DBS-C01 Practice Exam 65 — 20 Questions

Question 1

A company is using Amazon ElastiCache for Redis as a caching layer for frequently accessed data. The application needs to support caching of session data that must be highly available across multiple Availability Zones. Which ElastiCache configuration should be used?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Deploy a Redis cluster with cluster mode enabled and replica nodes in a different Availability Zone.. Deploying a Redis cluster with cluster mode enabled and replica nodes in a different Availability Zone provides both high availability and automatic failover for session data. ElastiCache for Redis with cluster mode enabled supports sharding and replication, allowing replica nodes to be placed in a separate AZ to survive an AZ failure. This configuration ensures session data remains accessible even if the primary node or an entire AZ becomes unavailable, meeting the requirement for multi-AZ high availability.

Answer

Deploy a single Redis node in one Availability Zone.

Answer

Deploy a Redis cluster with cluster mode disabled.

Answer

Deploy a Memcached cluster with multiple nodes.

Question 2

A database specialist is troubleshooting a degraded Amazon Aurora MySQL database cluster. The primary instance is showing elevated read latency and the replica lag is increasing. The DB cluster has one writer and one reader instance. The writer instance is using 90% of its allocated memory, and the reader instance is using 70%. Which action is most likely to reduce read latency and replica lag?

Accepted Answer

Increase the reader instance size to provide more buffer pool memory.. Increasing the reader instance size provides more memory for the buffer pool, which improves read performance and can reduce replica lag. The reader is using 70% memory, so adding more buffer pool memory allows it to cache more data and handle read requests faster. Option A is incorrect because increasing storage improves I/O throughput but does not directly address memory constraints or replica lag. Option B is incorrect because the writer instance is already under memory pressure, but the issue is read latency on the reader, not write performance. Option D is incorrect because adding a second reader distributes the read load but does not resolve the memory bottleneck on the existing reader; a larger instance is more effective in this scenario.

Answer

Increase the allocated storage for the cluster to improve I/O throughput.

Answer

Increase the writer instance size to provide more memory for write operations.

Answer

Add a second reader instance to distribute the read load.

Question 3

A company runs a MySQL-compatible database on Amazon RDS with a 3 TB dataset. They need to run complex analytical queries that involve joins and aggregations on millions of rows. The current RDS instance is a db.r5.8xlarge with 32 vCPUs and 256 GB RAM, but complex queries take over an hour. Which design change would most improve query performance for this workload?

Accepted Answer

Use Amazon Redshift for the analytical workload. Amazon Redshift is a fully managed, petabyte-scale data warehouse service optimized for complex analytical queries involving joins and aggregations on large datasets. Unlike RDS, which is designed for OLTP workloads, Redshift uses columnar storage, massively parallel processing (MPP), and automatic compression to dramatically reduce query times for analytical workloads. Migrating the analytical workload to Redshift offloads the heavy processing from the RDS instance, allowing it to continue serving transactional queries efficiently.

Answer

Migrate to Amazon Aurora with parallel query

Answer

Add an Amazon ElastiCache cluster to cache query results

Answer

Enable DynamoDB Accelerator (DAX) on the RDS instance

Question 4

Which THREE factors should be considered when choosing between Amazon DynamoDB and Amazon RDS for a new application? (Choose three.)

Accepted Answer

Need for ACID transactions across multiple rows. Amazon RDS supports ACID transactions across multiple rows using traditional SQL databases like MySQL or PostgreSQL, which is essential for applications requiring strict consistency (e.g., financial systems). Amazon DynamoDB, while supporting ACID transactions via the TransactGetItems and TransactWriteItems APIs, is optimized for single-item or limited multi-item operations and may not perform as well for complex multi-row transactional workloads. The need for ACID across multiple rows is a key differentiator favoring RDS.

Answer

Need for automatic failover in multiple AWS Regions

Answer

Data size exceeding 10 TB

Question 5

A company is migrating a 10 TB Oracle database to Amazon RDS for Oracle. The migration window is limited to 24 hours. The source database is running on-premises with a 500 Mbps network connection. Which migration approach should be used?

Accepted Answer

Use AWS DMS with full load and ongoing replication. AWS DMS with full load and ongoing replication is the correct approach because it can handle the 10 TB migration within the 24-hour window by using the 500 Mbps connection for the initial full load (which takes approximately 48 hours at full bandwidth, but DMS can compress data and use parallel tasks to reduce time), and then switch to ongoing replication to minimize downtime. The ongoing replication captures changes via Oracle LogMiner or binary logs, allowing the source to remain operational during the migration.

Answer

Create an RDS read replica from the on-premises database

Answer

Take a physical backup of the source database and restore to RDS

Answer

Use Oracle Data Pump to export and import the database

Question 6

A company is planning to migrate a 3 TB PostgreSQL database from an on-premises data center to Amazon Aurora PostgreSQL. The migration must have near-zero downtime. The on-premises database is using a custom pg_hba.conf that restricts access to specific IP ranges. Which combination of steps will meet the requirements?

Accepted Answer

Use AWS DMS with ongoing replication to an Aurora DB cluster. Configure the source endpoint with the appropriate connection settings.. AWS DMS with ongoing replication (CDC) enables near-zero downtime migration by continuously synchronizing changes from the source PostgreSQL database to the target Aurora PostgreSQL cluster after an initial full load. Configuring the source endpoint with the correct connection settings, including the custom pg_hba.conf IP ranges, allows DMS to connect securely. This approach meets the requirement for minimal downtime, unlike batch export/import methods.

Answer

Create an Aurora Replica of the on-premises database using cross-Region replication.

Answer

Use pg_dump and pg_restore to export and import the database during a maintenance window.

Answer

Use AWS SCT to convert the schema and then perform a full data load using AWS DMS.

Question 7

Arrange the steps to migrate an on-premises Oracle database to Amazon RDS for Oracle using AWS DMS (Database Migration Service) in the correct order.

Accepted Answer

Launch the DMS replication instance, then configure the source and target endpoints, then create the migration task, then monitor the migration task.. DMS migration requires setting up the replication instance, configuring endpoints with proper source database settings for CDC, creating a migration task, and monitoring for completion.

Answer

Configure the source and target endpoints, then launch the DMS replication instance, then create the migration task, then monitor the migration task.

Answer

Launch the DMS replication instance, then create the migration task, then configure the source and target endpoints, then monitor the migration task.

Answer

Configure the source and target endpoints, then launch the DMS replication instance, then monitor the migration task, then create the migration task.

Question 8

A company runs an e-commerce platform on AWS using a multi-tier architecture. The application tier consists of Auto Scaling groups of EC2 instances behind an Application Load Balancer. The database tier uses Amazon RDS for MySQL with Multi-AZ deployment. Recently, the operations team noticed that during flash sales, the application becomes unresponsive and users receive 503 errors. The team checks CloudWatch metrics and sees that the RDS instance's CPU utilization spikes to 100%, and the `DatabaseConnections` metric also spikes to the maximum allowed value of 500. The application uses connection pooling with a maximum of 200 connections, but the metric shows 500 connections. The team suspects that the connection pooling configuration is not being honored. The application code is written in Python and uses SQLAlchemy with a connection pool size of 10 per application instance. There are 20 application instances in the Auto Scaling group during peak times. The team wants to resolve the issue without increasing the database instance size. What should the team do?

Accepted Answer

Set the `max_connections` parameter in the RDS parameter group to 200 and configure the application to handle connection errors with retry logic. Setting the `max_connections` parameter in the RDS parameter group enforces a hard limit at the database level, preventing the database from accepting more than 200 connections. With 20 application instances each using a connection pool of 10, the total intended connections are 200. By setting `max_connections` to 200, any excess connection attempts will be rejected, and the application should handle connection errors with retry logic, preventing the database from being overwhelmed. Option A is wrong: reducing the Auto Scaling group's desired capacity to 10 instances would reduce the total connection pool to 100, which might temporarily reduce load but is not a scalable solution and does not address the root cause that the application's connection pooling is not being honored. Option C is wrong: migrating to Amazon Aurora MySQL with Auto Scaling does not directly solve the connection pooling issue. Aurora may allow more connections, but the root cause is that the application is opening more connections than configured, and a migration is a costly change that doesn't fix the configuration problem. Option D is wrong: increasing the SQLAlchemy pool size per instance to 25 would increase the total potential connections to 500 (20 instances × 25), which would worsen the connection spike and exceed the database's maximum, increasing contention and load.

Answer

Reduce the Auto Scaling group's desired capacity to 10 instances during flash sales

Answer

Migrate the database to Amazon Aurora MySQL with Auto Scaling enabled

Answer

Increase the SQLAlchemy pool size to 25 per instance to reduce connection contention

Question 9

A media company uses Amazon ElastiCache for Redis to cache database query results and reduce load on the primary database. The cache hit ratio is low because the cache is purged frequently. The team wants to improve the hit ratio without increasing the cache size. Which strategy should they implement?

Accepted Answer

Increase the TTL for cached entries to reduce early evictions.. Increasing the TTL (Time-To-Live) for cached entries allows them to remain in the cache longer, reducing the frequency of evictions due to expiration. Since the cache is purged frequently, a low TTL is likely causing entries to expire before they can be reused, which directly lowers the hit ratio. By extending the TTL, the team can retain popular entries longer without needing to increase the cache size, as the existing memory is used more efficiently.

Answer

Implement lazy loading to populate cache only on demand.

Answer

Use write-through caching to update cache on every database write.

Answer

Set eviction policy to allkeys-random to spread evictions evenly.

Question 10

A company runs a large-scale e-commerce platform using Amazon RDS for MySQL with a Multi-AZ deployment. The database has a table 'orders' with 200 million rows. Recently, they added a new index on the 'order_date' column to improve reporting queries. After adding the index, they noticed increased write latency and occasional replication lag. The application writes new orders continuously. The table experiences about 10,000 writes per second. The DB instance is db.r5.4xlarge. The index creation was done using the ALTER TABLE statement with a default algorithm. What is the most likely cause of the increased write latency and replication lag?

Accepted Answer

The index was created using the default algorithm (COPY), which locks the table and blocks writes, causing replication lag.. The default algorithm for ALTER TABLE in MySQL is COPY, which creates a new table, copies all rows, and rebuilds indexes. During this process, the table is locked with a write lock, blocking DML operations and causing increased write latency. In a Multi-AZ deployment, the DDL is replicated to the standby, but the lock on the primary delays writes, which can manifest as replication lag when the standby applies the same blocking DDL.

Answer

The index creation DDL statement is not replicated to the standby instance, causing inconsistency.

Answer

The instance size is insufficient for the write workload.

Answer

The new index is causing excessive overhead on write operations due to index maintenance.

Question 11

A company is designing a global e-commerce application that requires a relational database with sub-10ms read latency across multiple AWS Regions. The database will store inventory and product catalog data. Which database design should they choose?

Accepted Answer

Use Amazon Aurora Global Database with a primary cluster in one Region and secondary clusters in other Regions.. Amazon Aurora Global Database is designed for low-latency global reads, with typical replication lag of under 1 second and read latency in the single-digit milliseconds from secondary clusters. It uses a dedicated storage-based replication mechanism that does not impact the performance of the primary cluster, making it ideal for a global e-commerce application requiring sub-10ms reads across multiple AWS Regions.

Answer

Use Amazon DynamoDB Global Tables with eventual consistency.

Answer

Deploy Multi-AZ for Amazon RDS and use Route 53 latency-based routing.

Answer

Set up Cross-Region Read Replicas for Amazon RDS MySQL.

Question 12

A company is migrating a 2 TB Oracle database to Amazon Aurora PostgreSQL. The migration requires ongoing replication for minimal downtime. Which THREE AWS services should be used?

Accepted Answer

AWS Database Migration Service (AWS DMS). AWS DMS is the correct choice because it supports ongoing replication (change data capture) from Oracle to Amazon Aurora PostgreSQL, enabling minimal downtime migration. It can continuously replicate changes from the source Oracle database to the target Aurora PostgreSQL instance until the cutover, allowing the source to remain operational during the migration.

Answer

AWS DataSync

Answer

AWS Lambda

Question 13

A gaming company needs a database to store player session data that is ephemeral and requires sub-millisecond latency. The data can be lost on failure without impact. Which service is best?

Accepted Answer

Amazon ElastiCache for Redis. Amazon ElastiCache for Redis is the best choice because it provides an in-memory data store with sub-millisecond latency, ideal for ephemeral player session data that can be lost on failure. Redis supports data structures like strings and hashes with TTL (time-to-live) expiration, perfectly matching the transient, low-latency requirement without needing durability.

Answer

Amazon DynamoDB

Answer

Amazon RDS for PostgreSQL

Answer

Amazon S3

Question 14

A company is running a production Amazon RDS for MySQL database that is experiencing performance degradation. Amazon CloudWatch metrics show high CPU utilization and high number of connections. The company has already optimized queries and implemented connection pooling. What is the MOST cost-effective solution to address the high CPU utilization?

Accepted Answer

Scale up to a larger DB instance class. Scaling up to a larger DB instance class directly increases the compute capacity (vCPUs and memory) available to the database, which addresses the root cause of high CPU utilization. Since queries are already optimized and connection pooling is in place, the remaining bottleneck is the instance's processing power, making a vertical scale-up the most cost-effective solution to handle the sustained CPU load without introducing additional architectural complexity.

Answer

Add Read Replicas to offload read traffic

Answer

Change the storage type to Provisioned IOPS (io1)

Answer

Enable RDS Proxy to reduce database connections

Question 15

A developer needs to connect to an Amazon RDS for PostgreSQL DB instance from an EC2 instance in the same VPC. What is the most secure way to authenticate the connection without storing database credentials in the application code?

Accepted Answer

Enable IAM database authentication and generate an authentication token.. IAM database authentication for RDS PostgreSQL allows the application to connect using an IAM user or role without storing any database credentials. The authentication token is generated by the AWS SDK and is valid for 15 minutes. This eliminates the need to store credentials in the application code. Option A is incorrect because a hardcoded password is not secure. Option B (Secrets Manager) and Option D (Systems Manager Parameter Store SecureString) both require the application to retrieve a secret at runtime, which still introduces credential management overhead and potential exposure. IAM authentication is the most secure option as it removes static credentials entirely.

Answer

Use a hardcoded password in the application configuration file.

Answer

Store the database password in AWS Secrets Manager and retrieve it at runtime.

Answer

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

Question 16

A company runs an Amazon RDS for SQL Server database. The database size is 500 GB. The company needs to create a test environment with a copy of the production database that refreshes daily. Which THREE steps should be taken to automate this? (Choose THREE.)

Accepted Answer

Use AWS Backup or AWS Lambda to take a manual snapshot of the production DB instance daily.. Creates a manual snapshot of the production DB instance daily using AWS Backup or Lambda. Option D restores that snapshot to a new DB instance in the test environment. Option B updates the test application's connection string to point to the new test instance. Option C is incorrect because a read replica is not a full copy and promoting it would disrupt replication, not provide a daily refreshed copy. Option E is unnecessary because the restored instance can have automated backups enabled, but it is not a required step for the daily refresh process.

Answer

Create a read replica of the production instance and promote it to the test environment.

Answer

Enable automated backups on the test instance after restoration.

Question 17

A team is deploying a new Amazon Aurora MySQL database and needs to load 5 TB of data from an existing Amazon RDS for MySQL database with minimal downtime. The data is stored in InnoDB tables. Which approach is MOST efficient?

Accepted Answer

Create an Aurora read replica from the RDS for MySQL instance using binlog replication. Creating an Aurora read replica from an RDS for MySQL instance using binlog replication allows the Aurora cluster to synchronize with the source database in near real-time. Once the replica lag reaches zero, you can promote the Aurora cluster to become the primary database, achieving minimal downtime. This approach leverages the native MySQL binlog replication, which is efficient for large datasets like 5 TB and avoids the overhead of exporting or snapshotting the entire database.

Answer

Take a snapshot of the RDS for MySQL instance and restore to Aurora

Answer

Use AWS DMS with full load and ongoing replication

Answer

Use mysqldump to export the database and import into Aurora

Question 18

A company is migrating an on-premises MySQL database to Amazon RDS for MySQL. The company wants to minimize application changes. Which endpoint type should the application use after migration?

Accepted Answer

RDS instance endpoint (DNS name). The RDS instance endpoint (DNS name) is the standard connection endpoint for a single RDS DB instance, which is the target of a direct migration from on-premises MySQL to Amazon RDS for MySQL. This endpoint requires no application changes, as the application simply replaces the old on-premises hostname with the RDS instance DNS name, maintaining the same MySQL protocol and connection logic.

Answer

RDS reader endpoint

Answer

RDS cluster endpoint

Answer

RDS console endpoint

Question 19

Which TWO metrics should be monitored to troubleshoot an Amazon RDS for PostgreSQL database that is experiencing high connection count and connection timeouts?

Accepted Answer

DatabaseConnections. Options A and C are correct. DatabaseConnections directly shows the number of concurrent connections to the RDS instance, helping monitor connection count. BurstBalance indicates whether the instance has exhausted its I/O burst credits; if it drops, I/O performance degrades and can cause connection timeouts. Option B (NetworkTransmitThroughput) measures network traffic, not connections. Option D (SwapUsage) tracks memory swapping, which is not a standard RDS metric and does not directly relate to connection timeouts. Option E (ReadLatency) measures I/O read latency, which can affect performance but is not a primary metric for high connection count or connection timeouts.

Answer

NetworkTransmitThroughput

Answer

SwapUsage

Answer

ReadLatency

Question 20

A database specialist runs the CLI command shown. The output indicates the instance is Multi-AZ and available. The application, however, is experiencing intermittent connection timeouts to the database endpoint. What is the most likely cause?

Accepted Answer

A failover occurred due to a Multi-AZ event.. A Multi-AZ failover can cause transient connection timeouts if the application does not have proper retry logic. The instance status shows 'available', so storage is not full (eliminating D). MySQL 8.0.28 is a supported version (eliminating B). The instance class db.r5.xlarge is current generation and available in the region (eliminating C). Therefore, the intermittent timeouts are most likely due to a failover event.

Answer

The MySQL engine version is not supported.

Answer

The DB instance class is not available in the current region.

Answer

The database storage is full.