Amazon AWS Certified Solutions Architect - Associate SAA-C03 Bundle

The option Send suitable reads to read replicas and monitor replica lag addresses a separate condition: read queries block writer throughput during reporting windows. Replicas separate reporting reads from write traffic. The actual requirement is a dataset no longer fits the chosen database memory footprint. Recommended corrective action: Right-size instance memory or scale suitable database tier. Cache hit rate and memory pressure affect database latency.

Increase eligible provisioned IOPS or select suitable SSD storage class would help if rDS storage response latency rises because provisioned IOPS is insufficient. Storage IOPS can bottleneck database response time. That is not the symptom described here: a dataset no longer fits the chosen database memory footprint. The matching response is Right-size instance memory or scale suitable database tier, because cache hit rate and memory pressure affect database latency.

Use RDS Proxy and application connection pools solves a different operational problem where thousands of client connections consume memory before query processing. Pooling caps backend connection proliferation. It does not directly address a dataset no longer fits the chosen database memory footprint. The case calls for Right-size instance memory or scale suitable database tier, since cache hit rate and memory pressure affect database latency.

Use supported Redshift workload management and concurrency scaling would help if a data warehouse has unpredictable concurrency and high queue time. Warehouse workload policies allocate query processing capacity. That is not the symptom described here: a large analytical SQL query scans terabytes of unnecessary data. The matching response is Choose appropriate sort keys, table distribution and predicate pruning, because columnar query layout reduces scanned blocks and shuffles.

For the alternative failure analysts need serverless capacity for intermittent SQL analytics, the control Evaluate Redshift Serverless with appropriate base capacity is relevant: serverless warehouses scale resources without a dedicated cluster. Here the evidence instead is a large analytical SQL query scans terabytes of unnecessary data. The selected technical mechanism is Choose appropriate sort keys, table distribution and predicate pruning: columnar query layout reduces scanned blocks and shuffles.

The competing option Use DynamoDB/RDS rather than Redshift as the primary OLTP store would be useful when streaming transactional writes must be served with millisecond per-item latency. Warehouses target analytics rather than per-row transaction serving. The present issue is a large analytical SQL query scans terabytes of unnecessary data; it is more directly addressed by Choose appropriate sort keys, table distribution and predicate pruning. Columnar query layout reduces scanned blocks and shuffles.

For the alternative failure a data warehouse has unpredictable concurrency and high queue time, the control Use supported Redshift workload management and concurrency scaling is relevant: warehouse workload policies allocate query processing capacity. Here the evidence instead is streaming transactional writes must be served with millisecond per-item latency. The selected technical mechanism is Use DynamoDB/RDS rather than Redshift as the primary OLTP store: warehouses target analytics rather than per-row transaction serving.

The competing option Query S3 through Redshift Spectrum or Athena as use case requires would be useful when a report requires repeated queries against fresh S3 datasets without full copying. Federated/lake queries can avoid full ingestion. The present issue is streaming transactional writes must be served with millisecond per-item latency; it is more directly addressed by Use DynamoDB/RDS rather than Redshift as the primary OLTP store. Warehouses target analytics rather than per-row transaction serving.

The option Evaluate Redshift Serverless with appropriate base capacity addresses a separate condition: analysts need serverless capacity for intermittent SQL analytics. Serverless warehouses scale resources without a dedicated cluster. The actual requirement is streaming transactional writes must be served with millisecond per-item latency. Recommended corrective action: Use DynamoDB/RDS rather than Redshift as the primary OLTP store. Warehouses target analytics rather than per-row transaction serving.

The competing option Use DynamoDB/RDS rather than Redshift as the primary OLTP store would be useful when streaming transactional writes must be served with millisecond per-item latency. Warehouses target analytics rather than per-row transaction serving. The present issue is a data warehouse has unpredictable concurrency and high queue time; it is more directly addressed by Use supported Redshift workload management and concurrency scaling. Warehouse workload policies allocate query processing capacity.

The option Choose appropriate sort keys, table distribution and predicate pruning addresses a separate condition: a large analytical SQL query scans terabytes of unnecessary data. Columnar query layout reduces scanned blocks and shuffles. The actual requirement is a data warehouse has unpredictable concurrency and high queue time. Recommended corrective action: Use supported Redshift workload management and concurrency scaling. Warehouse workload policies allocate query processing capacity.

Evaluate Redshift Serverless with appropriate base capacity would help if analysts need serverless capacity for intermittent SQL analytics. Serverless warehouses scale resources without a dedicated cluster. That is not the symptom described here: a data warehouse has unpredictable concurrency and high queue time. The matching response is Use supported Redshift workload management and concurrency scaling, because warehouse workload policies allocate query processing capacity.

The competing option Evaluate Redshift Serverless with appropriate base capacity would be useful when analysts need serverless capacity for intermittent SQL analytics. Serverless warehouses scale resources without a dedicated cluster. The present issue is a report requires repeated queries against fresh S3 datasets without full copying; it is more directly addressed by Query S3 through Redshift Spectrum or Athena as use case requires. Federated/lake queries can avoid full ingestion.

Use DynamoDB/RDS rather than Redshift as the primary OLTP store would help if streaming transactional writes must be served with millisecond per-item latency. Warehouses target analytics rather than per-row transaction serving. That is not the symptom described here: a report requires repeated queries against fresh S3 datasets without full copying. The matching response is Query S3 through Redshift Spectrum or Athena as use case requires, because federated/lake queries can avoid full ingestion.

For the alternative failure a large analytical SQL query scans terabytes of unnecessary data, the control Choose appropriate sort keys, table distribution and predicate pruning is relevant: columnar query layout reduces scanned blocks and shuffles. Here the evidence instead is a report requires repeated queries against fresh S3 datasets without full copying. The selected technical mechanism is Query S3 through Redshift Spectrum or Athena as use case requires: federated/lake queries can avoid full ingestion.

The option Use supported Redshift workload management and concurrency scaling addresses a separate condition: a data warehouse has unpredictable concurrency and high queue time. Warehouse workload policies allocate query processing capacity. The actual requirement is analysts need serverless capacity for intermittent SQL analytics. Recommended corrective action: Evaluate Redshift Serverless with appropriate base capacity. Serverless warehouses scale resources without a dedicated cluster.

Use DynamoDB/RDS rather than Redshift as the primary OLTP store would help if streaming transactional writes must be served with millisecond per-item latency. Warehouses target analytics rather than per-row transaction serving. That is not the symptom described here: analysts need serverless capacity for intermittent SQL analytics. The matching response is Evaluate Redshift Serverless with appropriate base capacity, because serverless warehouses scale resources without a dedicated cluster.

Query S3 through Redshift Spectrum or Athena as use case requires solves a different operational problem where a report requires repeated queries against fresh S3 datasets without full copying. Federated/lake queries can avoid full ingestion. It does not directly address analysts need serverless capacity for intermittent SQL analytics. The case calls for Evaluate Redshift Serverless with appropriate base capacity, since serverless warehouses scale resources without a dedicated cluster.

Deploy supported Aurora Global Database or cross-region replicas as appropriate would help if a regional outage requires a geographically separate Aurora read copy. Regional replication shortens cross-region recovery setup. That is not the symptom described here: an existing Aurora cluster has replicas but the least suitable replica is ranked first for writer promotion. The matching response is Set failover priority tiers on Aurora Replicas to favor the approved recovery target, because aurora failover uses replica priorities when selecting promotion candidates.

Add RDS Proxy and use connection pooling solves a different operational problem where a serverless app's bursty connection creation overwhelms Aurora. Proxy reduces backend connection churn. It does not directly address an existing Aurora cluster has replicas but the least suitable replica is ranked first for writer promotion. The case calls for Set failover priority tiers on Aurora Replicas to favor the approved recovery target, since aurora failover uses replica priorities when selecting promotion candidates.

The competing option Use the Aurora cluster reader endpoint would be useful when an app requires read balancing across Aurora replicas. Reader endpoints route connections to replicas. The present issue is an existing Aurora cluster has replicas but the least suitable replica is ranked first for writer promotion; it is more directly addressed by Set failover priority tiers on Aurora Replicas to favor the approved recovery target. Aurora failover uses replica priorities when selecting promotion candidates.

For the alternative failure an app requires write consistency and mistakenly sends mutations to reader endpoint, the control Direct transactional writes to the Aurora writer endpoint is relevant: aurora readers do not accept ordinary writes. Here the evidence instead is an app requires read balancing across Aurora replicas. The selected technical mechanism is Use the Aurora cluster reader endpoint: reader endpoints route connections to replicas.

Add RDS Proxy and use connection pooling solves a different operational problem where a serverless app's bursty connection creation overwhelms Aurora. Proxy reduces backend connection churn. It does not directly address an app requires read balancing across Aurora replicas. The case calls for Use the Aurora cluster reader endpoint, since reader endpoints route connections to replicas.

The competing option Set failover priority tiers on Aurora Replicas to favor the approved recovery target would be useful when an existing Aurora cluster has replicas but the least suitable replica is ranked first for writer promotion. Aurora failover uses replica priorities when selecting promotion candidates. The present issue is an app requires read balancing across Aurora replicas; it is more directly addressed by Use the Aurora cluster reader endpoint. Reader endpoints route connections to replicas.

The competing option Deploy supported Aurora Global Database or cross-region replicas as appropriate would be useful when a regional outage requires a geographically separate Aurora read copy. Regional replication shortens cross-region recovery setup. The present issue is an app requires write consistency and mistakenly sends mutations to reader endpoint; it is more directly addressed by Direct transactional writes to the Aurora writer endpoint. Aurora readers do not accept ordinary writes.

The option Add RDS Proxy and use connection pooling addresses a separate condition: a serverless app's bursty connection creation overwhelms Aurora. Proxy reduces backend connection churn. The actual requirement is an app requires write consistency and mistakenly sends mutations to reader endpoint. Recommended corrective action: Direct transactional writes to the Aurora writer endpoint. Aurora readers do not accept ordinary writes.

Set failover priority tiers on Aurora Replicas to favor the approved recovery target would help if an existing Aurora cluster has replicas but the least suitable replica is ranked first for writer promotion. Aurora failover uses replica priorities when selecting promotion candidates. That is not the symptom described here: an app requires write consistency and mistakenly sends mutations to reader endpoint. The matching response is Direct transactional writes to the Aurora writer endpoint, because aurora readers do not accept ordinary writes.

The option Deploy supported Aurora Global Database or cross-region replicas as appropriate addresses a separate condition: a regional outage requires a geographically separate Aurora read copy. Regional replication shortens cross-region recovery setup. The actual requirement is a serverless app's bursty connection creation overwhelms Aurora. Recommended corrective action: Add RDS Proxy and use connection pooling. Proxy reduces backend connection churn.

Set failover priority tiers on Aurora Replicas to favor the approved recovery target would help if an existing Aurora cluster has replicas but the least suitable replica is ranked first for writer promotion. Aurora failover uses replica priorities when selecting promotion candidates. That is not the symptom described here: a serverless app's bursty connection creation overwhelms Aurora. The matching response is Add RDS Proxy and use connection pooling, because proxy reduces backend connection churn.

For the alternative failure an app requires read balancing across Aurora replicas, the control Use the Aurora cluster reader endpoint is relevant: reader endpoints route connections to replicas. Here the evidence instead is a serverless app's bursty connection creation overwhelms Aurora. The selected technical mechanism is Add RDS Proxy and use connection pooling: proxy reduces backend connection churn.

The option Set failover priority tiers on Aurora Replicas to favor the approved recovery target addresses a separate condition: an existing Aurora cluster has replicas but the least suitable replica is ranked first for writer promotion. Aurora failover uses replica priorities when selecting promotion candidates. The actual requirement is a regional outage requires a geographically separate Aurora read copy. Recommended corrective action: Deploy supported Aurora Global Database or cross-region replicas as appropriate. Regional replication shortens cross-region recovery setup.

For the alternative failure an app requires write consistency and mistakenly sends mutations to reader endpoint, the control Direct transactional writes to the Aurora writer endpoint is relevant: aurora readers do not accept ordinary writes. Here the evidence instead is a regional outage requires a geographically separate Aurora read copy. The selected technical mechanism is Deploy supported Aurora Global Database or cross-region replicas as appropriate: regional replication shortens cross-region recovery setup.

Use the Aurora cluster reader endpoint solves a different operational problem where an app requires read balancing across Aurora replicas. Reader endpoints route connections to replicas. It does not directly address a regional outage requires a geographically separate Aurora read copy. The case calls for Deploy supported Aurora Global Database or cross-region replicas as appropriate, since regional replication shortens cross-region recovery setup.