SAP-C02 Practice Question: Design Solutions for Organizational Complexity
A company has a centralized logging account that receives VPC Flow Logs, CloudTrail logs, and AWS Config logs from all member accounts in AWS Organizations. The logs are stored in an S3 bucket in the logging account. Security analysts need to query these logs using Amazon Athena. What is the MOST efficient way to set up the table partitions?
⚠ Common exam trap
Test-takers frequently assume AWS Glue Crawler can automatically create optimal partitions for multi-account log structures, but it typically only partitions on the last directory level (e.g., date), missing the account ID and region partitions that are crucial for query performance in a centralized logging setup.
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 Crawler to create a table, then manually add partitions for each account ID and region.
VPC Flow Logs, CloudTrail, and AWS Config logs are stored in S3 with key prefixes that include account ID, region, and date (e.g., AWSLogs/{account-id}/CloudTrail/{region}/{year}/{month}/{day}/). To efficiently query these logs in Athena, partitions should be created on account ID and region to enable partition pruning, reducing the amount of data scanned. Manually adding partitions for each account ID and region ensures precise control and avoids the overhead of crawling all historical data, which is more efficient than relying solely on automatic date-based partitioning.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use AWS Glue Crawler to create a table with no partitions, and query the entire dataset each time.
Why it's wrong here
Without partitions, Athena scans all data, which is inefficient.
- ✗
Use AWS Glue Crawler to automatically create partitions based on the date prefix in the S3 key.
Why it's wrong here
Date-only partitioning does not account for account or region, leading to more data scanned.
- ✓
Use AWS Glue Crawler to create a table, then manually add partitions for each account ID and region.
Why this is correct
Partitioning by account and region optimizes query performance for multi-account environments.
- ✗
Use AWS Glue Crawler to create a table partitioned by log type and date.
Why it's wrong here
Partitioning by log type and date is less effective than by account and region for typical queries.
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 |
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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.