Amazon AWS SAA-C03 Database Performance, Access Patterns, Read Scaling, Proxies, and Caching Practice Test 1

 

Topic 14 Practice Test 1 covers Database Performance, Access Patterns, Read Scaling, Proxies, and Caching for AWS SAA-C03. For broader exam preparation, review the AWS SAA-C03 Exam Dumps. Every option includes focused technical reasoning explaining both the AWS architecture concept and its fit to the scenario.

Question 1

A reporting tier generates heavy SELECT traffic against an Aurora cluster and should spread connections across several read replicas. Which option most directly satisfies the requirement to scale Aurora reads through a cluster-managed read endpoint?

1. Aurora Replica
2. DynamoDB strongly consistent read
3. ElastiCache for Memcached
4. Aurora reader endpoint

Correct Answer(s)

 

D

Rationale

1. Aurora Replica provides an asynchronously updated read instance that. It fits an Aurora workload needs additional read. Here, a reporting tier generates heavy SELECT traffic against an Aurora cluster and should spread connections across several read replicas. The team must scale Aurora reads through a cluster-managed read endpoint; that points to Aurora reader endpoint.
2. DynamoDB strongly consistent read returns the most up-to-date successful write for. Its role covers a read must reflect the latest. Here, a reporting tier generates heavy SELECT traffic against an Aurora cluster and should spread connections across several read replicas. The architecture must scale Aurora reads through a cluster-managed read endpoint; Aurora reader endpoint supplies that function.
3. ElastiCache for Memcached provides a simple distributed in-memory object cache. Normally for a stateless cache needs straightforward scale-out. The scenario has a reporting tier generates heavy SELECT traffic against an Aurora cluster and should spread connections across several read replicas. Because the solution must scale Aurora reads through a cluster-managed read endpoint, Aurora reader endpoint fits better.
4. Aurora reader endpoint load balances read-only connections across available Aurora. Here, a reporting tier generates heavy SELECT traffic against an Aurora cluster and should spread connections across several read replicas. Appropriate for applications need horizontal read scaling without. The team must scale Aurora reads through a cluster-managed read endpoint; Aurora reader endpoint supplies the mechanism.

 

Question 2

An Aurora database is CPU-bound on analytical reads while writes are modest and should remain on the writer. What should the architect select to add read capacity without creating a separate data copy process?

1. DynamoDB DAX
2. Aurora Serverless v2
3. RDS read replica
4. Aurora Replica

Correct Answer(s)

 

D

Rationale

1. DynamoDB DAX is an in-memory cache purpose-built for DynamoDB. Suited to a DynamoDB application needs microsecond read. The key fact is an Aurora database is CPU-bound on analytical reads while writes are modest and should remain on the writer. The team must add read capacity without creating a separate data copy process; Aurora Replica supports that decision.
2. Aurora Serverless v2 automatically adjusts Aurora database compute capacity within. It addresses Aurora workload demand is highly variable. The review finds an Aurora database is CPU-bound on analytical reads while writes are modest and should remain on the writer. Implementation must add read capacity without creating a separate data copy process, so Aurora Replica is aligned.
3. RDS read replica creates an asynchronously replicated read-only database instance. It helps with read-heavy workloads should be offloaded from. Here, an Aurora database is CPU-bound on analytical reads while writes are modest and should remain on the writer. The required result is to add read capacity without creating a separate data copy process, making Aurora Replica stronger.
4. Aurora Replica provides an asynchronously updated read instance that. The case has an Aurora database is CPU-bound on analytical reads while writes are modest and should remain on the writer. It suits an Aurora workload needs additional read. The decision is to add read capacity without creating a separate data copy process, which Aurora Replica provides.

 

Question 3

A MySQL RDS primary is overloaded by business-intelligence queries that can tolerate seconds of stale data. Which design choice best enables the team to offload eligible reads to an asynchronously updated copy?

1. RDS Performance Insights/Database Insights
2. DynamoDB partition key
3. RDS read replica
4. RDS Proxy

Correct Answer(s)

 

C

Rationale

1. RDS Performance Insights/Database Insights surfaces database load and wait information to. Intended for operators need evidence about SQL, waits,. Here, a MySQL RDS primary is overloaded by business-intelligence queries that can tolerate seconds of stale data. The team must offload eligible reads to an asynchronously updated copy; RDS read replica provides that behavior.
2. DynamoDB partition key determines how items are distributed across partitions. Better for a DynamoDB table needs an access. The constraint is a MySQL RDS primary is overloaded by business-intelligence queries that can tolerate seconds of stale data. The design must offload eligible reads to an asynchronously updated copy, which RDS read replica does.
3. RDS read replica creates an asynchronously replicated read-only database instance. In this scenario, a MySQL RDS primary is overloaded by business-intelligence queries that can tolerate seconds of stale data. It fits read-heavy workloads should be offloaded from. The design needs to offload eligible reads to an asynchronously updated copy; RDS read replica is the direct match.
4. RDS Proxy pools and shares database connections so applications. Its value covers bursty serverless or container workloads create. Here, a MySQL RDS primary is overloaded by business-intelligence queries that can tolerate seconds of stale data. The solution must offload eligible reads to an asynchronously updated copy; RDS read replica matches the need.

 

Question 4

Thousands of Lambda invocations open brief connections to an RDS database and connection churn is exhausting database resources. Which capability is the best fit when the goal is to pool application database connections?

1. Read-through cache pattern
2. DynamoDB sort key
3. RDS Proxy
4. RDS Proxy read-only endpoint

Correct Answer(s)

 

C

Rationale

1. Read-through cache pattern checks the cache first and loads missing. Normally for applications repeatedly read data and can. The scenario has thousands of Lambda invocations open brief connections to an RDS database and connection churn is exhausting database resources. Because the solution must pool application database connections, RDS Proxy fits better.
2. DynamoDB sort key orders items sharing a partition key and. It fits related items must be queried efficiently. Here, thousands of Lambda invocations open brief connections to an RDS database and connection churn is exhausting database resources. The team must pool application database connections; that points to RDS Proxy.
3. RDS Proxy pools and shares database connections so applications. The key condition is thousands of Lambda invocations open brief connections to an RDS database and connection churn is exhausting database resources. It supports bursty serverless or container workloads create. The architecture must pool application database connections; RDS Proxy performs that role.
4. RDS Proxy read-only endpoint routes proxy client sessions toward read replicas. Useful for applications need connection pooling plus a. Here, thousands of Lambda invocations open brief connections to an RDS database and connection churn is exhausting database resources. The design must pool application database connections; RDS Proxy, not RDS Proxy read-only endpoint, supplies that behavior.

 

Question 5

A service already uses RDS Proxy but wants reporting connections isolated onto read replicas while keeping pooled connections. What is the most appropriate solution to combine proxy connection management with a read-only route?

1. RDS Proxy read-only endpoint
2. DynamoDB GSI
3. ElastiCache for Redis
4. TTL-based cache expiration

Correct Answer(s)

 

A

Rationale

1. RDS Proxy read-only endpoint routes proxy client sessions toward read replicas. Here, a service already uses RDS Proxy but wants reporting connections isolated onto read replicas while keeping pooled connections. Useful for applications need connection pooling plus a. The team must combine proxy connection management with a read-only route, which RDS Proxy read-only endpoint supplies.
2. DynamoDB GSI provides an alternate partition/sort key access pattern. It helps with queries need a key pattern not. Here, a service already uses RDS Proxy but wants reporting connections isolated onto read replicas while keeping pooled connections. The required result is to combine proxy connection management with a read-only route, making RDS Proxy read-only endpoint stronger.
3. ElastiCache for Redis provides an in-memory key-value cache that can. Its role covers applications repeatedly request hot data that. Here, a service already uses RDS Proxy but wants reporting connections isolated onto read replicas while keeping pooled connections. The architecture must combine proxy connection management with a read-only route; RDS Proxy read-only endpoint supplies that function.
4. TTL-based cache expiration automatically ages cached entries out after a. Suited to the application can tolerate bounded staleness. The key fact is a service already uses RDS Proxy but wants reporting connections isolated onto read replicas while keeping pooled connections. The team must combine proxy connection management with a read-only route; RDS Proxy read-only endpoint supports that decision.

 

Question 6

A product catalog repeatedly reads the same popular records from a relational database and sub-millisecond access is valuable. Which technology or control should be used to cache frequently requested application data outside the database?

1. ElastiCache for Memcached
2. DynamoDB LSI
3. ElastiCache for Redis
4. Database connection reuse

Correct Answer(s)

 

C

Rationale

1. ElastiCache for Memcached a stateless cache needs straightforward scale-out. It addresses provides a simple distributed in-memory object cache. The review finds a product catalog repeatedly reads the same popular records from a relational database and sub-millisecond access is valuable. Implementation must cache frequently requested application data outside the database, so ElastiCache for Redis is aligned.
2. DynamoDB LSI provides an alternate sort key while retaining. Its value covers queries need another ordering within the. Here, a product catalog repeatedly reads the same popular records from a relational database and sub-millisecond access is valuable. The solution must cache frequently requested application data outside the database; ElastiCache for Redis matches the need.
3. ElastiCache for Redis provides an in-memory key-value cache that can. The review finds a product catalog repeatedly reads the same popular records from a relational database and sub-millisecond access is valuable. Intended for applications repeatedly request hot data that. To satisfy the case, the system must cache frequently requested application data outside the database.
4. Database connection reuse keeps or pools established sessions instead of. Better for connection establishment is a significant part. The constraint is a product catalog repeatedly reads the same popular records from a relational database and sub-millisecond access is valuable. The design must cache frequently requested application data outside the database, which ElastiCache for Redis does.

 

Question 7

A web tier needs a disposable distributed cache for rendered objects and can tolerate losing all cached entries. Which approach most directly addresses the need to add a simple ephemeral object cache?

1. DynamoDB DAX
2. ElastiCache for Memcached
3. DynamoDB eventually consistent read
4. Query-specific index

Correct Answer(s)

 

B

Rationale

1. DynamoDB DAX a DynamoDB application needs microsecond read. Intended for is an in-memory cache purpose-built for DynamoDB. Here, a web tier needs a disposable distributed cache for rendered objects and can tolerate losing all cached entries. The team must add a simple ephemeral object cache; ElastiCache for Memcached provides that behavior.
2. ElastiCache for Memcached provides a simple distributed in-memory object cache. Under this constraint, a web tier needs a disposable distributed cache for rendered objects and can tolerate losing all cached entries. It serves a stateless cache needs straightforward scale-out. The correct action is to add a simple ephemeral object cache, making ElastiCache for Memcached appropriate.
3. DynamoDB eventually consistent read can reduce read cost and improve scalability. Useful for applications can tolerate brief staleness and. Here, a web tier needs a disposable distributed cache for rendered objects and can tolerate losing all cached entries. The design must add a simple ephemeral object cache; ElastiCache for Memcached, not DynamoDB eventually consistent read, supplies that behavior.
4. Query-specific index adds an index aligned to selective predicates. It fits a relational workload is slow because. Here, a web tier needs a disposable distributed cache for rendered objects and can tolerate losing all cached entries. The team must add a simple ephemeral object cache; that points to ElastiCache for Memcached.

 

Question 8

A gaming service repeatedly reads the same DynamoDB items and can use eventually consistent responses. What should be implemented to accelerate hot DynamoDB reads through a managed compatible cache?

1. DynamoDB strongly consistent read
2. DynamoDB DAX
3. DynamoDB partition key
4. Aurora reader endpoint

Correct Answer(s)

 

B

Rationale

1. DynamoDB strongly consistent read a read must reflect the latest. Its role covers returns the most up-to-date successful write for. Here, a gaming service repeatedly reads the same DynamoDB items and can use eventually consistent responses. The architecture must accelerate hot DynamoDB reads through a managed compatible cache; DynamoDB DAX supplies that function.
2. DynamoDB DAX is an in-memory cache purpose-built for DynamoDB. The scenario shows a gaming service repeatedly reads the same DynamoDB items and can use eventually consistent responses. It handles a DynamoDB application needs microsecond read. The solution must accelerate hot DynamoDB reads through a managed compatible cache; DynamoDB DAX supplies that function.
3. DynamoDB partition key a DynamoDB table needs an access. Normally for determines how items are distributed across partitions. The scenario has a gaming service repeatedly reads the same DynamoDB items and can use eventually consistent responses. Because the solution must accelerate hot DynamoDB reads through a managed compatible cache, DynamoDB DAX fits better.
4. Aurora reader endpoint load balances read-only connections across available Aurora. It helps with applications need horizontal read scaling without. Here, a gaming service repeatedly reads the same DynamoDB items and can use eventually consistent responses. The required result is to accelerate hot DynamoDB reads through a managed compatible cache, making DynamoDB DAX stronger.

 

Question 9

A high-volume table uses the same customer tier value for most writes and one partition becomes throttled. Which option aligns best with the requirement to choose a partition key that distributes traffic more evenly?

1. DynamoDB sort key
2. Aurora Serverless v2
3. Aurora Replica
4. DynamoDB partition key

Correct Answer(s)

 

D

Rationale

1. DynamoDB sort key related items must be queried efficiently. Suited to orders items sharing a partition key and. The key fact is a high-volume table uses the same customer tier value for most writes and one partition becomes throttled. The team must choose a partition key that distributes traffic more evenly; DynamoDB partition key supports that decision.
2. Aurora Serverless v2 Aurora workload demand is highly variable. It addresses automatically adjusts Aurora database compute capacity within. The review finds a high-volume table uses the same customer tier value for most writes and one partition becomes throttled. Implementation must choose a partition key that distributes traffic more evenly, so DynamoDB partition key is aligned.
3. Aurora Replica an Aurora workload needs additional read. Its value covers provides an asynchronously updated read instance that. Here, a high-volume table uses the same customer tier value for most writes and one partition becomes throttled. The solution must choose a partition key that distributes traffic more evenly; DynamoDB partition key matches the need.
4. DynamoDB partition key determines how items are distributed across partitions. In this architecture, a high-volume table uses the same customer tier value for most writes and one partition becomes throttled. It addresses a DynamoDB table needs an access. Meeting the requirement means the team must choose a partition key that distributes traffic more evenly.

 

Question 10

An application stores all orders for a customer and often requests that customer’s orders for a date range. Which component should the team choose to model an ordered attribute within each customer partition?

1. RDS Performance Insights/Database Insights
2. DynamoDB sort key
3. RDS read replica
4. DynamoDB GSI

Correct Answer(s)

 

B

Rationale

1. RDS Performance Insights/Database Insights operators need evidence about SQL, waits,. Intended for surfaces database load and wait information to. Here, an application stores all orders for a customer and often requests that customer’s orders for a date range. The team must model an ordered attribute within each customer partition; DynamoDB sort key provides that behavior.
2. DynamoDB sort key orders items sharing a partition key and. The deployment has an application stores all orders for a customer and often requests that customer’s orders for a date range. It fits related items must be queried efficiently. The design must model an ordered attribute within each customer partition, which DynamoDB sort key enables.
3. RDS read replica read-heavy workloads should be offloaded from. Useful for creates an asynchronously replicated read-only database instance. Here, an application stores all orders for a customer and often requests that customer’s orders for a date range. The design must model an ordered attribute within each customer partition; DynamoDB sort key, not RDS read replica, supplies that behavior.
4. DynamoDB GSI queries need a key pattern not. Better for provides an alternate partition/sort key access pattern. The constraint is an application stores all orders for a customer and often requests that customer’s orders for a date range. The design must model an ordered attribute within each customer partition, which DynamoDB sort key does.

 

Question 11

Orders are keyed by customer, but operations frequently needs to query all orders by status across customers. What is the strongest architectural response to add an alternate global query key?

1. RDS Proxy
2. DynamoDB LSI
3. Read-through cache pattern
4. DynamoDB GSI

Correct Answer(s)

 

D

Rationale

1. RDS Proxy bursty serverless or container workloads create. Its role covers pools and shares database connections so applications. Here, orders are keyed by customer, but operations frequently needs to query all orders by status across customers. The architecture must add an alternate global query key; DynamoDB GSI supplies that function.
2. DynamoDB LSI queries need another ordering within the. It fits provides an alternate sort key while retaining. Here, orders are keyed by customer, but operations frequently needs to query all orders by status across customers. The team must add an alternate global query key; that points to DynamoDB GSI.
3. Read-through cache pattern applications repeatedly read data and can. Normally for checks the cache first and loads missing. The scenario has orders are keyed by customer, but operations frequently needs to query all orders by status across customers. Because the solution must add an alternate global query key, DynamoDB GSI fits better.
4. DynamoDB GSI provides an alternate partition/sort key access pattern. Here, orders are keyed by customer, but operations frequently needs to query all orders by status across customers. Appropriate for queries need a key pattern not. The team must add an alternate global query key; DynamoDB GSI supplies the mechanism.

 

Question 12

A table keyed by customer and order ID must also sort each customer’s records by order date, and the requirement is known before table creation. Which mechanism is intended to add an alternate local sort-key index?

1. DynamoDB eventually consistent read
2. RDS Proxy read-only endpoint
3. TTL-based cache expiration
4. DynamoDB LSI

Correct Answer(s)

 

D

Rationale

1. DynamoDB eventually consistent read applications can tolerate brief staleness and. It helps with can reduce read cost and improve scalability. Here, a table keyed by customer and order ID must also sort each customer’s records by order date, and the requirement is known before table creation. The required result is to add an alternate local sort-key index, making DynamoDB LSI stronger.
2. RDS Proxy read-only endpoint applications need connection pooling plus a. It addresses routes proxy client sessions toward read replicas. The review finds a table keyed by customer and order ID must also sort each customer’s records by order date, and the requirement is known before table creation. Implementation must add an alternate local sort-key index, so DynamoDB LSI is aligned.
3. TTL-based cache expiration the application can tolerate bounded staleness. Suited to automatically ages cached entries out after a. The key fact is a table keyed by customer and order ID must also sort each customer’s records by order date, and the requirement is known before table creation. The team must add an alternate local sort-key index; DynamoDB LSI supports that decision.
4. DynamoDB LSI provides an alternate sort key while retaining. The case has a table keyed by customer and order ID must also sort each customer’s records by order date, and the requirement is known before table creation. It suits queries need another ordering within the. The decision is to add an alternate local sort-key index, which DynamoDB LSI provides.

 

Question 13

A public product-browse page can display inventory counts that may lag by a moment and must minimize read cost. Which solution best meets the stated need to use lower-cost read consistency appropriate for tolerant workloads?

1. DynamoDB eventually consistent read
2. Database connection reuse
3. ElastiCache for Redis
4. DynamoDB strongly consistent read

Correct Answer(s)

 

A

Rationale

1. DynamoDB eventually consistent read can reduce read cost and improve scalability. In this scenario, a public product-browse page can display inventory counts that may lag by a moment and must minimize read cost. It fits applications can tolerate brief staleness and. The design needs to use lower-cost read consistency appropriate for tolerant workloads; DynamoDB eventually consistent read is the direct match.
2. Database connection reuse connection establishment is a significant part. Better for keeps or pools established sessions instead of. The constraint is a public product-browse page can display inventory counts that may lag by a moment and must minimize read cost. The design must use lower-cost read consistency appropriate for tolerant workloads, which DynamoDB eventually consistent read does.
3. ElastiCache for Redis applications repeatedly request hot data that. Intended for provides an in-memory key-value cache that can. Here, a public product-browse page can display inventory counts that may lag by a moment and must minimize read cost. The team must use lower-cost read consistency appropriate for tolerant workloads; DynamoDB eventually consistent read provides that behavior.
4. DynamoDB strongly consistent read returns the most up-to-date successful write for. Its value covers a read must reflect the latest. Here, a public product-browse page can display inventory counts that may lag by a moment and must minimize read cost. The solution must use lower-cost read consistency appropriate for tolerant workloads; DynamoDB eventually consistent read matches the need.

 

Question 14

Immediately after updating a user’s authorization flag, the application must read back the current value before allowing an operation. What should the team use to request the latest DynamoDB item state?

1. Query-specific index
2. ElastiCache for Memcached
3. DynamoDB strongly consistent read
4. Aurora Serverless v2

Correct Answer(s)

 

C

Rationale

1. Query-specific index a relational workload is slow because. It fits adds an index aligned to selective predicates. Here, immediately after updating a user’s authorization flag, the application must read back the current value before allowing an operation. The team must request the latest DynamoDB item state; that points to DynamoDB strongly consistent read.
2. ElastiCache for Memcached provides a simple distributed in-memory object cache. Normally for a stateless cache needs straightforward scale-out. The scenario has immediately after updating a user’s authorization flag, the application must read back the current value before allowing an operation. Because the solution must request the latest DynamoDB item state, DynamoDB strongly consistent read fits better.
3. DynamoDB strongly consistent read returns the most up-to-date successful write for. The key condition is immediately after updating a user’s authorization flag, the application must read back the current value before allowing an operation. It supports a read must reflect the latest. The architecture must request the latest DynamoDB item state; DynamoDB strongly consistent read performs that role.
4. Aurora Serverless v2 automatically adjusts Aurora database compute capacity within. Useful for Aurora workload demand is highly variable. Here, immediately after updating a user’s authorization flag, the application must read back the current value before allowing an operation. The design must request the latest DynamoDB item state; DynamoDB strongly consistent read, not Aurora Serverless v2, supplies that behavior.

 

Question 15

A SaaS database experiences unpredictable daytime peaks and very low overnight load but needs Aurora compatibility. Which design decision most directly achieves the goal to scale relational compute capacity dynamically with demand?

1. Aurora Serverless v2
2. RDS Performance Insights/Database Insights
3. DynamoDB DAX
4. Aurora reader endpoint

Correct Answer(s)

 

A

Rationale

1. Aurora Serverless v2 automatically adjusts Aurora database compute capacity within. Here, a SaaS database experiences unpredictable daytime peaks and very low overnight load but needs Aurora compatibility. Useful for Aurora workload demand is highly variable. The team must scale relational compute capacity dynamically with demand, which Aurora Serverless v2 supplies.
2. RDS Performance Insights/Database Insights surfaces database load and wait information to. Its role covers operators need evidence about SQL, waits,. Here, a SaaS database experiences unpredictable daytime peaks and very low overnight load but needs Aurora compatibility. The architecture must scale relational compute capacity dynamically with demand; Aurora Serverless v2 supplies that function.
3. DynamoDB DAX is an in-memory cache purpose-built for DynamoDB. Suited to a DynamoDB application needs microsecond read. The key fact is a SaaS database experiences unpredictable daytime peaks and very low overnight load but needs Aurora compatibility. The team must scale relational compute capacity dynamically with demand; Aurora Serverless v2 supports that decision.
4. Aurora reader endpoint applications need horizontal read scaling without. It helps with load balances read-only connections across available Aurora. Here, a SaaS database experiences unpredictable daytime peaks and very low overnight load but needs Aurora compatibility. The required result is to scale relational compute capacity dynamically with demand, making Aurora Serverless v2 stronger.

 

Question 16

An RDS database has intermittent latency spikes and the team needs to identify which SQL and waits dominate during the event. Which feature best supports the requirement to analyze database load before tuning?

1. Aurora Replica
2. RDS Performance Insights/Database Insights
3. Read-through cache pattern
4. DynamoDB partition key

Correct Answer(s)

 

B

Rationale

1. Aurora Replica provides an asynchronously updated read instance that. Its value covers an Aurora workload needs additional read. Here, an RDS database has intermittent latency spikes and the team needs to identify which SQL and waits dominate during the event. The solution must analyze database load before tuning; RDS Performance Insights/Database Insights matches the need.
2. RDS Performance Insights/Database Insights surfaces database load and wait information to. The review finds an RDS database has intermittent latency spikes and the team needs to identify which SQL and waits dominate during the event. Intended for operators need evidence about SQL, waits,. To satisfy the case, the system must analyze database load before tuning.
3. Read-through cache pattern checks the cache first and loads missing. It addresses applications repeatedly read data and can. The review finds an RDS database has intermittent latency spikes and the team needs to identify which SQL and waits dominate during the event. Implementation must analyze database load before tuning, so RDS Performance Insights/Database Insights is aligned.
4. DynamoDB partition key determines how items are distributed across partitions. Better for a DynamoDB table needs an access. The constraint is an RDS database has intermittent latency spikes and the team needs to identify which SQL and waits dominate during the event. The design must analyze database load before tuning, which RDS Performance Insights/Database Insights does.

 

Question 17

A service should avoid querying the database for popular objects after the first request but still retrieve missing objects automatically. Which choice addresses the controlling constraint to implement cache-first retrieval with database fallback?

1. Read-through cache pattern
2. RDS read replica
3. DynamoDB sort key
4. TTL-based cache expiration

Correct Answer(s)

 

A

Rationale

1. Read-through cache pattern checks the cache first and loads missing. Under this constraint, a service should avoid querying the database for popular objects after the first request but still retrieve missing objects automatically. It serves applications repeatedly read data and can. The correct action is to implement cache-first retrieval with database fallback, making Read-through cache pattern appropriate.
2. RDS read replica creates an asynchronously replicated read-only database instance. Useful for read-heavy workloads should be offloaded from. Here, a service should avoid querying the database for popular objects after the first request but still retrieve missing objects automatically. The design must implement cache-first retrieval with database fallback; Read-through cache pattern, not RDS read replica, supplies that behavior.
3. DynamoDB sort key orders items sharing a partition key and. It fits related items must be queried efficiently. Here, a service should avoid querying the database for popular objects after the first request but still retrieve missing objects automatically. The team must implement cache-first retrieval with database fallback; that points to Read-through cache pattern.
4. TTL-based cache expiration automatically ages cached entries out after a. Intended for the application can tolerate bounded staleness. Here, a service should avoid querying the database for popular objects after the first request but still retrieve missing objects automatically. The team must implement cache-first retrieval with database fallback; Read-through cache pattern provides that behavior.

 

Question 18

Exchange-rate responses may be cached for five minutes but should refresh automatically after that interval. What is the best next design choice to set a bounded cache lifetime?

1. TTL-based cache expiration
2. RDS Proxy
3. DynamoDB GSI
4. Database connection reuse

Correct Answer(s)

 

A

Rationale

1. TTL-based cache expiration automatically ages cached entries out after a. The scenario shows exchange-rate responses may be cached for five minutes but should refresh automatically after that interval. It handles the application can tolerate bounded staleness. The solution must set a bounded cache lifetime; TTL-based cache expiration supplies that function.
2. RDS Proxy pools and shares database connections so applications. Its role covers bursty serverless or container workloads create. Here, exchange-rate responses may be cached for five minutes but should refresh automatically after that interval. The architecture must set a bounded cache lifetime; TTL-based cache expiration supplies that function.
3. DynamoDB GSI provides an alternate partition/sort key access pattern. It helps with queries need a key pattern not. Here, exchange-rate responses may be cached for five minutes but should refresh automatically after that interval. The required result is to set a bounded cache lifetime, making TTL-based cache expiration stronger.
4. Database connection reuse keeps or pools established sessions instead of. Normally for connection establishment is a significant part. The scenario has exchange-rate responses may be cached for five minutes but should refresh automatically after that interval. Because the solution must set a bounded cache lifetime, TTL-based cache expiration fits better.

 

Question 19

A container service performs short database operations but opens and closes a new TLS database connection for every request. Which capability should be selected to reduce connection setup overhead?

1. DynamoDB LSI
2. Query-specific index
3. Database connection reuse
4. RDS Proxy read-only endpoint

Correct Answer(s)

 

C

Rationale

1. DynamoDB LSI provides an alternate sort key while retaining. Its value covers queries need another ordering within the. Here, a container service performs short database operations but opens and closes a new TLS database connection for every request. The solution must reduce connection setup overhead; Database connection reuse matches the need.
2. Query-specific index adds an index aligned to selective predicates. Suited to a relational workload is slow because. The key fact is a container service performs short database operations but opens and closes a new TLS database connection for every request. The team must reduce connection setup overhead; Database connection reuse supports that decision.
3. Database connection reuse keeps or pools established sessions instead of. In this architecture, a container service performs short database operations but opens and closes a new TLS database connection for every request. It addresses connection establishment is a significant part. Meeting the requirement means the team must reduce connection setup overhead.
4. RDS Proxy read-only endpoint routes proxy client sessions toward read replicas. It addresses applications need connection pooling plus a. The review finds a container service performs short database operations but opens and closes a new TLS database connection for every request. Implementation must reduce connection setup overhead, so Database connection reuse is aligned.

 

Question 20

A reporting query filters by customer ID and date but the table has no index supporting those predicates. Which option solves the described need to improve the query access path before increasing instance size?

1. Aurora reader endpoint
2. Query-specific index
3. DynamoDB eventually consistent read
4. ElastiCache for Redis

Correct Answer(s)

 

B

Rationale

1. Aurora reader endpoint load balances read-only connections across available Aurora. Better for applications need horizontal read scaling without. The constraint is a reporting query filters by customer ID and date but the table has no index supporting those predicates. The design must improve the query access path before increasing instance size, which Query-specific index does.
2. Query-specific index adds an index aligned to selective predicates. The deployment has a reporting query filters by customer ID and date but the table has no index supporting those predicates. It fits a relational workload is slow because. The design must improve the query access path before increasing instance size, which Query-specific index enables.
3. DynamoDB eventually consistent read can reduce read cost and improve scalability. Useful for applications can tolerate brief staleness and. Here, a reporting query filters by customer ID and date but the table has no index supporting those predicates. The design must improve the query access path before increasing instance size; Query-specific index, not DynamoDB eventually consistent read, supplies that behavior.
4. ElastiCache for Redis provides an in-memory key-value cache that can. Intended for applications repeatedly request hot data that. Here, a reporting query filters by customer ID and date but the table has no index supporting those predicates. The team must improve the query access path before increasing instance size; Query-specific index provides that behavior.

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