DBS-C01 Practice Test 3 — 25 Questions

Question 1

A company has a 100 GB MySQL database on an EC2 instance. They want to migrate to Amazon RDS for MySQL with minimal downtime. They have set up replication from the source to the target using MySQL native replication. After enabling replication, the 'Seconds_Behind_Master' value is increasing. The source database is write-heavy. What should the team do to reduce replication lag?

Accepted Answer

Increase the RDS instance size to a larger instance class.. The replication lag is increasing because the RDS instance is not powerful enough to apply changes from the write-heavy source as fast as they arrive. Increasing the RDS instance class (option C) provides more CPU and memory resources, allowing the replica to apply transactions more quickly and reduce lag. Option A (tuning the source) might help but is not the most direct solution if the target is the bottleneck. Option B (Multi-AZ) improves availability, not replication performance. Option D (AWS DMS) is an alternative migration tool but does not directly address lag in an existing native replication setup.

Answer

Tune the source database to reduce write load.

Answer

Enable Multi-AZ on the RDS instance.

Answer

Switch to AWS DMS for migration.

Question 2

A social media company runs a large Amazon DynamoDB table (Users) with 10 TB of data. The table uses on-demand capacity. Recently, the application started experiencing occasional ProvisionedThroughputExceeded exceptions during read-heavy periods. The table's read metrics show that consumed read capacity is consistently below 50% of provisioned capacity. The application uses eventually consistent reads. The table has a global secondary index (GSI) on the 'status' attribute. The GSI's read capacity consumption is often at 100% of its provisioned capacity. What is the most likely cause of the throttling?

Accepted Answer

The GSI is throttling because its read capacity is not set to on-demand, or the GSI's partition key is causing hot partitions.. The GSI has its own read capacity settings. If the GSI is throttled, reads on the base table that require the GSI may also be throttled. Option C is correct because the GSI is likely using provisioned capacity, not on-demand, and its read capacity is often at 100%, causing throttling. Option A is incorrect because on-demand capacity mode for the base table is not the issue; the issue is the GSI. Option B is incorrect because the base table's read capacity is not the bottleneck (consumed read capacity is below 50%). Option D is incorrect because using strongly consistent reads would increase read consumption, not reduce throttling.

Answer

The on-demand capacity mode is not suitable for this workload; switch to provisioned with auto scaling.

Answer

The base table's read capacity is insufficient despite on-demand mode.

Answer

The application should use strongly consistent reads to reduce throttling.

Question 3

A company is migrating an on-premises Oracle database to Amazon RDS for Oracle. The database is 2 TB in size and has a 100 Mbps internet connection. The migration must be completed within 3 days with minimal downtime. Which approach is MOST suitable?

Accepted Answer

Use AWS Database Migration Service (DMS) with a full load from an AWS Snowball device, then ongoing replication.. Option B is correct because the 2 TB database cannot be fully loaded over a 100 Mbps internet connection within 3 days (theoretical max transfer ~2.6 TB in 3 days, but real-world throughput is lower due to overhead and contention). AWS Snowball provides a physical appliance to transfer the full load offline, bypassing bandwidth constraints, and then AWS DMS ongoing replication captures and applies changes with minimal downtime.

Answer

Export the database as a dump file, upload to S3, and restore to RDS.

Answer

Use AWS DMS with full load over the internet, then ongoing replication.

Answer

Create a VPN connection to AWS and use Oracle Data Pump over the VPN.

Question 4

A database specialist is troubleshooting an Amazon RDS for SQL Server instance that is experiencing high CPU utilization. The instance has multiple databases. Which TWO actions should the specialist take to identify the cause?

Accepted Answer

Use Performance Insights to identify top SQL queries. Options B and E are correct because Performance Insights helps identify top SQL queries causing high CPU, and Enhanced Monitoring provides OS-level metrics (like CPU utilization per database process) to pinpoint the source. Option A is wrong: read replicas offload read traffic but do not diagnose CPU issues. Option C is wrong: increasing instance size is a remediation, not a diagnostic step. Option D is wrong: changing to a burstable instance class is also a remediation, not diagnostic.

Answer

Create a read replica to offload read traffic

Answer

Increase the instance size to handle the load

Answer

Modify the DB instance class to a burstable type

Question 5

A company is designing a database for an e-commerce application that needs to store product catalog data. The data is highly structured with relationships between products, categories, and suppliers. The application requires ACID transactions to maintain data integrity when updating inventory. The company expects moderate read and write traffic. Which AWS database service is MOST suitable for this workload?

Accepted Answer

Amazon RDS for MySQL. Amazon RDS for MySQL is the most suitable choice because it provides a fully managed relational database that supports ACID transactions, which are essential for maintaining data integrity during inventory updates. The highly structured nature of product catalog data with relationships between products, categories, and suppliers maps naturally to MySQL's relational model with foreign keys and joins. RDS for MySQL handles moderate read/write traffic efficiently and offers features like Multi-AZ for high availability and read replicas for scaling reads.

Answer

Amazon ElastiCache for Redis

Answer

Amazon Neptune

Answer

Amazon DynamoDB

Question 6

A database specialist sees the above error log entries from an Amazon RDS for MySQL DB instance. Which action should be taken to resolve the issue?

Accepted Answer

Restore the DB instance from the latest automated snapshot.. The error log entries indicate corruption in the InnoDB tablespace, likely due to a crash or hardware failure. Restoring from the latest automated snapshot is the correct action because it provides a consistent, point-in-time recovery of the entire database, including all table structures and data, without relying on potentially corrupted files. This approach ensures data integrity and avoids further damage that could occur from attempting repairs on a corrupted instance.

Answer

Increase the allocated storage for the DB instance.

Answer

Reboot the DB instance to clear the error.

Answer

Run the mysqlcheck command to repair the corrupted tables.

Question 7

A social media analytics company uses Amazon DynamoDB as the primary data store for user session data. Each session record has a partition key of user_id (String) and a sort key of session_start_time (Number, epoch). The application often queries the most recent 10 sessions for a given user. The traffic pattern shows that 90% of reads are for the last 10 sessions, while 10% are for historical sessions. The table has a provisioned read capacity of 5000 RCU and consistently experiences throttled read requests during peak hours. The company wants to optimize read performance without changing the provisioned capacity. Which design change will MOST improve read performance for this workload?

Accepted Answer

Create a Global Secondary Index (GSI) with the same partition key and a sort key of session_start_time, but query with ScanIndexForward=false and Limit=10.. Option A is correct because creating a GSI with the same partition key (user_id) and sort key (session_start_time) allows you to query with ScanIndexForward=false and Limit=10 to efficiently retrieve only the most recent 10 sessions per user. This avoids scanning all sessions for a user, reducing consumed read capacity and eliminating throttling without increasing provisioned RCU. The GSI also supports the 90% workload pattern by providing a targeted index that minimizes read unit consumption.

Answer

Increase the provisioned read capacity to 10000 RCU to handle the peak load.

Answer

Enable DynamoDB Accelerator (DAX) with default settings to cache the most recent sessions.

Answer

Configure Amazon ElastiCache for Redis as a read-through cache for session data.

Question 8

A company is designing a new e-commerce platform using Amazon DynamoDB. The workload requires single-digit millisecond latency for user session data, which is accessed by session token. The session data is temporary and should be automatically deleted after 24 hours. Which DynamoDB design should the database specialist recommend?

Accepted Answer

Enable DynamoDB Time to Live (TTL) on the session token attribute. DynamoDB Time to Live (TTL) automatically deletes expired items after a specified timestamp, making it ideal for session data that must be removed after 24 hours. This approach requires no additional infrastructure, meets the single-digit millisecond latency requirement by using the session token as the primary key, and ensures automatic cleanup without manual intervention or added cost.

Answer

Create an AWS Lambda function that runs every hour and deletes expired session data

Answer

Store session data in Amazon S3 with a lifecycle policy to delete objects after 24 hours

Answer

Use DynamoDB Accelerator (DAX) to cache session data and set a 24-hour TTL on the cache

Question 9

A company is running a critical application on Amazon DynamoDB. The table has a partition key of 'user_id' and a sort key of 'timestamp'. The application frequently queries for all items for a given user within a date range. The read capacity is often throttled during peak hours. Which THREE steps should the database specialist take to resolve the throttling?

Accepted Answer

Enable DynamoDB adaptive capacity to automatically adjust throughput. Option A is correct because DynamoDB adaptive capacity automatically manages throughput to accommodate uneven access patterns, such as when a single 'user_id' partition receives more reads than provisioned. It allows the table to absorb throttling by redistributing unused capacity from other partitions, which directly addresses the peak-hour throttling without manual intervention.

Answer

Change the partition key to 'timestamp' to improve read distribution

Answer

Decrease the provisioned write capacity units (WCU) to free up resources for reads

Question 10

A company is designing a multi-tenant SaaS application on Amazon Aurora MySQL. Each tenant has its own database, but some tenants are very large and generate high write traffic. The company wants to isolate tenant workloads to prevent a noisy neighbor from affecting other tenants. Which TWO design strategies should the database specialist recommend?

Accepted Answer

Use Aurora Serverless for tenants with variable workloads. Option A is correct because Aurora Serverless automatically scales compute capacity based on application demand, which is ideal for tenants with variable workloads. This prevents a noisy neighbor scenario by ensuring that a tenant's burst of write traffic does not consume shared resources that would degrade performance for other tenants.

Answer

Use a single Aurora cluster with read replicas for each tenant

Answer

Migrate all tenants to Amazon DynamoDB and use DynamoDB Accelerator (DAX) for caching

Answer

Use Amazon RDS Proxy to pool connections and limit throughput per tenant

Question 11

A financial services company is migrating its Oracle database to Amazon Aurora PostgreSQL. The database runs a critical batch processing job every night that updates millions of rows. The company needs the migration to minimize downtime and ensure data integrity. Which AWS service should the database specialist use to perform the migration?

Accepted Answer

AWS Database Migration Service (AWS DMS) with ongoing replication from Oracle to Aurora PostgreSQL. AWS DMS with ongoing replication (change data capture, CDC) is the correct choice because it enables a near-zero-downtime migration by continuously replicating changes from the source Oracle database to the target Aurora PostgreSQL while the source remains fully operational. After the initial full load, DMS applies ongoing transactions, allowing you to cut over with minimal interruption. This directly addresses the requirement to minimize downtime for the nightly batch job and ensures data integrity through transactional consistency.

Answer

AWS Data Pipeline to export data from Oracle and import into Aurora PostgreSQL

Answer

AWS Schema Conversion Tool (AWS SCT) to convert the schema and then use native PostgreSQL tools to migrate data

Answer

AWS Glue to extract data from Oracle and load into Aurora PostgreSQL

Question 12

A company is designing a multi-tenant SaaS application on Amazon RDS for PostgreSQL. Each tenant's data must be isolated for security and performance. The application has millions of tenants, with most tenants having small datasets (under 100 MB). Which database design pattern is MOST cost-effective and operationally efficient?

Accepted Answer

Use a single RDS instance with a shared schema and implement Row-Level Security (RLS) policies based on tenant_id.. Option B is correct because using a single RDS for PostgreSQL instance with Row-Level Security (RLS) allows you to isolate tenant data at the row level based on a tenant_id column, without the overhead of managing millions of separate schemas or tables. This design is both cost-effective (single instance, no per-tenant provisioning) and operationally efficient (simple schema management, no connection pooling issues), while still meeting security and performance isolation requirements for small datasets under 100 MB.

Answer

Use Amazon DynamoDB with a separate table per tenant.

Answer

Use a single RDS instance with a separate schema per tenant.

Answer

Use a separate Amazon RDS for PostgreSQL instance per tenant.

Question 13

A company is migrating an on-premises PostgreSQL database to Amazon RDS for PostgreSQL. The database has a large table that is frequently accessed by reporting queries. The reporting queries filter on a column that has a high cardinality but low selectivity. To optimize query performance on this table, which design choice should the database specialist recommend?

Accepted Answer

Create a covering index on the filter column. Option D is correct because a covering index includes all columns needed by the reporting queries, allowing PostgreSQL to satisfy the query entirely from the index without accessing the heap (table) pages. This eliminates the overhead of random I/O for row lookups, which is especially beneficial when filtering on a high-cardinality, low-selectivity column where many rows match but the index scan alone can return the required data. In Amazon RDS for PostgreSQL, this reduces read IOPS consumption and improves query latency.

Answer

Partition the table by the filter column

Answer

Use a read replica to offload reporting queries

Answer

Increase the provisioned read IOPS for the RDS instance

Question 14

A social media application uses Amazon DynamoDB as its primary data store. The application stores user posts and allows users to retrieve the most recent 10 posts of users they follow. The access pattern is a followee-based query that needs to be highly scalable and low-latency. Which DynamoDB table design should the database specialist recommend?

Accepted Answer

Use a composite primary key with a partition key of follower ID and a sort key of timestamp, and store the followee ID as an attribute. Option C is correct because it models the access pattern directly: the follower ID as the partition key ensures all posts from followed users are co-located, and the sort key of timestamp allows efficient retrieval of the most recent 10 posts via a Query with a limit of 10 and descending order. This design avoids expensive scans or secondary index lookups, meeting the low-latency and scalability requirements.

Answer

Use a partition key of post ID and a local secondary index on the followee ID

Answer

Use a single table with a scan operation and filter on the followee attribute

Answer

Design the table with a partition key of user ID and a sort key of timestamp, and create a global secondary index (GSI) on followee ID

Question 15

A gaming company uses Amazon DynamoDB for player session data. Each session has a partition key of `game_id` and a sort key of `session_id`. The table has a global secondary index (GSI) on `player_id` for leaderboard queries. Recently, the company noticed that write traffic to the GSI is causing throttling on the base table, even though the base table's write capacity is not fully utilized. What is the MOST likely cause?

Accepted Answer

The GSI is not designed with a high-cardinality partition key, causing write hot spots on the GSI.. The correct answer is B. A global secondary index (GSI) has its own provisioned read and write capacity, separate from the base table. If the GSI's partition key (player_id) has low cardinality (e.g., only a few distinct player_id values), writes to the base table will concentrate on a small number of GSI partitions, causing throttling on the GSI. This throttling on the GSI then back-pressures the base table, resulting in write throttling on the base table even if its own write capacity is underutilized.

Answer

The application is using strongly consistent reads on the GSI, which consumes double the read capacity.

Answer

Point-in-time recovery (PITR) is enabled, consuming extra write capacity.

Answer

The table's auto-scaling settings are not configured correctly for the GSI.

Question 16

A company is migrating a 500 GB MySQL database from on-premises to Amazon RDS for MySQL. The migration must have minimal downtime and support ongoing replication. Which AWS service should be used?

Accepted Answer

Use AWS Database Migration Service (DMS) with a full load and ongoing replication from a change data capture source.. AWS DMS is the correct choice because it supports both a full load of the 500 GB database and ongoing replication using change data capture (CDC) from the on-premises MySQL source. This enables minimal downtime by keeping the target RDS instance synchronized during the migration window, and it handles schema conversion automatically for MySQL-to-MySQL migrations without needing a separate tool.

Answer

Use mysqldump to export the database and import to RDS during a maintenance window.

Answer

Use AWS Schema Conversion Tool (SCT) to convert the schema and migrate data.

Answer

Take a physical backup, copy it to Amazon S3, and restore to RDS.

Question 17

A database specialist is analyzing an Aurora MySQL error log and finds the above deadlock error. The application performs an update on the orders table and then updates the inventory table within the same transaction. The deadlock occurs when two concurrent transactions try to update orders and inventory in different orders. Which design change should the database specialist recommend to reduce deadlocks?

Accepted Answer

Ensure all transactions update tables in the same order (e.g., always update inventory first, then orders). Option B is correct because deadlocks in Aurora MySQL often occur when concurrent transactions acquire row-level locks on tables in different orders. By enforcing a consistent lock order (e.g., always updating inventory first, then orders), the database can avoid circular wait conditions, which are a necessary condition for deadlocks. This is a standard best practice for reducing deadlocks in InnoDB, which uses row-level locking and two-phase locking.

Answer

Combine the orders and inventory tables into a single table to avoid multiple table locks

Answer

Use SELECT ... FOR UPDATE on both tables before updating

Answer

Change the transaction isolation level to READ UNCOMMITTED

Question 18

A company is using Amazon DynamoDB for a shopping cart application. The table has a partition key of `user_id` and a sort key of `item_id`. The application performs frequent updates to the `quantity` attribute. The company notices that write requests are being throttled during peak hours. Which TWO actions would help reduce throttling? (Choose two.)

Accepted Answer

Increase the provisioned write capacity for the table.. Option A is correct because increasing the provisioned write capacity directly raises the number of write capacity units (WCUs) available per second, allowing more write requests to succeed without being throttled. Since the application performs frequent updates to the `quantity` attribute, which consumes write capacity, adding more capacity alleviates throttling during peak hours.

Answer

Use conditional writes to prevent overwrites.

Answer

Enable DynamoDB Streams to process writes asynchronously.

Answer

Enable DynamoDB Accelerator (DAX) for the table.

Question 19

A company is running a MySQL database on Amazon RDS and needs to store JSON documents that are frequently queried by fields within the JSON. The company wants to reduce development complexity and improve query performance. Which RDS MySQL feature should the database specialist recommend?

Accepted Answer

Use the JSON data type in MySQL 8.0 and utilize JSON path expressions in queries. Option B is correct because MySQL 8.0's native JSON data type stores JSON documents in an optimized binary format, enabling efficient indexing and querying via JSON path expressions (e.g., `JSON_EXTRACT`, `->`, `->>`). This reduces development complexity by allowing direct SQL access to JSON fields without application-level parsing, and improves query performance through generated columns and virtual indexes.

Answer

Migrate the JSON data to Amazon DynamoDB and use DynamoDB's document model

Answer

Store JSON documents in a VARCHAR(MAX) column and use LIKE operations for queries

Answer

Store JSON documents as BLOBs and parse them in application code

Question 20

A company is migrating a MySQL database to Amazon Aurora MySQL. The current database uses multi-statement transactions with read committed isolation level. The application frequently encounters deadlocks on the source database. Which Aurora MySQL feature can help reduce deadlocks without application changes?

Accepted Answer

Use Amazon RDS Proxy to pool and share database connections.. RDS Proxy helps reduce deadlocks by pooling and reusing database connections, which minimizes the overhead of establishing new connections and reduces contention on database resources. In MySQL, deadlocks often occur when multiple transactions compete for the same resources under high connection churn; by maintaining a stable pool of connections, RDS Proxy lowers the probability of concurrent conflicting locks. Since the proxy is transparent to the application, no code changes are required to benefit from this behavior.

Answer

Use Amazon Aurora Auto Scaling to automatically adjust the number of replicas.

Answer

Use Amazon Aurora Global Database to replicate data to multiple regions.

Answer

Use Amazon Aurora Backtrack to quickly revert transactions.