DBS-C01 Mock Exam 76 — 25 Questions

Question 1

An IAM policy is attached to a user. What does this policy allow the user to do?

Accepted Answer

Get an item from the Orders table but only return the order_id, customer_id, and status attributes.. The IAM policy allows the GetItem action on the Orders table, with a condition that restricts the returned attributes to order_id, customer_id, and status. This matches option D. Option A is incorrect because the policy does not allow UpdateItem. Option B is incorrect because the policy does not allow Scan (it only allows GetItem). Option C is incorrect because the policy does not allow DeleteItem.

Answer

Update an item in the Orders table.

Answer

Scan the entire Orders table and return all attributes.

Answer

Delete an item from the Orders table.

Question 2

A financial services company uses Amazon RDS for MySQL to store transaction data. The database has a single table 'transactions' with 500 million rows. The table has an auto-increment primary key and an index on 'transaction_date'. The company runs a monthly report that aggregates transactions by account_id and transaction_date. The report query uses a GROUP BY on account_id and transaction_date, and scans the entire table. The query takes over 2 hours to complete and often times out. The DBA suggests creating a materialized view. However, the company wants to minimize operational overhead. Which solution meets the requirements with the LEAST operational overhead?

Accepted Answer

Migrate the reporting workload to Amazon Redshift by loading the transactions table into Redshift and running the report query there.. Amazon Redshift is purpose-built for large-scale analytical queries. By migrating the reporting workload to Redshift, the company offloads the heavy aggregation from the transactional RDS instance to a columnar storage engine that can scan and aggregate 500 million rows efficiently using massively parallel processing (MPP). This approach requires no changes to the existing RDS database and minimizes operational overhead compared to managing a materialized view or manual indexing.

Answer

Increase the RDS instance size to the largest available to improve performance.

Answer

Create a materialized view in MySQL that pre-aggregates the data and refreshes it nightly.

Answer

Add a composite index on (account_id, transaction_date) to speed up the GROUP BY.

Question 3

A company is migrating a 3 TB on-premises Oracle database to Amazon Aurora PostgreSQL using AWS DMS. The migration task is failing with an error indicating insufficient memory. Which TWO actions should the company take to resolve this issue? (Choose TWO.)

Accepted Answer

Increase the instance class of the DMS replication instance.. The 'insufficient memory' error during an AWS DMS migration indicates that the replication instance lacks the memory required to handle the data volume, transformation rules, or cache for large transactions. Increasing the instance class (e.g., from dms.c5.large to dms.c5.2xlarge) provides more memory and CPU, directly resolving the resource constraint.

Answer

Change the target database engine to Amazon RDS for MySQL.

Answer

Disable Multi-AZ on the DMS replication instance.

Answer

Use a smaller instance class for the DMS replication instance.

Question 4

A company wants to migrate its on-premises Oracle database to Amazon Aurora PostgreSQL. The company needs to automatically convert the Oracle schema to PostgreSQL-compatible format. Which AWS service should the company use?

Accepted Answer

AWS Schema Conversion Tool (AWS SCT). AWS Schema Conversion Tool (AWS SCT) is designed specifically to convert database schemas from one engine to another, including Oracle to Amazon Aurora PostgreSQL. It automatically translates Oracle DDL (tables, indexes, stored procedures, functions, etc.) into PostgreSQL-compatible format, handling data type mappings, PL/SQL to PL/pgSQL conversion, and other schema-level transformations. AWS DMS handles data migration, not schema conversion, making SCT the correct choice for this requirement.

Answer

AWS Database Migration Service (AWS DMS) with the Oracle native dump and load option

Answer

AWS Server Migration Service (AWS SMS)

Answer

AWS Database Migration Service (AWS DMS)

Question 5

A company is using Amazon DynamoDB for a gaming leaderboard. The table has a partition key of 'game_id' and a sort key of 'score'. The application performs a query to retrieve the top 10 scores for a given game_id. The query uses ScanIndexForward: false and Limit: 10. Recently, the query response time has increased. The table's read capacity is 1000 RCU, and the average item size is 1 KB. Which is the most likely cause of the increased latency?

Accepted Answer

A hot partition on the game_id key is causing throttling for that specific partition.. The increased latency is most likely due to a hot partition on the 'game_id' key. When a specific game_id receives a disproportionate amount of write or read traffic, that single partition can exceed its throughput limits (1/1000th of provisioned RCU per partition), causing throttling and retries that degrade query response time. Even though the query uses ScanIndexForward: false and Limit: 10, the request is still constrained by the partition's capacity, and throttling at the partition level leads to increased latency.

Answer

The table lacks a global secondary index on game_id, causing a full table scan.

Answer

The query is using strongly consistent reads instead of eventually consistent reads.

Answer

The provisioned read capacity is too low for the query pattern.

Question 6

A company runs an e-commerce platform on Amazon RDS for MySQL with a Multi-AZ deployment. The database has a table 'orders' with 50 million rows. During Black Friday sales, the application experiences severe slowdowns. Analysis shows that the CPU utilization is at 90% and there are many slow queries that perform full table scans on the 'orders' table. The development team has already added indexes on the most queried columns, but the problem persists. The database specialist suspects that the issue is not solely due to missing indexes. They notice that the queries often filter on a combination of 'order_date', 'customer_id', and 'status', and that the data distribution is heavily skewed: 80% of orders are 'completed' status. The 'order_date' range is typically the last 30 days. What should the database specialist do to improve query performance?

Accepted Answer

Partition the 'orders' table by 'status' and 'order_date' and create covering indexes on common query patterns.. Partitioning the 'orders' table by 'status' and 'order_date' can significantly reduce the amount of data scanned, as queries often filter on these columns. With 80% of orders being 'completed', partitioning by status allows queries for non-completed statuses to skip most rows, and range partitioning by order_date (e.g., monthly) further limits scans to relevant time periods. Adding covering indexes on common query patterns (e.g., (status, order_date, customer_id)) can make these partition scans index-only. Option B (read replicas) offloads read traffic but does not fix the slow queries themselves—they would still perform full scans on the replicas. Option C (caching) helps with repeated queries but not with ad-hoc analytical scans that still hit the database. Option D (vertical scaling) provides temporary relief but does not address the root cause of unnecessary full table scans.

Answer

Create multiple read replicas and distribute read traffic.

Answer

Implement an in-memory caching layer using Amazon ElastiCache for frequently accessed data.

Answer

Upgrade the RDS instance to a larger instance class with more vCPUs and memory.

Question 7

A financial services company is migrating an on-premises Oracle database to AWS. The database supports an OLTP application with complex joins, stored procedures, and requires high availability within a single Region. The company wants to minimize licensing costs and use a fully managed service. Which AWS database service should they choose?

Accepted Answer

Amazon Aurora PostgreSQL-Compatible Edition. Amazon Aurora PostgreSQL-Compatible Edition is the correct choice because it is a fully managed, high-availability database service that supports complex joins, stored procedures, and OLTP workloads while minimizing licensing costs. Aurora provides built-in replication across three Availability Zones, automatic failover, and up to 15 read replicas, meeting the high availability requirement without the licensing overhead of commercial databases like Oracle.

Answer

Amazon DynamoDB

Answer

Amazon RDS for Oracle

Answer

AWS Database Migration Service (DMS)

Question 8

A company uses Amazon DynamoDB for a gaming application. During a new game launch, the application experiences high latency and throttling on a table with a partition key of 'user_id' and a sort key of 'timestamp'. The access pattern is to query recent items for a given user. Which TWO design changes can improve performance?

Accepted Answer

Use a composite key with 'game_id' as partition key and 'timestamp' as sort key.. Using a composite key with 'game_id' as partition key and 'timestamp' as sort key distributes traffic more evenly if 'game_id' has high cardinality, reducing hot partitions. Option C is correct because adding a Global Secondary Index (GSI) with a different partition key allows queries to be served from the index, offloading read traffic from the base table. Option A is incorrect because strongly consistent reads do not solve hot partition issues and consume more throughput. Option D is incorrect because increasing read capacity does not address the root cause of a hot partition; the table may still throttle requests to the hot partition. Option E is incorrect because DAX is a caching layer for reads, not writes, and does not resolve partition-level throttling.

Answer

Use strongly consistent reads for all queries.

Answer

Increase the provisioned read capacity for the table.

Answer

Enable DynamoDB Accelerator (DAX) to cache write operations.

Question 9

A company is designing a multi-tenant SaaS application on Amazon RDS for PostgreSQL. Tenants have vastly different data sizes and access patterns. The current design uses a separate schema per tenant, but some tenants experience slow queries while others are fine. Which approach would best isolate tenant performance and simplify management?

Accepted Answer

Use a separate database per tenant.. Using a separate database per tenant provides the strongest resource isolation at the database instance level. This design prevents noisy neighbors—tenants with large data volumes or heavy access patterns from degrading the performance of other tenants—and simplifies management tasks such as backup, restore, and point-in-time recovery on a per-tenant basis. Amazon RDS for PostgreSQL supports multiple databases within a single DB instance, and each database operates with its own catalog, tables, and connection pool, ensuring that query execution and memory allocation are not shared across tenants.

Answer

Use row-level security (RLS) policies within a single schema to restrict tenant data access.

Answer

Keep the current schema design and add a tenant_id index to all tables.

Answer

Use Amazon RDS Proxy to manage connections and improve performance.

Question 10

A developer reports that an application using Amazon DynamoDB is experiencing high latency during peak hours. The table has a provisioned capacity of 500 read capacity units (RCUs) and 500 write capacity units (WCUs). The application uses eventually consistent reads and the table is about 50 GB. The developer notices throttled write requests in CloudWatch. Which action would most effectively reduce write throttling?

Accepted Answer

Increase the provisioned write capacity for the table.. The developer reports throttled write requests, which directly indicates that the provisioned write capacity (500 WCUs) is insufficient to handle the peak write traffic. Increasing the provisioned write capacity for the table is the most direct and effective action to eliminate write throttling, as it raises the limit on write operations per second. Option C is correct because it addresses the root cause—write capacity exhaustion—without introducing unnecessary components or changing read behavior.

Answer

Enable DynamoDB Accelerator (DAX) for the table.

Answer

Create a global secondary index on the table.

Answer

Switch from eventually consistent reads to strongly consistent reads.

Question 11

A company is designing a data lake on Amazon S3 with Amazon Redshift Spectrum for analytics. The data includes JSON logs from web servers. Which THREE design practices should the company follow to optimize query performance and cost?

Accepted Answer

Compress files using gzip or snappy.. Compressing JSON files with gzip or Snappy reduces the data size stored in S3, lowering storage costs and minimizing the amount of data that Redshift Spectrum must scan over the network. Redshift Spectrum can read compressed files directly, and compression often improves query performance by reducing I/O, even though it adds a small CPU overhead for decompression.

Answer

Use many small files to maximize parallelism.

Answer

Create indexes on the S3 data using AWS Glue.

Question 12

Which TWO of the following are best practices for designing a DynamoDB table for high traffic? (Choose 2)

Accepted Answer

Use global secondary indexes for alternate access patterns. Global secondary indexes (GSIs) allow you to define alternate partition and sort keys to support different query patterns without duplicating data. This is a best practice for high-traffic workloads because it enables efficient access to data using multiple access patterns while maintaining a single base table, reducing the need for expensive scans or application-level joins.

Answer

Store large items to reduce the number of items

Answer

Use normalized tables and perform joins in application

Answer

Always use strongly consistent reads for best performance

Question 13

A database administrator is troubleshooting an issue where an Amazon RDS for PostgreSQL DB instance is not allowing connections. The administrator checks the security group and network ACLs, and they are correctly configured. What is the next step to diagnose the issue?

Accepted Answer

Review the DB instance error logs in Amazon CloudWatch. Reviewing the DB instance error logs in Amazon CloudWatch can reveal connection issues such as authentication failures, SSL/TLS errors, or the maximum number of connections being reached. This is a direct diagnostic step. Option A is incorrect because rebooting may temporarily resolve a connection issue but does not help identify the root cause. Option B is incorrect because modifying the parameter group changes configuration settings, which is not a diagnostic action for existing connection problems. Option C is incorrect because creating a snapshot is for backup and recovery, not for troubleshooting current connectivity.

Answer

Reboot the DB instance

Answer

Modify the DB instance's parameter group

Answer

Create a DB snapshot

Question 14

A startup is building a social media application that needs to store user profiles, posts, comments, and likes. The data is highly interconnected, and the team wants to query relationships efficiently, such as 'find all friends of a user who liked a post'. Which database service is best suited for this workload?

Accepted Answer

Amazon Neptune. Amazon Neptune is a fully managed graph database service optimized for highly interconnected data. It supports property graph and RDF models, enabling efficient traversal of relationships such as 'find all friends of a user who liked a post' using Gremlin or SPARQL queries. This makes it the ideal choice for social media applications requiring real-time relationship queries.

Answer

Amazon ElastiCache for Redis

Answer

Amazon DynamoDB

Answer

Amazon RDS for PostgreSQL

Question 15

Refer to the exhibit. A company's production RDS MySQL instance 'mydb' is configured as shown. The application experiences write latency spikes during peak hours. Which action would most effectively reduce write latency?

Accepted Answer

Change the storage type to Provisioned IOPS (io1) and allocate sufficient IOPS.. The RDS MySQL instance uses gp2 storage with 500 GB, providing a baseline of 1500 IOPS (3 IOPS per GB). Write latency spikes during peak hours indicate that the workload is exceeding these IOPS, causing throttling. Changing to Provisioned IOPS (io1) allows allocating a higher, consistent IOPS level that matches the write workload, directly reducing write latency. Option D (Multi-AZ) adds synchronous replication overhead, increasing write latency. Option B (Read Replica) offloads reads, not writes. Option C (increasing storage) raises baseline IOPS but is less efficient and more costly than provisioning exact IOPS with io1.

Answer

Create a Read Replica in a different region.

Answer

Increase the allocated storage to 1 TB to improve baseline IOPS.

Answer

Enable Multi-AZ deployment to provide a standby instance.

Question 16

Which TWO Amazon RDS features can be used to increase the availability of a production database?

Accepted Answer

Cross-Region read replicas with automatic promotion.. Cross-Region read replicas provide a secondary copy of the database in a different AWS Region, which can be manually promoted to a standalone primary instance in the event of a regional outage. This feature increases availability by enabling a disaster recovery strategy that goes beyond a single AWS Region, ensuring business continuity even if the entire primary Region becomes unavailable.

Answer

Enhanced Monitoring and Performance Insights.

Answer

Manual DB snapshot taken every hour.

Answer

Automated backups with a retention period of 35 days.

Question 17

A company is using Amazon RDS for PostgreSQL with automated backups. The security team requires that backups be encrypted at rest. The DB instance is currently unencrypted. What is the most efficient way to enable encryption for future backups?

Accepted Answer

Create a snapshot of the DB instance, copy the snapshot with encryption enabled, and restore the encrypted snapshot to a new DB instance.. The correct method to enable encryption for future backups on an existing unencrypted Amazon RDS for PostgreSQL instance is to create a snapshot of the DB instance, copy the snapshot with encryption enabled, and restore the encrypted snapshot to a new DB instance. Option A is incorrect because there is no 'backup_encryption' parameter in the DB parameter group. Option B is incorrect because modifying the DB instance does not allow enabling encryption on an unencrypted instance; encryption can only be enabled at creation time. Option C is incorrect because enabling encryption on the S3 bucket does not encrypt the RDS backups themselves; the backups must be encrypted at the source.

Answer

Enable encryption by setting the 'backup_encryption' parameter in the DB parameter group.

Answer

Modify the DB instance to enable encryption.

Answer

Enable encryption on the S3 bucket where backups are stored.

Question 18

A company wants to encrypt data at rest for an existing Amazon RDS for Oracle DB instance. The database is currently unencrypted. What is the simplest way to enable encryption with minimal downtime?

Accepted Answer

Create a snapshot of the DB instance, copy the snapshot with encryption enabled, and restore the encrypted snapshot to a new DB instance.. You cannot directly enable encryption on an existing unencrypted Amazon RDS instance. The correct process is to create a snapshot of the DB instance, copy the snapshot with encryption enabled, and then restore the encrypted snapshot to a new DB instance. You then redirect traffic to the new instance. Option A is incorrect because creating a read replica does not encrypt the master instance, and the replica can only be encrypted if the master is already encrypted. Option B is incorrect because you cannot modify an existing DB instance to enable encryption through the RDS console. Option D is incorrect because enabling encryption directly on the existing DB instance is not supported.

Answer

Create an encrypted read replica and promote it to a standalone instance.

Answer

Modify the DB instance and enable encryption using the RDS console.

Answer

Enable encryption directly on the existing DB instance by modifying the DB instance settings.

Question 19

A company is migrating a 100 GB MySQL database to Amazon Aurora MySQL. The migration must have minimal downtime and the source database is currently in use. Which approach should the company take?

Accepted Answer

Use AWS DMS with ongoing replication from the source MySQL database to Aurora.. AWS DMS with ongoing replication (change data capture, CDC) is the correct approach because it allows a live migration with minimal downtime. DMS performs a full load of the 100 GB database and then continuously replicates incremental changes from the source MySQL to the target Aurora MySQL until you cut over, keeping the source fully operational throughout the process.

Answer

Create an Aurora Replica from the on-premises MySQL database and promote it.

Answer

Export the database using mysqldump and import it into Aurora during a maintenance window.

Answer

Take a physical backup of the MySQL database, upload to S3, and restore to Aurora.

Question 20

A company is designing a database for an IoT application that ingests millions of sensor readings per second. Each reading is a small JSON document (less than 1 KB) and must be stored with low latency. Queries are primarily by device ID and timestamp range. The team expects to rarely update or delete old data. Which AWS database solution is MOST cost-effective and performant?

Accepted Answer

Amazon DynamoDB with a composite primary key (device_id, timestamp). Amazon DynamoDB with a composite primary key (device_id, timestamp) is the most cost-effective and performant solution because it provides single-digit millisecond latency for point lookups and range queries, scales horizontally to handle millions of writes per second, and its on-demand or auto-scaling capacity model avoids over-provisioning. The access pattern of querying by device ID and timestamp range maps directly to DynamoDB's partition and sort key design, enabling efficient use of the Query API without scanning.

Answer

Amazon S3 with a partition prefix of device_id/timestamp/

Answer

Amazon Redshift with distribution key on device_id

Answer

Amazon RDS for MySQL with multiple read replicas