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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Operations and Support | 22% | - Monitor and troubleshoot data pipelines
- Automate operational tasks - Backup, restore, and disaster recovery |
| Topic 2: Data Ingestion and Transformation | 34% | - Ingest data from various sources
|
| Topic 3: Data Security and Governance | 18% | - Implement access control and authentication
- Enforce compliance and data governance
|
| Topic 4: Data Store Management | 26% | - Optimize storage performance and cost - Manage data lifecycle and storage tiers - Design and implement data storage solutions
|
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NEW QUESTION # 84
A company uses AWS Glue jobs to implement several data pipelines. The pipelines are critical to the company.
The company needs to implement a monitoring mechanism that will alert stakeholders if the pipelines fail.
Which solution will meet these requirements with the LEAST operational overhead?
Answer: A
Explanation:
Creating an EventBridge rule that triggers a Lambda function on AWS Glue job failure events and then sends notifications via Amazon SNS is the most direct and operationally efficient method:
"Practice Quiz 10: A data engineer must monitor the data pipeline... Which solution will meet these requirements?
A: Inspect the job run monitoring section of the AWS Glue console.
-Ace the AWS Certified Data Engineer - Associate Certification - version 2 - apple.pdf Although this reference directly supports using AWS Glue's monitoring features via EventBridge, it implies that solutions likeA-which directly use EventBridge failure events for automation-are more optimal and less complex than constructing custom logs and metrics.
NEW QUESTION # 85
A company is uploading log files from on-premises servers to an Amazon S3 bucket. The company needs to validate that the logs from the on-premises servers are the same as the logs that are stored in the S3 bucket.
Which solution will meet this requirement?
Answer: C
Explanation:
Amazon S3 natively supports checksum validation during uploads when objects are uploaded by using the AWS SDK. The SDK can automatically calculate a checksum, such as CRC32, on the client side and send it with the upload request. Amazon S3 validates the checksum upon receipt and stores it with the object, ensuring that the data uploaded is exactly the same as the source data.
Storing the checksum in the S3 object metadata provides a lightweight and cost-effective way to verify data integrity without requiring additional compute, storage, or post-processing steps. This approach validates the logs at upload time, which is the most efficient and reliable method.
Using AWS Lambda to calculate SHA-256 checksums would require additional compute, orchestration, and storage, increasing cost and operational complexity. Amazon S3 Object Lock enforces immutability and retention but does not validate data integrity between source and destination. Governance or compliance mode Object Lock cannot detect whether uploaded data matches the original logs.
Therefore, using the AWS SDK checksum validation during upload is the simplest, most efficient, and AWS- recommended approach for ensuring log integrity.
NEW QUESTION # 86
A company is developing a log streaming pipeline that uses Amazon Data Firehose. The pipeline streams Amazon CloudWatch Logs data to an Amazon S3 bucket. The company ' s analytics team needs to use the data in audits. The pipeline must deliver only the relevant logs to the S3 bucket in a compatible format for the team ' s analysis.
Which solution will meet these requirements and maintain reliable performance?
Answer: C
Explanation:
Option B is correct because CloudWatch Logs subscription filters are the native way to send only matching log events to a downstream destination such as Amazon Data Firehose. AWS states that a subscription filter defines the filter pattern for which log events get delivered and where they are sent. AWS also documents that CloudWatch Logs events can be sent to Firehose by using subscription filters. This directly satisfies the requirement to deliver only relevant logs. Once the logs are in Firehose, AWS documents that Firehose can invoke an AWS Lambda function to transform incoming source data before delivering it to the destination, which satisfies the requirement to deliver the logs in a compatible format for analysis.
Option A is incorrect because S3 bucket rules do not filter CloudWatch log events by timestamp for ingestion control, and using S3 triggers adds unnecessary post-delivery processing. Option C is invalid because the subscription filter applies at the CloudWatch Logs log group, not by "monitoring the Firehose stream." Option D is incorrect because Firehose does not natively ingest only CloudWatch log groups based on tags or automatically reformat arbitrary logs without a transformation step. The most reliable and AWS-native design is subscription filtering + Firehose + Lambda transformation.
NEW QUESTION # 87
A company stores customer records in Amazon S3. The company must not delete or modify the customer record data for 7 years after each record is created. The root user also must not have the ability to delete or modify the data.
A data engineer wants to use S3 Object Lock to secure the data.
Which solution will meet these requirements?
Answer: D
Explanation:
The company wants to ensure that no customer records are deleted or modified for 7 years, and even the root user should not have the ability to change the data. S3 Object Lock in Compliance Mode is the correct solution for this scenario.
Option B: Enable compliance mode on the S3 bucket. Use a default retention period of 7 years.
In Compliance Mode, even the root user cannot delete or modify locked objects during the retention period. This ensures that the data is protected for the entire 7-year duration as required. Compliance mode is stricter than governance mode and prevents all forms of alteration, even by privileged users.
Option A (Governance Mode) still allows certain privileged users (like the root user) to bypass the lock, which does not meet the company's requirement. Option C (legal hold) and Option D (setting retention per object) do not fully address the requirement to block root user modifications.
Reference:
Amazon S3 Object Lock Documentation
NEW QUESTION # 88
The company stores a large volume of customer records in Amazon S3. To comply with regulations, the company must be able to access new customer records immediately for the first 30 days after the records are created. The company accesses records that are older than 30 days infrequently.
The company needs to cost-optimize its Amazon S3 storage.
Which solution will meet these requirements MOST cost-effectively?
Answer: D
Explanation:
The most cost-effective solution in this case is to apply a lifecycle policy to transition records to Amazon S3 Standard-IA storage after 30 days. Here's why:
* Amazon S3 Lifecycle Policies: Amazon S3 offers lifecycle policies that allow you to automatically transition objects between different storage classes to optimize costs. For data that is frequently accessed in the first 30 days and infrequently accessed after that, transitioning from theS3 Standard storage class to S3 Standard-Infrequent Access (S3 Standard-IA)after 30 days makes the most sense. S3 Standard-IA is designed for data that is accessed less frequently but stillneeds to be retained, offering lower storage costs than S3 Standard with a retrieval cost for access.
* Cost Optimization: S3 Standard-IA offers a lower price per GB than S3 Standard. Since the data will be accessed infrequently after 30 days, using S3 Standard-IA will lower storage costs while still allowing for immediate retrieval when necessary.
* Compliance with Regulations: Since the records need to be immediately accessible for the first 30 days, the use ofS3 Standardfor that period ensures compliance with regulatory requirements. After 30 days, transitioning toS3 Standard-IAcontinues to meet access requirements for infrequent access while reducing storage costs.
* Alternatives Considered:
* Option B (S3 Intelligent-Tiering): While S3 Intelligent-Tiering automatically moves data between access tiers based on access patterns, it incurs a small monthly monitoring and automation charge per object. It could be a viable option, but transitioning data toS3 Standard-IA directly would be more cost-effective since the pattern of access is well-known (frequent for 30 days, infrequent thereafter).
* Option C (S3 Glacier Deep Archive): Glacier Deep Archive is the lowest-cost storage class, but it is not suitable in this case because the data needs to be accessed immediately within 30 days and on an infrequent basis thereafter. Glacier Deep Archive requires hours for data retrieval, which is not acceptable for infrequent access needs.
* Option D (S3 Standard-IA for all records): UsingS3 Standard-IA for all recordswould result in higher costs for the first 30 days, as the data is frequently accessed. S3 Standard-IA incurs retrieval charges, making it less suitable for frequently accessed data.
:
Amazon S3 Lifecycle Policies
S3 Storage Classes
Cost Management and Data Optimization Using Lifecycle Policies
AWS Data Engineering Documentation
NEW QUESTION # 89
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