SOA-C02 Cost and Performance Optimization Practice Question

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 S3 Intelligent-Tiering to automatically optimize storage costs.

  Why this is correct

  S3 Intelligent-Tiering automatically monitors access patterns and moves objects between frequent, infrequent, and archive-instant access tiers, charging a small monthly monitoring and automation fee per object. Unlike a static lifecycle rule, it adapts to changing access without retrieval fees or operational overhead, making it ideal for data with unpredictable usage. However, it does not compress or deduplicate data, and you still pay for the storage class actually used, but it optimizes cost by minimizing manual tier choices.

• ✗

  Use S3 One Zone-IA for all data after 30 days to reduce costs.

  Why it's wrong here

  S3 One Zone-IA stores data redundantly within a single Availability Zone, so it does not protect against AZ loss, fire, or flooding—offering only 99.5% durability compared to 99.999999999% for other S3 classes. For analytics datasets that may be needed for compliance, re-processing, or long-term business value, losing the data is unacceptable. Additionally, One Zone-IA has a 30-day minimum storage duration and per-GB retrieval fees, so applying it to all data after 30 days can still be costly if any objects are accessed more frequently than expected.

• ✓

  Create a lifecycle policy to transition objects to S3 Glacier Deep Archive after 90 days.

  Why this is correct

  S3 Glacier Deep Archive is the lowest-cost storage class in S3, designed for long-term preservation of data that is accessed at most once a year and where retrieval times of 12 hours or more are acceptable. Transitioning to Deep Archive after 90 days is appropriate for analytics data that must be retained for regulatory compliance or historical reference but is unlikely to be queried interactively. This approach minimizes storage costs, but you must ensure your analytics pipeline can tolerate hours-long retrieval delays and that the 180-day minimum storage duration aligns with your retention requirements.

• ✓

  Create a lifecycle policy to transition objects to S3 Standard-IA after 30 days.

  Why this is correct

  S3 Standard-IA is optimized for data that is accessed infrequently but needs millisecond retrieval when needed. Transitioning objects to Standard-IA after 30 days is a good compromise for analytics data that may still be referenced for reporting or ad-hoc queries over the next few months, as it costs significantly less per GB than S3 Standard while keeping latency low. However, Standard-IA charges a retrieval fee per GB and has a 30-day minimum storage duration, so it is only cost-effective if the data is not accessed frequently; otherwise, frequent retrievals can negate the storage savings.

• ✗

  Use S3 Standard storage for all data to ensure high performance.

  Why it's wrong here

  S3 Standard offers high durability, availability, and low latency with no retrieval fees, but it comes at a higher per-GB storage price than other classes. Keeping all analytics data in S3 Standard means paying premium rates for data that may become cold or rarely accessed after the initial processing window, leading to unnecessary storage expenditures. For a company using S3 for analytics, it is more cost-effective to use lifecycle policies or Intelligent-Tiering to move older data to cheaper tiers rather than leaving everything in Standard.

Go deeper

Related to this question