafka producers and requires managed Kafka brokers for an AWS-based ML event pipeline without rewriting those clients for Kinesis. It would not demonstrate that a later experiment can retrieve the same immutable historical object revisions where retained.
C:That result concerns several SageMaker training workers require concurrent access to a POSIX directory tree containing many small training files instead of manually syncing copies into every container. It would not demonstrate that a later experiment can retrieve the same immutable historical object revisions where retained.
D:That result concerns a finance lake receives one S3 object per nightly batch and wants ingestion validation to start when the specific input prefix receives a complete new object. It would not demonstrate that a later experiment can retrieve the same immutable historical object revisions where retained.
Question 36
After a planned change, the release team needs evidence of the expected outcome. The change is: Configure an AWS Glue ETL job with an approved JDBC connection and S3 output dataset. This relates to a situation where a team needs a scheduled extraction of selected records from Amazon RDS into S3 for modeling while applying typed transformations and recording job history. What outcome should the team look for if that change succeeds?
- Relational records enter the governed data lake in a repeatable transformation pipeline.
- Updated item attributes can flow into downstream feature processing with lower polling overhead.
- Column pruning and compression reduce input read and query cost for the selected fields.
- Completed parts can be retried independently before finalizing the large object.
Explanation
Correct Answer
A:This is the expected observable result: Relational records enter the governed data lake in a repeatable transformation pipeline. It follows when engineers configure an AWS Glue ETL job with an approved JDBC connection and S3 output dataset. The team must still consider the limitation: Database credentials, VPC connectivity, and read load require explicit protections.
Incorrect Answers
B:That result concerns a merchant needs downstream features updated when items in a DynamoDB inventory table change, without polling and scanning the entire table each minute. It would not demonstrate that relational records enter the governed data lake in a repeatable transformation pipeline.
C:That result concerns an insurance company trains on years of wide structured claims data in Amazon S3, but analysts repeatedly scan only six columns and spend too much time reading CSV files. It would not demonstrate that relational records enter the governed data lake in a repeatable transformation pipeline.
D:That result concerns a remote sensor network periodically uploads 30 GB compressed datasets, and a failed connection currently forces a full restart of each upload. It would not demonstrate that relational records enter the governed data lake in a repeatable transformation pipeline.
Question 37
An implementation review needs the operational result of this step: Enable DynamoDB Streams and consume the relevant change records with an authorized processing integration. This relates to a situation where a merchant needs downstream features updated when items in a DynamoDB inventory table change, without polling and scanning the entire table each minute. What outcome should the team look for if that change succeeds?
- Updated item attributes can flow into downstream feature processing with lower polling overhead.
- Column pruning and compression reduce input read and query cost for the selected fields.
- Eligible remote uploads can use the optimized AWS edge network path to reach the bucket.
- Existing Kafka producers can send events to a managed Kafka infrastructure.
Explanation
Correct Answer
A:This is the expected observable result: Updated item attributes can flow into downstream feature processing with lower polling overhead. It follows when engineers enable DynamoDB Streams and consume the relevant change records with an authorized processing integration. The team must still consider the limitation: DynamoDB Streams has finite retention and consumers must handle retries and duplicate delivery.
Incorrect Answers
B:That result concerns an insurance company trains on years of wide structured claims data in Amazon S3, but analysts repeatedly scan only six columns and spend too much time reading CSV files. It would not demonstrate that updated item attributes can flow into downstream feature processing with lower polling overhead.
C:That result concerns a research partner uploads multi-gigabyte labeled video datasets to a distant AWS Region and the normal S3 transfer route underperforms. It would not demonstrate that updated item attributes can flow into downstream feature processing with lower polling overhead.
D:That result concerns an enterprise already uses Apache Kafka producers and requires managed Kafka brokers for an AWS-based ML event pipeline without rewriting those clients for Kinesis. It would not demonstrate that updated item attributes can flow into downstream feature processing with lower polling overhead.
Question 38
A postdeployment test assesses this specific remediation: Deploy appropriately configured Amazon MSK with secure broker access and existing Kafka-topic conventions. This relates to a situation where an enterprise already uses Apache Kafka producers and requires managed Kafka brokers for an AWS-based ML event pipeline without rewriting those clients for Kinesis. What outcome should the team look for if that change succeeds?
- Existing Kafka producers can send events to a managed Kafka infrastructure.
- The training host receives predictable block-storage performance within provisioned limits.
- A later experiment can retrieve the same immutable historical object revisions where retained.
- Updated item attributes can flow into downstream feature processing with lower polling overhead.
Explanation
Correct Answer
A:This is the expected observable result: Existing Kafka producers can send events to a managed Kafka infrastructure. It follows when engineers deploy appropriately configured Amazon MSK with secure broker access and existing Kafka-topic conventions. The team must still consider the limitation: MSK brokers still require capacity, partition, authentication, and consumer lag management.
Incorrect Answers
B:That result concerns a GPU training instance repeatedly reads a random-access local index and standard EBS storage saturates on small I/O requests during preprocessing. It would not demonstrate that existing Kafka producers can send events to a managed Kafka infrastructure.
C:That result concerns a data scientist discovers that yesterday's feature extraction changed the raw CSV underlying a model run and must recover the exact original S3 object revision. It would not demonstrate that existing Kafka producers can send events to a managed Kafka infrastructure.
D:That result concerns a merchant needs downstream features updated when items in a DynamoDB inventory table change, without polling and scanning the entire table each minute. It would not demonstrate that existing Kafka producers can send events to a managed Kafka infrastructure.
Question 39
After a planned change, the release team needs evidence of the expected outcome. The change is: Configure SageMaker Feature Store with appropriate online and offline storage for shared feature groups. This relates to a situation where an online fraud API needs current user feature values in milliseconds, while model training needs historical feature records from the same definitions. What outcome should the team look for if that change succeeds?
- Workers share a consistent POSIX file namespace throughout processing.
- Online inference can retrieve low-latency values while training reads durable feature histories.
- Updated item attributes can flow into downstream feature processing with lower polling overhead.
- The training host receives predictable block-storage performance within provisioned limits.
Explanation
Correct Answer
B:This is the expected observable result: Online inference can retrieve low-latency values while training reads durable feature histories. It follows when engineers configure SageMaker Feature Store with appropriate online and offline storage for shared feature groups. The team must still consider the limitation: Point-in-time correctness requires timestamp-aware joins; online latest values must not leak into past training examples.
Incorrect Answers
A:That result concerns several SageMaker training workers require concurrent access to a POSIX directory tree containing many small training files instead of manually syncing copies into every container. It would not demonstrate that online inference can retrieve low-latency values while training reads durable feature histories.
C:That result concerns a merchant needs downstream features updated when items in a DynamoDB inventory table change, without polling and scanning the entire table each minute. It would not demonstrate that online inference can retrieve low-latency values while training reads durable feature histories.
D:That result concerns a GPU training instance repeatedly reads a random-access local index and standard EBS storage saturates on small I/O requests during preprocessing. It would not demonstrate that online inference can retrieve low-latency values while training reads durable feature histories.
Question 40
An implementation review needs the operational result of this step: Use S3 multipart upload with checkpointed part identifiers and abort rules for abandoned attempts. This relates to a situation where a remote sensor network periodically uploads 30 GB compressed datasets, and a failed connection currently forces a full restart of each upload. What outcome should the team look for if that change succeeds?
- Completed parts can be retried independently before finalizing the large object.
- Relational records enter the governed data lake in a repeatable transformation pipeline.
- Existing Kafka producers can send events to a managed Kafka infrastructure.
- Workers share a consistent POSIX file namespace throughout processing.
Explanation
Correct Answer
A:This is the expected observable result: Completed parts can be retried independently before finalizing the large object. It follows when engineers use S3 multipart upload with checkpointed part identifiers and abort rules for abandoned attempts. The team must still consider the limitation: Incomplete multipart parts can incur storage costs until completed or explicitly cleaned up.
Incorrect Answers
B:That result concerns a team needs a scheduled extraction of selected records from Amazon RDS into S3 for modeling while applying typed transformations and recording job history. It would not demonstrate that completed parts can be retried independently before finalizing the large object.
C:That result concerns an enterprise already uses Apache Kafka producers and requires managed Kafka brokers for an AWS-based ML event pipeline without rewriting those clients for Kinesis. It would not demonstrate that completed parts can be retried independently before finalizing the large object.
D:That result concerns several SageMaker training workers require concurrent access to a POSIX directory tree containing many small training files instead of manually syncing copies into every container. It would not demonstrate that completed parts can be retried independently before finalizing the large object.
AWS Certified Machine Learning Engineer - Associate MLA-C01 Practice Tests
