SAP-C02 Practice Question: Design Solutions for Organizational Complexity
A company is centralizing its logging across multiple AWS accounts using a central logging account. Each application account delivers its CloudTrail logs and VPC Flow Logs to an S3 bucket in the logging account. The security team needs to query these logs using Amazon Athena. The logs are currently in separate S3 prefixes per account. The team wants to create a single Athena table that can query logs from all accounts without having to modify the table definition every time a new account is added. The logs are in CSV format for VPC Flow Logs and JSON format for CloudTrail. What is the MOST efficient solution?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use AWS Glue crawlers configured to crawl the S3 bucket with a partition structure based on account ID and log type. Enable partition indexing to improve query performance.
Using AWS Glue crawlers configured to crawl the S3 bucket with a partition structure based on account ID and log type allows automatic discovery of new partitions as new accounts are added. The crawler can be scheduled to run periodically, updating the table metadata without manual intervention. Partition indexing improves query performance by reducing the amount of data scanned. Option A is incorrect because updating a view requires manual DDL changes each time a new account is added. Option C is incorrect because manually managing partitions and using MSCK REPAIR TABLE still requires manual effort to add new partitions. Option D is incorrect because converting logs to Parquet adds overhead and does not solve the need for automatic partition discovery across accounts.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create a view that unions all the tables for each account, and update the view DDL when a new account is added.
Why it's wrong here
This requires manual updates to the view definition.
- ✓
Use AWS Glue crawlers configured to crawl the S3 bucket with a partition structure based on account ID and log type. Enable partition indexing to improve query performance.
Why this is correct
Glue crawlers automatically discover new partitions and update the table metadata.
- ✗
Create an Athena table with partitions manually for each account and use MSCK REPAIR TABLE to add new partitions.
Why it's wrong here
MSCK REPAIR TABLE is not automatic and requires manual intervention.
- ✗
Convert all logs to Parquet format using AWS Glue ETL jobs and store them in a single prefix.
Why it's wrong here
This adds transformation cost and complexity, and does not solve the auto-discovery issue.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
Go deeper
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This SAP-C02 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the SAP-C02 exam.