AWS Certified Database Specialty DBS-C01 DBS-C01 Questions 1651–1663 | Page 23/23

1651

MCQeasy

A company needs to store and analyze log data from thousands of servers. The logs are timestamped and rarely updated. Queries are mostly time-range aggregations. Which database service is best suited for this workload?

A.Amazon CloudWatch Logs

B.Amazon ElastiCache for Redis

C.Amazon DynamoDB

D.Amazon RDS for PostgreSQL

AnswerA

CloudWatch Logs is purpose-built for log ingestion, storage, and analysis.

Why this answer

Amazon CloudWatch Logs is purpose-built for ingesting, storing, and analyzing timestamped log data from distributed sources. It supports real-time and historical time-range aggregations via Logs Insights, which uses a query language optimized for pattern matching and aggregation over time windows. The service automatically handles high-throughput ingestion from thousands of servers and is cost-effective for append-only, rarely updated log data.

Exam trap

The trap here is that candidates often choose DynamoDB or RDS because they are familiar with general-purpose databases, but they overlook that CloudWatch Logs is a fully managed, serverless service specifically designed for log ingestion and time-series analysis, eliminating the need for custom schema design, indexing, or scaling logic.

How to eliminate wrong answers

Option B (Amazon ElastiCache for Redis) is wrong because Redis is an in-memory key-value store designed for low-latency caching and real-time data structures, not for persistent storage or time-range aggregation queries over large volumes of log data; it lacks native log analytics capabilities and would require significant custom development. Option C (Amazon DynamoDB) is wrong because DynamoDB is a NoSQL key-value and document database optimized for point lookups and high-throughput transactional workloads, not for time-series aggregations; it does not support native time-range aggregation queries and would require complex application-level logic and secondary indexes to approximate log analysis. Option D (Amazon RDS for PostgreSQL) is wrong because PostgreSQL is a relational database designed for structured, transactional data with complex joins and ACID compliance; it is not optimized for high-ingest, append-only log workloads and would incur high storage costs and performance bottlenecks under the write load from thousands of servers, and its time-range aggregation queries would be slower than a purpose-built log analytics service.

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1652

MCQhard

A company runs an Amazon Aurora MySQL DB cluster with one writer and two readers. They notice that one reader instance is consistently showing higher than expected lag. The other reader is fine. What is the most likely cause?

A.The writer instance is experiencing high write activity

B.There is a network connectivity issue between the writer and that reader

C.The reader instance is being used for heavy analytical queries

D.The reader instance has a different DB parameter group

AnswerC

Heavy read workload on a reader can cause replication lag.

Why this answer

An imbalanced workload on that reader can cause it to lag. Option A is wrong because writer load affects all replicas. Option B is wrong because network issues would affect both readers.

Option D is wrong because parameter group change would affect both readers if applied to cluster.

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1653

MCQmedium

A company uses Amazon DynamoDB to store IoT sensor data. Each sensor writes a record every second, and the application needs to query the last 24 hours of data for a specific sensor. The query must be very fast. Which table design and query pattern will minimize cost and latency?

A.Use a simple primary key (sensor ID) and scan the table filtering by timestamp

B.Use a composite primary key: partition key = sensor ID, sort key = timestamp

C.Use a composite primary key: partition key = timestamp, sort key = sensor ID

D.Use a simple primary key (sensor ID) and a global secondary index on timestamp

AnswerB

This allows efficient range queries on timestamp for a sensor.

Why this answer

Using a composite primary key with partition key = sensor ID and sort key = timestamp allows DynamoDB to efficiently query all items for a specific sensor in a single partition, using the Query API with a sort key condition on timestamp. This design ensures fast, targeted reads without scanning, minimizing read capacity units and latency.

Exam trap

The trap here is that candidates often choose Option C, mistakenly thinking that timestamp as a partition key provides global time ordering, but this actually scatters sensor data across partitions, making per-sensor queries impossible without a full scan.

How to eliminate wrong answers

Option A is wrong because using a simple primary key (sensor ID) with a scan and filter forces DynamoDB to read every item in the table, consuming excessive read capacity and causing high latency, which violates the requirement for fast queries. Option C is wrong because using timestamp as the partition key would scatter each sensor's data across many partitions, making it impossible to query all data for a single sensor efficiently; instead, you would need to query every partition or use a costly scan. Option D is wrong because while a global secondary index on timestamp could help, the base table still uses a simple primary key (sensor ID), which would require a scan or an inefficient index design; additionally, GSI writes incur extra cost and eventual consistency, and the query pattern would not be as optimal as using a composite key directly.

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1654

Multi-Selecteasy

Which TWO actions should be taken to troubleshoot high memory usage on an Amazon ElastiCache for Redis node? (Choose two.)

Select 1 answer

A.Monitor the Evictions CloudWatch metric.

B.Increase the maxmemory parameter to allow more memory usage.

C.Monitor CPUUtilization CloudWatch metric.

D.Enable cluster mode to distribute memory across shards.

E.Enable Reserved Memory parameter group setting.

AnswersA

Correct. Monitoring the Evictions metric directly indicates memory pressure because Redis evicts keys when it reaches the maxmemory limit. A high eviction count signals high memory usage.

Why this answer

Monitoring the Evictions CloudWatch metric is the only valid action among the options for troubleshooting high memory usage on an Amazon ElastiCache for Redis node. Option B is incorrect because the maxmemory parameter is determined by the node type and cannot be increased; it is fixed. Options C, D, and E are not direct troubleshooting steps for memory pressure.

Option C monitors CPU, not memory. Option D (enabling cluster mode) is a scaling action, not a troubleshooting step for an existing node. Option E (Reserved Memory) is a preventive setting but not a primary troubleshooting action.

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1655

MCQeasy

A company is using Amazon Aurora MySQL and needs to audit all database logins and query activity. Which feature should be enabled to meet this requirement?

A.Enable database audit logs by setting the audit_log_enabled parameter to 1.

B.Enable RDS Enhanced Monitoring.

C.Enable AWS CloudTrail to log database queries.

D.Enable Advanced Auditing through the DB cluster parameter group by setting the server_audit_logging parameter and related parameters.

AnswerD

This is the correct feature for auditing queries and logins in Aurora MySQL.

Why this answer

Amazon Aurora MySQL's Advanced Auditing feature, enabled by setting the server_audit_logging parameter and related parameters in the DB cluster parameter group, captures all database logins and query activity. Option A (audit_log_enabled) is a different, less detailed audit log feature, not the full advanced auditing. Option B (Enhanced Monitoring) monitors OS-level metrics, not database activity.

Option C (CloudTrail) logs AWS API calls, not database queries.

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1656

MCQeasy

Refer to the exhibit. A DBA is troubleshooting a performance issue on an RDS for MySQL DB instance. The DBA runs the AWS CLI command shown. Based on the output, which of the following is a potential performance bottleneck?

A.The storage type is gp2, which may have limited IOPS performance.

B.The DB instance is not Multi-AZ, causing failover delay.

C.The DB instance status is 'available', meaning it is not accepting connections.

D.The engine version 8.0.27 has a known performance bug.

AnswerA

gp2 is burstable; under sustained load, performance may degrade.

Why this answer

The instance uses gp2 storage, which has burstable IOPS. If the burst balance is depleted, performance can degrade. The engine version is recent, Multi-AZ is not enabled, but that affects availability, not necessarily performance.

DB instance status is available so no issue there.

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1657

MCQhard

A company runs a critical MySQL database on Amazon RDS Single-AZ (db.m5.large) with 200 GB of Provisioned IOPS (io1) storage set to 3000 IOPS. The application team reports that write operations are occasionally slow. CloudWatch metrics show that the Write IOPS metric peaks at 3500 IOPS during the slowdowns, but the average is 2000 IOPS. The Read IOPS average is 500 IOPS. The queue depth metric occasionally spikes to 20. The storage configuration includes a 50 GB General Purpose SSD (gp2) log volume attached to the same RDS instance. Which change will MOST effectively resolve the write latency?

A.Change the storage type to gp3 with 3000 baseline IOPS.

B.Move the log volume to the same io1 volume to reduce I/O overhead.

C.Increase the provisioned IOPS on the io1 volume to 4000.

D.Enable Multi-AZ for failover protection.

AnswerC

Increasing provisioned IOPS to match peak demand (3500) gives headroom and reduces queue depth.

Why this answer

The io1 volume is provisioned at 3000 IOPS, but the workload bursts to 3500 IOPS, causing queue depth to spike. Increasing the provisioned IOPS to 4000 ensures that the volume can handle the peak without queuing. Option A is incorrect because changing to gp3 with 3000 baseline IOPS does not address the peak IOPS requirement; gp3 can burst but the consistent peak above baseline may still cause throttling.

Option B is incorrect because moving the log volume to the same io1 volume would mix I/O streams and could increase contention, not reduce it. Option D is incorrect because enabling Multi-AZ provides high availability and fails over to a standby, but does not increase IOPS capacity or resolve write latency.

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1658

MCQmedium

A team is migrating an on-premises Microsoft SQL Server database to AWS. The database is used for reporting and analytics, with complex queries that join multiple tables. The team wants to minimize application changes and ensure compatibility. Which AWS service should they use?

A.Amazon RDS for SQL Server

B.Amazon RDS for MySQL

C.Amazon Redshift

D.Amazon DynamoDB

AnswerA

RDS for SQL Server offers native compatibility, minimizing migration effort.

Why this answer

Amazon RDS for SQL Server is the correct choice because it provides a managed SQL Server database engine that is fully compatible with on-premises SQL Server, minimizing application changes. The service supports complex queries with joins and reporting workloads without requiring code modifications, as it uses the same T-SQL dialect and features.

Exam trap

The trap here is that candidates often choose Amazon Redshift for analytics workloads, overlooking that the question emphasizes minimizing application changes and compatibility with an existing SQL Server database, which Redshift cannot provide due to its different SQL dialect and architecture.

How to eliminate wrong answers

Option B is wrong because Amazon RDS for MySQL uses a different SQL dialect and does not support T-SQL-specific features like stored procedures, linked servers, or certain window functions that SQL Server applications may rely on, requiring significant application changes. Option C is wrong because Amazon Redshift is a columnar data warehouse optimized for large-scale analytical queries, not a transactional or relational database; it does not support the same SQL Server syntax, triggers, or stored procedures, and would require rewriting queries and application logic. Option D is wrong because Amazon DynamoDB is a NoSQL key-value and document database that does not support SQL joins, complex queries, or relational schemas, making it incompatible with the existing reporting and analytics workload.

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1659

MCQmedium

A developer needs to allow an application running on EC2 to access an Amazon RDS database without storing database credentials in the application code. Which solution is the MOST secure?

A.Use IAM database authentication for the RDS instance and assign an IAM role to the EC2 instance.

B.Store the database password in AWS Systems Manager Parameter Store as a SecureString.

C.Store the database password in the application configuration file.

D.Store the database password in AWS Secrets Manager and enable automatic rotation.

AnswerA

Correct. IAM database authentication uses IAM roles to grant access without passwords, eliminating credential storage.

Why this answer

IAM database authentication allows the EC2 instance to use an IAM role to authenticate to the RDS database, eliminating the need to store any credentials in the application code. This is the most secure method. Options B and C still rely on storing and retrieving a password, which introduces risk.

Option D stores credentials in a config file, which is insecure.

Exam trap

Candidates often assume that any solution using a secrets vault (Parameter Store or Secrets Manager) is the most secure, but IAM database authentication avoids credentials entirely, making it more secure.

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1660

MCQeasy

A database administrator needs to automate the backup process for an Amazon RDS for MySQL DB instance. The backups must be retained for 30 days and should be taken daily. Which AWS service should be used to implement this automation?

A.Amazon S3 lifecycle policies

B.AWS Backup

C.AWS Lambda with custom scripts

D.Amazon RDS automated backups

AnswerD

RDS automated backups can be enabled with a retention period of up to 35 days and perform daily backups automatically.

Why this answer

Amazon RDS automated backups are the native, built-in mechanism for backing up RDS DB instances. They automatically take daily snapshots during the backup window and retain transaction logs for point-in-time recovery. By default, the retention period can be set from 1 to 35 days, so configuring it to 30 days meets the requirement without any additional services or custom scripting.

Exam trap

The trap here is that candidates may over-engineer the solution by choosing AWS Backup or Lambda, not realizing that RDS automated backups natively support daily backups with a configurable retention period up to 35 days, making them the simplest and most appropriate choice.

How to eliminate wrong answers

Option A is wrong because Amazon S3 lifecycle policies manage the transition and expiration of objects stored in S3 buckets, not the scheduling or retention of RDS backups. Option B is wrong because AWS Backup is a centralized backup service that can back up RDS instances, but it is not required for this simple automation—RDS automated backups already provide daily backups with configurable retention natively. Option C is wrong because while AWS Lambda with custom scripts could be used to trigger manual snapshots, it adds unnecessary complexity and operational overhead when the built-in automated backup feature of RDS directly satisfies the requirement.

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1661

MCQmedium

A company is using Amazon RDS for MySQL with Multi-AZ deployment. The database experiences a failover event, and after failover, the application reports increased latency. Which action should the database specialist take to diagnose the issue?

A.Check Amazon CloudWatch metrics for Database Connections and Latency, and verify DNS resolution.

B.Promote the secondary instance to primary manually.

C.Create a new read replica and redirect traffic.

D.Force a reboot of the DB instance to reset connections.

AnswerA

Monitoring metrics and DNS can pinpoint the cause of increased latency.

Why this answer

After a Multi-AZ failover, the DNS record for the RDS endpoint is updated to point to the new primary in a different Availability Zone. If the application's DNS cache still resolves to the old IP (which is now unreachable or in a different AZ), connections may time out or route suboptimally, increasing latency. Checking CloudWatch metrics for Database Connections and Latency helps isolate whether the issue is due to connection churn, resource contention, or DNS caching, while verifying DNS resolution confirms the application is connecting to the correct endpoint.

Exam trap

The trap here is that candidates assume increased latency after failover is always due to resource exhaustion or a need to reset connections, overlooking the common root cause of DNS caching and stale client connections routing to the wrong AZ.

How to eliminate wrong answers

Option B is wrong because manually promoting the secondary instance is unnecessary and counterproductive; Multi-AZ failover already promotes the standby automatically, and manual promotion would cause another disruption. Option C is wrong because creating a new read replica does not address the primary's latency issue; read replicas are for offloading read traffic, not for fixing failover-related latency on the primary. Option D is wrong because forcing a reboot resets connections but does not resolve the underlying cause of increased latency, such as DNS caching or a cold buffer pool on the new primary; it would only add downtime.

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1662

MCQhard

A logistics company operates a fleet tracking system using Amazon DocumentDB (with MongoDB compatibility). The database stores location updates from thousands of vehicles every second. The collection has a compound index on (vehicle_id, timestamp). Recently, the company noticed that write latency has increased, and the primary instance's CPU is consistently above 80%. The storage is gp2, and the instance is a db.r5.large. The operations team suspects that index maintenance is causing high CPU. The database administrator needs to reduce write latency without sacrificing query performance for real-time location queries. What should the administrator do?

A.Remove the compound index and rely on the default _id index for queries.

B.Upgrade to a larger instance class, such as db.r5.xlarge, to provide more CPU and memory.

C.Disable journaling to reduce write I/O.

D.Shard the collection using a hash-based shard key on vehicle_id to distribute write load.

AnswerD

Sharding the collection using a hash-based shard key on vehicle_id distributes writes evenly and reduces index maintenance overhead.

Why this answer

Sharding the collection using a hash-based shard key on vehicle_id distributes writes evenly and reduces index maintenance overhead. Option A is wrong because removing the compound index harms query performance for real-time location queries. Option B is wrong because upgrading to a larger instance class adds CPU but does not address the root cause of index maintenance overhead.

Option C is wrong because disabling journaling reduces durability, not index maintenance.

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1663

MCQeasy

A company wants to migrate an on-premises Oracle database to Amazon Aurora PostgreSQL. They need to convert the schema and code. Which AWS service should they use?

A.AWS Schema Conversion Tool (SCT)

B.AWS Lambda

C.Amazon S3

D.AWS Database Migration Service (DMS)

AnswerA

Converts schema and code.

Why this answer

AWS Schema Conversion Tool (SCT) is the correct choice because it is specifically designed to convert database schemas and code objects (such as stored procedures, functions, and triggers) from one database engine to another. For an Oracle-to-Aurora PostgreSQL migration, SCT analyzes the source schema, identifies incompatible data types and syntax, and generates equivalent PostgreSQL DDL and PL/pgSQL code, handling complex conversions like Oracle sequences to PostgreSQL sequences and Oracle packages to PostgreSQL schemas.

Exam trap

The trap here is that candidates often confuse AWS DMS with schema conversion, but DMS only moves data and requires SCT for the schema and code transformation; AWS explicitly separates these tasks in the migration process.

How to eliminate wrong answers

Option B (AWS Lambda) is wrong because Lambda is a serverless compute service for running code in response to events, not a schema or code conversion tool; it cannot translate Oracle PL/SQL to PostgreSQL PL/pgSQL. Option C (Amazon S3) is wrong because S3 is an object storage service used for storing data and backups, not for converting database schemas or code. Option D (AWS Database Migration Service) is wrong because DMS handles data migration (moving table data) but does not perform schema or code conversion; it relies on SCT to generate the target schema before DMS can migrate the data.

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AWS Certified Database Specialty DBS-C01 (DBS-C01) — Questions 1651–1663