Amazon Web Services Updated DAS-C01 Exam Questions and Answers by erik

• Kafka ACLs are a way to control access to Kafka resources, such as topics, consumer groups, or clusters, based on the principal of the client1. A principal is an identity that can be authenticated by Kafka. In this case, since the Kafka cluster only allows TLS encrypted data, the principal can be derived from the distinguished name of the clients’ TLS certificates2. For example, if a client has a TLS certificate with the subject name CN=app1.example.com,OU=IT,O=Org,L=City,ST=State,C=US, then the principal name will be in the form of CN=app1.example.com,OU=IT,O=Org,L=City,ST=State,C=US3.
• The organization can use Kafka ACLs to configure read and write permissions for each topic. For example, to allow only app1 to write to topic1, the organization can use the following command:

kafka-acls --authorizer-properties zookeeper.connect=zookeeper:2181 --add --allow-principal User:CN=app1.example.com,OU=IT,O=Org,L=City,ST=State,C=US --operation Write --topic topic1

• Similarly, to allow only app2 to read from topic2, the organization can use the following command:

kafka-acls --authorizer-properties zookeeper.connect=zookeeper:2181 --add --allow-principal User:CN=app2.example.com,OU=IT,O=Org,L=City,ST=State,C=US --operation Read --topic topic2

• By using Kafka ACLs, the organization can prevent applications from writing to a topic different than the one they should write to. If an application tries to write to a topic that it does not have permission for, it will get an authorization error.

This solution meets the requirements because:

• AWS Glue is a fully managed extract, transform, and load (ETL) service that can be used to prepare and load data for analytics1. You can use AWS Glue to create a job that copies the CloudTrail logs from the source S3 bucket to a new S3 bucket, and converts them to Apache Parquet format2. Parquet is a columnar storage format that is optimized for analytics and supports compression3. Snappy is a compression codec that provides a good balance between compression ratio and speed4.
• AWS Glue can also create a table based on the Parquet files in the new S3 bucket, and partition the table by date2. Partitioning is a technique that divides a large dataset into smaller subsets based on a partition key, such as date5. Partitioning can improve query performance by reducing the amount of data scanned and filtering out irrelevant data5.
• Amazon Athena is an interactive query service that allows you to analyze data in S3 using standard SQL6. You can use Athena to query the table created by AWS Glue, and specify the partitions you want to query based on the daterange. Athena can leverage the benefits of Parquet format and partitioning to run queries faster and more cost-effectively.

This solution will improve query performance because:

• Apache Parquet is a columnar storage format that is optimized for analytics and supports compression1. Parquet files can reduce the amount of data scanned and transferred by Athena, thus improving performance and reducing cost1.
• The Athena CREATE TABLE AS SELECT (CTAS) statement allows you to create a new table from the results of a SELECT query2. You can use this statement to convert the CSV files to Parquet format and store them in a different location in S32. You can also specify partitioning keys for the new table, which can further improve query performance by filtering out irrelevant data2.
• Querying the Parquet data will be faster and cheaper than querying the CSV data, as Parquet files are more efficient for analytical queries1.

C. Run a daily AWS Glue ETL job to convert the data files to Apache Parquet format and to partition the converted files. Create a periodic AWS Glue crawler to automatically crawl the partitioned data each day.

This solution will improve query performance because:

• AWS Glue is a fully managed extract, transform, and load (ETL) service that can be used to prepare and load data for analytics3. You can use AWS Glue to create a job that copies the CSV files from the source S3 bucket to a new S3 bucket, and converts them to Apache Parquet format3.