Accurate & Verified 2023 New AWS-Certified-Database-Specialty Answers As Experienced in the Actual Test!
AWS-Certified-Database-Specialty Certification Sample Questions certification Exam
The DBS-C01 exam consists of multiple-choice and multiple-response questions, and the duration of the exam is 180 minutes. AWS-Certified-Database-Specialty exam fee is $300, and the certification is valid for three years. AWS-Certified-Database-Specialty exam can be taken at a testing center or remotely using an online proctoring service.
NEW QUESTION # 170
An ecommerce company uses Amazon DynamoDB as the backend for its payments system. A new regulation requires the company to log all data access requests for financial audits. For this purpose, the company plans to use AWS logging and save logs to Amazon S3 How can a database specialist activate logging on the database?
- A. Create two trails in AWS CloudTrail. Use Trail1 to monitor DynamoDB control-plane operations. Use Trail2 to monitor DynamoDB data-plane operations.
- B. Use AWS CloudTrail to monitor DynamoDB data-plane operations. Create a DynamoDB stream to monitor control-plane operations. Pass the stream to Amazon Kinesis Data Streams. Use that stream as a source for Amazon Kinesis Data Firehose to store the data in an Amazon S3 bucket.
- C. Use AWS CloudTrail to monitor DynamoDB data-plane and control-plane operations.
- D. Use AWS CloudTrail to monitor DynamoDB control-plane operations. Create a DynamoDB stream to monitor data-plane operations. Pass the stream to Amazon Kinesis Data Streams. Use that stream as a source for Amazon Kinesis Data Firehose to store the data in an Amazon S3 bucket.
Answer: C
Explanation:
Explanation
https://aws.amazon.com/about-aws/whats-new/2021/04/you-now-can-use-aws-cloudtrail-to-log-amazon-dynamo
NEW QUESTION # 171
A company maintains several databases using Amazon RDS for MySQL and PostgreSQL. Each RDS database generates log files with retention periods set to their default values. The company has now mandated that database logs be maintained for up to 90 days in a centralized repository to facilitate real-time and after- the-fact analyses.
What should a Database Specialist do to meet these requirements with minimal effort?
- A. Create an AWS Lambda function to pull logs from the RDS databases and consolidate the log files in an Amazon S3 bucket. Set a lifecycle policy to expire the objects after 90 days.
- B. Modify the RDS databases to publish log to Amazon CloudWatch Logs. Change the log retention policy for each log group to expire the events after 90 days.
- C. Create an AWS Lambda function to download the logs from the RDS databases and publish the logs to Amazon CloudWatch Logs. Change the log retention policy for the log group to expire the events after 90 days.
- D. Write a stored procedure in each RDS database to download the logs and consolidate the log files in an Amazon S3 bucket. Set a lifecycle policy to expire the objects after 90 days.
Answer: B
Explanation:
https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_LogAccess.html
https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_LogAccess.Procedural.UploadtoCloudWatch.htm
https://aws.amazon.com/premiumsupport/knowledge-center/rds-aurora-mysql-logs-cloudwatch/
https://docs.aws.amazon.com/AmazonCloudWatchLogs/latest/APIReference/API_PutRetentionPolicy.html
NEW QUESTION # 172
An online gaming company is planning to launch a new game with Amazon DynamoDB as its data store. The database should be designated to support the following use cases:
Update scores in real time whenever a player is playing the game. Retrieve a player's score details for a specific game session.
A Database Specialist decides to implement a DynamoDB table. Each player has a unique user_id and each game has a unique game_id.
Which choice of keys is recommended for the DynamoDB table?
- A. Create a global secondary index with game_id as the partition key
- B. Create a composite primary key with user_id as the partition key and game_id as the sort key
- C. Create a composite primary key with game_id as the partition key and user_id as the sort key
- D. Create a global secondary index with user_id as the partition key
Answer: B
Explanation:
Explanation
https://aws.amazon.com/blogs/database/amazon-dynamodb-gaming-use-cases-and-design-patterns/
"EA uses the user ID as the partition key and primary key (a 1:1 modeling pattern)."
https://aws.amazon.com/blogs/database/choosing-the-right-dynamodb-partition-key/
"Partition key and sort key: Referred to as a composite primary key, this type of key is composed of two attributes. The first attribute is the partition key, and the second attribute is the sort key."
NEW QUESTION # 173
A company migrated an on-premises Oracle database to Amazon RDS for Oracle. A database specialist needs to monitor the latency of the database.
Which solution will meet this requirement with the LEAST operational overhead?
- A. Create a new DB parameter group that includes the AllocatedStorage, DBInstanceClassMemory, and DBInstanceVCPU variables. Enable RDS Performance Insights
- B. Enable RDS Performance Insights to visualize the database load. Enable Enhanced Monitoring to view how different threads use the CPU
- C. Publish RDS Performance insights metrics to Amazon CloudWatch. Add AWS CloudTrail filters to monitor database performance
- D. Install Oracle Statspack. Enable the performance statistics feature to collect, store, and display performance data to monitor database performance.
Answer: B
Explanation:
Correct answer: C
Explanation from Amazon documents:
Amazon RDS for Oracle is a fully managed relational database service that supports Oracle Database. Amazon RDS for Oracle provides several features to monitor the performance and health of your database, such as RDS Performance Insights, Enhanced Monitoring, Amazon CloudWatch, and AWS CloudTrail.
RDS Performance Insights is a feature that helps you quickly assess the load on your database and determine when and where to take action. RDS Performance Insights displays a dashboard that shows the database load in terms of average active sessions (AAS), which is the average number of sessions that are actively running SQL statements at any given time. RDS Performance Insights also shows the top SQL statements, waits, hosts, and users that are contributing to the database load.
Enhanced Monitoring is a feature that provides metrics in real time for the operating system (OS) that your DB instance runs on. Enhanced Monitoring metrics include CPU utilization, memory, file system, disk I/O, network I/O, process list, and thread count. Enhanced Monitoring allows you to view how different threads use the CPU and how much memory each thread consumes.
By enabling RDS Performance Insights and Enhanced Monitoring for the RDS for Oracle DB instance, the database specialist can monitor the latency of the database with the least operational overhead. This solution will allow the database specialist to use the RDS console or API to enable these features and view the metrics and dashboards without installing any additional software or tools. This solution will also provide comprehensive and granular information about the database load and resource utilization.
Therefore, option C is the correct solution to meet the requirement. Option A is not optimal because publishing RDS Performance Insights metrics to Amazon CloudWatch and adding AWS CloudTrail filters to monitor database performance will incur additional operational overhead and cost. Amazon CloudWatch is a service that collects monitoring and operational data in the form of logs, metrics, and events. AWS CloudTrail is a service that records AWS API calls for your account and delivers log files to you. These services are useful for monitoring performance trends and auditing activities, but they are not necessary for monitoring latency in real time. Option B is not optimal because installing Oracle Statspack and enabling the performance statistics feature will require manual intervention and configuration on the RDS for Oracle DB instance. Oracle Statspack is a tool that collects, stores, and displays performance data for Oracle Database. The performance statistics feature is an option that enables Statspack to collect additional statistics such as wait events, latches, SQL statements, segments, rollback segments, etc. These tools are useful for performance tuning and troubleshooting, but they are not as easy to use as RDS Performance Insights and Enhanced Monitoring. Option D is not relevant because creating a new DB parameter group that includes the AllocatedStorage, DBInstanceClassMemory, and DBInstanceVCPU variables will not help monitor the latency of the database. A DB parameter group is a collection of DB engine configuration values that define how a DB instance operates. The AllocatedStorage parameter specifies the allocated storage size in gibibytes (GiB). The DBInstanceClassMemory parameter specifies the amount of memory available to an instance class in bytes. The DBInstanceVCPU parameter specifies the number of virtual CPUs available to an instance class. These parameters are used to configure the capacity and performance of a DB instance, but they do not provide any monitoring or metrics information. Enabling RDS Performance Insights alone will not provide enough information about the OS-level metrics such as CPU utilization or memory usage.
NEW QUESTION # 174
Recently, a financial institution created a portfolio management service. The application's backend is powered by Amazon Aurora, which supports MySQL.
The firm demands a response time of five minutes and a response time of five minutes. A database professional must create a disaster recovery system that is both efficient and has a low replication latency.
How should the database professional tackle these requirements?
- A. Configure a cross-Region read replica.
- B. Configure a binlog and create a replica in a different AWS Region.
- C. Configure an Amazon Aurora global database and add a different AWS Region.
- D. Configure AWS Database Migration Service (AWS DMS) and create a replica in a different AWS Region.
Answer: C
Explanation:
Explanation
https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/aurora-global-database-disaster-recovery.htm
https://aws.amazon.com/blogs/database/how-to-choose-the-best-disaster-recovery-option-for-your-amazon-auror
https://aws.amazon.com/about-aws/whats-new/2019/11/aurora-supports-in-place-conversion-to-global-database/
NEW QUESTION # 175
An ecommerce company has tasked a Database Specialist with creating a reporting dashboard that visualizes critical business metrics that will be pulled from the core production database running on Amazon Aurora.
Data that is read by the dashboard should be available within 100 milliseconds of an update.
The Database Specialist needs to review the current configuration of the Aurora DB cluster and develop a cost-effective solution. The solution needs to accommodate the unpredictable read workload from the reporting dashboard without any impact on the write availability and performance of the DB cluster.
Which solution meets these requirements?
- A. Add an automatic scaling policy to the DB cluster to add Aurora Replicas to the cluster based on CPUconsumption.
- B. Turn on the serverless option in the DB cluster so it can automatically scale based on demand.
- C. Create a separate DB cluster for the new workload, refresh from the source DB cluster, and set up ongoingreplication using AWS DMS change data capture (CDC).
- D. Provision a clone of the existing DB cluster for the new Application team.
Answer: B
NEW QUESTION # 176
Amazon DynamoDB global tables are being used by a business to power an online gaming game. The game is played by gamers from all around the globe. As the game became popularity, the amount of queries to DynamoDB substantially rose. Recently, gamers have complained about the game's condition being inconsistent between nations. A database professional notices that the ReplicationLatency metric for many replica tables is set to an abnormally high value.
Which strategy will resolve the issue?
- A. Configure a DynamoDB Accelerator (DAX) cluster on each of the replicas.
- B. Configure the primary table to use DynamoDB auto scaling and the replica tables to use manually provisioned capacity.
- C. Configure all replica tables to use DynamoDB auto scaling.
- D. Configure the table-level write throughput limit service quota to a higher value.
Answer: C
Explanation:
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/V2globaltables_reqs_bestpractices.html
NEW QUESTION # 177
An online bookstore uses Amazon Aurora MySQL as its backend database. After the online bookstore added a popular book to the online catalog, customers began reporting intermittent timeouts on the checkout page. A database specialist determined that increased load was causing locking contention on the database. The database specialist wants to automatically detect and diagnose database performance issues and to resolve bottlenecks faster.
Which solution will meet these requirements?
- A. Use the Amazon RDS query editor to get the process ID of the query that is causing the database to lock.
Run a command to end the process. - B. Create a CPU usage alarm. Select the CPU utilization metric for the DB instance. Create an Amazon Simple Notification Service (Amazon SNS) topic to notify the database specialist when CPU utilization is over 75%.
- C. Use the SELECT INTO OUTFILE S3 statement to query data from the database. Save the data directly to an Amazon S3 bucket. Use Amazon Athena to analyze the files for long-running queries.
- D. Turn on Performance Insights for the Aurora MySQL database. Configure and turn on Amazon DevOps Guru for RDS.
Answer: D
Explanation:
Explanation from Amazon documents:
Performance Insights is a feature of Amazon Aurora MySQL that helps you quickly assess the load on your database and determine when and where to take action. Performance Insights displays a dashboard that shows the database load in terms of average active sessions (AAS), which is the average number of sessions that are actively running SQL statements at any given time. Performance Insights also shows the top SQL statements, waits, hosts, and users that are contributing to the database load.
Amazon DevOps Guru is a fully managed service that helps you improve the operational performance and availability of your applications by detecting operational issues and recommending specific actions for remediation. Amazon DevOps Guru applies machine learning to automatically analyze data such as application metrics, logs, events, and traces for behaviors that deviate from normal operating patterns. Amazon DevOps Guru supports Amazon RDS as a resource type and can monitor the performance and availability of your RDS databases.
By turning on Performance Insights for the Aurora MySQL database and configuring and turning on Amazon DevOps Guru for RDS, the database specialist can automatically detect and diagnose database performance issues and resolve bottlenecks faster. This solution will allow the database specialist to monitor the database load and identify the root causes of performance problems using Performance Insights, and receive actionable insights and recommendations from Amazon DevOps Guru to improve the operational performance and availability of the database.
Therefore, option A is the correct solution to meet the requirements. Option B is not sufficient because creating a CPU usage alarm will only notify the database specialist when the CPU utilization is high, but it will not help diagnose or resolve the database performance issues. Option C is not efficient because using the Amazon RDS query editor to get the process ID of the query that is causing the database to lock and running a command to end the process will require manual intervention and may cause data loss or inconsistency. Option D is not efficient because using the SELECT INTO OUTFILE S3 statement to query data from the database and saving the data directly to an Amazon S3 bucket will incur additional time and cost, and using Amazon Athena to analyze the files for long-running queries will not help prevent or resolve locking contention on the database.
NEW QUESTION # 178
The Development team recently executed a database script containing several data definition language (DDL) and data manipulation language (DML) statements on an Amazon Aurora MySQL DB cluster. The release accidentally deleted thousands of rows from an important table and broke some application functionality. This was discovered 4 hours after the release. Upon investigation, a Database Specialist tracked the issue to a DELETE command in the script with an incorrect WHERE clause filtering the wrong set of rows.
The Aurora DB cluster has Backtrack enabled with an 8-hour backtrack window. The Database Administrator also took a manual snapshot of the DB cluster before the release started. The database needs to be returned to the correct state as quickly as possible to resume full application functionality. Data loss must be minimal. How can the Database Specialist accomplish this?
- A. Restore the DB cluster using the manual backup snapshot created before the release and change the application configuration settings to point to the new DB cluster.
- B. Create a clone of the DB cluster with Backtrack enabled. Rewind the cloned cluster to a point in time before the release. Copy deleted rows from the clone to the original database.
- C. Quickly rewind the DB cluster to a point in time before the release using Backtrack.
- D. Perform a point-in-time recovery (PITR) of the DB cluster to a time before the release and copy the deleted rows from the restored database to the original database.
Answer: B
NEW QUESTION # 179
A media company hosts a highly available news website on AWS but needs to improve its page load time, especially during very popular news releases. Once a news page is published, it is very unlikely to change unless an error is identified. The company has decided to use Amazon ElastiCache.
What is the recommended strategy for this use case?
- A. Use ElastiCache for Redis with lazy loading and short time to live (TTL)
- B. Use ElastiCache for Memcached with write-through and long time to live (TTL)
- C. Use ElastiCache for Memcached with lazy loading and short time to live (TTL)
- D. Use ElastiCache for Redis with write-through and long time to live (TTL)
Answer: B
Explanation:
The recommended strategy for this use case is option A: use ElastiCache for Memcached with write-through and long time to live (TTL).
Amazon ElastiCache is a fully managed in-memory data store service that supports two open source engines: Memcached and Redis. Amazon ElastiCache can be used to improve the performance and scalability of web applications by caching frequently accessed data in memory, reducing the load and latency of database queries.
Memcached and Redis have different features and use cases. Memcached is a simple, high-performance, distributed caching system that supports a large number of concurrent connections and large object sizes. Redis is an advanced, feature-rich, in-memory data structure store that supports data persistence, replication, transactions, pub/sub, Lua scripting, and various data types.
For this use case, Memcached is more suitable than Redis because the news website does not need the advanced features of Redis, such as data persistence or replication. The news website only needs a fast and simple caching solution that can handle high traffic and large objects.
Write-through and lazy loading are two common caching strategies that determine when and how data is written to the cache. Write-through is a strategy that writes data to the cache whenever it is written to the database. Lazy loading is a strategy that writes data to the cache only when it is requested for the first time.
For this use case, write-through is more suitable than lazy loading because the news website needs to improve its page load time, especially during very popular news releases. Write-through ensures that the cache always has the most up-to-date data and avoids cache misses or stale data. Lazy loading may cause cache misses or stale data if the data is not cached or updated in time.
Time to live (TTL) is a parameter that specifies how long an item can remain in the cache before it expires and is deleted. TTL can be used to control the cache size and freshness.
For this use case, long TTL is more suitable than short TTL because the news website has a low probability of changing its data once a news page is published. Long TTL allows the data to stay in the cache longer and reduces the frequency of cache updates or evictions. Short TTL may cause unnecessary cache updates or evictions if the data does not change frequently.
Therefore, option A is the recommended strategy for this use case because it uses ElastiCache for Memcached with write-through and long TTL, which provides a fast and simple caching solution that can handle high traffic and large objects, and ensures that the cache always has the most up-to-date and relevant data.
NEW QUESTION # 180
A marketing company is using Amazon DocumentDB and requires that database audit logs be enabled. A Database Specialist needs to configure monitoring so that all data definition language (DDL) statements performed are visible to the Administrator. The Database Specialist has set the audit_logs parameter to enabled in the cluster parameter group.
What should the Database Specialist do to automatically collect the database logs for the Administrator?
- A. Enable DocumentDB Events to export the logs to Amazon CloudWatch Logs
- B. Enable DocumentDB to export the logs to Amazon CloudWatch Logs
- C. Enable DocumentDB to export the logs to AWS CloudTrail
- D. Configure an AWS Lambda function to download the logs using the download-db-log-file-portion operation and store the logs in Amazon S3
Answer: A
Explanation:
https://docs.aws.amazon.com/documentdb/latest/developerguide/event-auditing.html Auditing Amazon DocumentDB Events PDF Kindle RSS With Amazon DocumentDB (with MongoDB compatibility), you can audit events that were performed in your cluster. Examples of logged events include successful and failed authentication attempts, dropping a collection in a database, or creating an index. By default, auditing is disabled on Amazon DocumentDB and requires that you opt in to use this feature.
When auditing is enabled, Amazon DocumentDB records Data Definition Language (DDL), authentication, authorization, and user management events to Amazon CloudWatch Logs. When auditing is enabled, Amazon DocumentDB exports your cluster's auditing records (JSON documents) to Amazon CloudWatch Logs. You can use Amazon CloudWatch Logs to analyze, monitor, and archive your Amazon DocumentDB auditing events.
NEW QUESTION # 181
A gaming company is designing a mobile gaming app that will be accessed by many users across the globe. The company wants to have replication and full support for multi-master writes. The company also wants to ensure low latency and consistent performance for app users.
Which solution meets these requirements?
- A. Use Amazon Aurora for storage and cache the user content with Amazon ElastiCache
- B. Use Amazon Neptune for storage
- C. Use Amazon Aurora for storage and enable cross-Region Aurora Replicas
- D. Use Amazon DynamoDB global tables for storage and enable DynamoDB automatic scaling
Answer: D
NEW QUESTION # 182
A coffee machine manufacturer is equipping all of its coffee machines with 10T sensors. The 10T core application is writing measurements for each record to Amazon Timestream. The records have multiple dimensions and measures. The measures include multiple measure names and values.
An analysis application is running queries against the Timestream database and is focusing on data from the current week. A database specialist needs to optimize the query costs of the analysis application.
Which solution will meet these requirements?
- A. Avoid canceling any query after the query starts running.
- B. Use time range, measure name, and dimensions in the WHERE clause of the query.
- C. Implement exponential backoff in the application.
- D. Ensure that queries contain whole records over the relevant time range.
Answer: B
Explanation:
Use time range, measure name, and dimensions in the WHERE clause of the query.
Explanation from Amazon documents:
Amazon Timestream is a serverless time series database service that allows you to store and analyze time series data at any scale. To optimize the cost of queries, you should use the following best practices1:
Include only the measure and dimension names essential to query. Adding extraneous columns will increase data scans and therefore will also increase the query cost.
Include a time range in the WHERE clause of your query. For example, if you only need the last one hour of data in your dataset, include a time predicate such as time > ago (1h).
Include the measure names in the WHERE clause of the query when a query accesses a subset of measures in a table.
Option B follows these best practices, while option A does not. Option C is incorrect because canceling a query can save on cost if the query will not return the desired results1. Option D is irrelevant because exponential backoff is a technique to handle throttling errors, not to optimize query costs2.
NEW QUESTION # 183
A gaming company has recently acquired a successful iOS game, which is particularly popular during the holiday season. The company has decided to add a leaderboard to the game that uses Amazon DynamoDB.
The application load is expected to ramp up over the holiday season.
Which solution will meet these requirements at the lowest cost?
- A. DynamoDB with on-demand capacity mode
- B. DynamoDB with provisioned capacity mode with Auto Scaling
- C. DynamoDB with DynamoDB Accelerator
- D. DynamoDB Streams
Answer: A
NEW QUESTION # 184
An online gaming company is using an Amazon DynamoDB table in on-demand mode to store game scores.
After an intensive advertisement campaign in South
America, the average number of concurrent users rapidly increases from 100,000 to 500,000 in less than 10 minutes every day around 5 PM.
The on-call software reliability engineer has observed that the application logs contain a high number of DynamoDB throttling exceptions caused by game score insertions around 5 PM. Customer service has also reported that several users are complaining about their scores not being registered.
How should the database administrator remediate this issue at the lowest cost?
- A. Switch the table to provisioned mode and set the throughput to the peak value.
- B. Enable auto scaling and set the target usage rate to 90%.
- C. Switch the table to provisioned mode and enable auto scaling.
- D. Create a DynamoDB Accelerator cluster and use it to access the DynamoDB table.
Answer: C
NEW QUESTION # 185
Amazon Aurora MySQL is being used by an ecommerce business to migrate its main application database.
The firm is now doing OLTP stress testing using concurrent database connections. A database professional detected sluggish performance for several particular write operations during the first round of testing.
Examining the Amazon CloudWatch stats for the Aurora DB cluster revealed a CPU usage of 90%.
Which actions should the database professional take to determine the main cause of excessive CPU use and sluggish performance most effectively? (Select two.)
- A. Enable Enhanced Monitoring at less than 30 seconds of granularity to review the operating system metrics before the next round of tests.
- B. Review Amazon RDS API calls in AWS CloudTrail to identify long-running queries.
- C. Review the VolumeBytesUsed metric in CloudWatch to see if there is a spike in write I/O.
- D. Review Amazon RDS Performance Insights to identify the top SQL statements and wait events.
- E. Enable Advance Auditing to log QUERY events in Amazon CloudWatch before the next round of tests.
Answer: A,D
Explanation:
Explanation
https://aws.amazon.com/premiumsupport/knowledge-center/rds-instance-high-cpu/
https://aws.amazon.com/premiumsupport/knowledge-center/rds-mysql-slow-query/
NEW QUESTION # 186
An electric utility company wants to store power plant sensor data in an Amazon DynamoDB table. The utility company has over 100 power plants and each power plant has over 200 sensors that send data every 2 seconds.
The sensor data includes time with milliseconds precision, a value, and a fault attribute if the sensor is malfunctioning. Power plants are identified by a globally unique identifier. Sensors are identified by a unique identifier within each power plant. A database specialist needs to design the table to support an efficient method of finding all faulty sensors within a given power plant.
Which schema should the database specialist use when creating the DynamoDB table to achieve the fastest query time when looking for faulty sensors?
- A. Create a composite of the plant identifier and sensor identifier as the partition key. Use the measurement time as the sort key. Create a global secondary index (GSI) with the plant identifier as the partition key and the fault attribute as the sort key.
- B. Use the plant identifier as the partition key and the measurement time as the sort key. Create a global secondary index (GSI) with the plant identifier as the partition key and the fault attribute as the sort key.
- C. Create a composite of the plant identifier and sensor identifier as the partition key. Use the measurement time as the sort key. Create a local secondary index (LSI) on the fault attribute.
- D. Use the plant identifier as the partition key and the sensor identifier as the sort key. Create a local secondary index (LSI) on the fault attribute.
Answer: D
Explanation:
Explanation
Plant id as partition key and Sensor id as a sort key. Fault can be identified quickly using the local secondary index and associated plant and sensor can be identified easily.
NEW QUESTION # 187
A large financial services company requires that all data be encrypted in transit. A Developer is attempting to connect to an Amazon RDS DB instance using the company VPC for the first time with credentials provided by a Database Specialist. Other members of the Development team can connect, but this user is consistently receiving an error indicating a communications link failure. The Developer asked the Database Specialist to reset the password a number of times, but the error persists.
Which step should be taken to troubleshoot this issue?
- A. Ensure that the RDS DB instance has not reached its maximum connections limit
- B. Ensure that the connection is using SSL and is addressing the port where the RDS DB instance is listening for encrypted connections
- C. Ensure that the database option group for the RDS DB instance allows ingress from the Developer machine's IP address
- D. Ensure that the RDS DB instance's subnet group includes a public subnet to allow the Developer to connect
Answer: B
Explanation:
Explanation
https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/SQLServer.Concepts.General.SSL.Using.html
NEW QUESTION # 188
A pharmaceutical company's drug search API is using an Amazon Neptune DB cluster. A bulk uploader process automatically updates the information in the database a few times each week. A few weeks ago during a bulk upload, a database specialist noticed that the database started to respond frequently with a ThrottlingException error. The problem also occurred with subsequent uploads.
The database specialist must create a solution to prevent ThrottlingException errors for the database. The solution must minimize the downtime of the cluster.
Which solution meets these requirements?
- A. Take the latest backup, and restore it in a DB cluster of a larger size. Point the application to the newly created DB cluster.
- B. Create a read replica that uses a larger instance size than the primary DB instance. Fail over the primary DB instance to the read replica.
- C. Add a read replica to each Availability Zone. Use an instance for the read replica that is the same size as the primary DB instance. Keep the traffic between the API and the database within the Availability Zone.
- D. Create a read replica that uses a larger instance size than the primary DB instance. Offload the reads from the primary DB instance.
Answer: D
Explanation:
Explanation
https://docs.aws.amazon.com/neptune/latest/userguide/manage-console-add-replicas.html Neptune replicas connect to the same storage volume as the primary DB instance and support only read operations. Neptune replicas can offload read workloads from the primary DB instance.
NEW QUESTION # 189
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