Question 1

A company's security team mandates that their Amazon RDS databases should only accept connections from specific, known IP addresses to ensure security. As a data engineer, you are tasked with implementing this requirement for an RDS instance that will be accessed by multiple clients located in different geographical locations, each with a fixed set of IP addresses.

Which of the following would be the most effective and secure way to comply with this security requirement?

Options :

A : Implement a network Access Control List (ACL) with rules to allow the known IP addresses and deny all others, applying these to the subnet associated with the RDS instance.

B : Configure AWS WAF with a set of rules to allowlist the specific IP addresses, and associate these rules with the RDS instance.

C : Utilize AWS Identity and Access Management (IAM) policies to restrict database access to the specific IP addresses.

D : Modify the inbound rules of the RDS instance-s security group to allow traffic from the known IP addresses and deny all other traffic.

Answer: D

Question 2

A Data Engineering team is planning to perform sampling on a large dataset stored in Amazon S3 for exploratory data analysis. Their goal is to understand the overall trends without processing the entire dataset. The dataset is structured and spread across multiple S3 objects.

Which AWS service and method should the team use to implement an efficient and cost-effective sampling strategy?

Options :

A : Implement AWS Glue with a custom Python script to sequentially scan through each S3 object and randomly pick samples from each.

B : Leverage AWS Data Pipeline to orchestrate and move subsets of the data into Amazon RDS, where sampling can be done using SQL queries.

C : Use Amazon S3 Select to efficiently sample individual records from each S3 object, thus reducing the amount of data loaded and processed.

D : Configure Amazon Redshift Spectrum to load the full dataset into a Redshift cluster, and then use SQL queries to perform random sampling.

Answer: C

Question 3

A digital marketing agency wants to collect, analyze, and visualize web traffic data from their diverse portfolio of client websites for enhanced marketing insights. The solution needs to handle large volumes of data, offer powerful search capabilities, and provide an interactive dashboard for visualization and analysis.

Which combination of AWS services should the agency use to collect, search, analyze, and visualize the web traffic data?

Options :

A : Use Amazon Kinesis Data Firehose for data collection, Amazon OpenSearch Service for search and analysis, and Amazon QuickSight for visualization.

B : Implement Amazon MSK for data streaming, Amazon Redshift for data analysis, and Amazon OpenSearch Service for visualization.

C : Use AWS Direct Connect for data ingestion, Amazon RDS for data storage and querying, and Amazon OpenSearch Service for visualization.

D : Set up Amazon S3 for data storage, AWS Glue for data ETL, and Amazon OpenSearch Service for search, analysis, and visualization.

Answer: A

Question 4

A financial services company is in need of an enhanced storage solution for their transactional relational database system. The solution must ensure high durability, strong consistency, and enhanced read performance for real-time analytics. Additionally, the company needs to maintain high availability and disaster recovery capabilities. Cost management is also a priority, but not at the expense of these performance characteristics. The company's current infrastructure does not require multiple geographical regions.

Which combination of AWS storage services and features should the consultant recommend to meet these requirements? (Select TWO)

Options :

A : Use Amazon DynamoDB with provisioned capacity to manage cost while offering built-in high availability and durability.

B : Implement Amazon EFS with lifecycle management policies to transition older transaction data to EFS Infrequent Access.

C : Utilize Amazon ElastiCache to improve read performance and reduce the load on the primary transaction database.

D : Deploy Amazon Aurora Global Database for high performance, availability, and cross-region disaster recovery.

E : Enable Amazon RDS Multi-AZ deployments for high availability and durability with synchronous data replication.

Answer: C,E

Question 5

A Cloud Data Engineer is troubleshooting a batch processing workflow where Amazon EC2 instances intermittently fail to process and load transformed data into an Amazon RDS instance. The EC2 instances transform data using a Python script and should handle varying loads efficiently. The Data Engineer observes that the EC2 instances are not scaling as expected, leading to timeouts and failed data loads during peak hours.

Which actions should the Data Engineer take to identify and rectify the scaling issues and prevent future timeouts and load failures? (Select TWO)

Options :

A : Transition to AWS Lambda for data transformation, using its automatic scaling to manage the varying load without manual intervention.

B : Increase the instance size of the EC2 instances to provide more consistent performance under peak loads.

C : Implement Amazon CloudWatch alarms to monitor EC2 CPU utilization and trigger scaling events more effectively.

D : Modify the EC2 Auto Scaling group policies to better match the workload patterns, ensuring that scaling occurs in anticipation of load increases.

E : Optimize the Python data transformation script to decrease the execution time and reduce the processing load on each EC2 instance.

Answer: C,D

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