Exams / SCS-C03 / Study guide / Data retention and lifecycle (S3 Lifecycle, EFS lifecycle, FSx backups)
Data retention and lifecycle (S3 Lifecycle, EFS lifecycle, FSx backups): SCS-C03 study notes and practice questions
What to know about Data retention and lifecycle (S3 Lifecycle, EFS lifecycle, FSx backups) for the SCS-C03 exam, from the Data Protection domain (18% of the exam guide), then 1 free question to test it. Part of the SCS-C03 study guide.
These questions pair a retention rule, such as “keep logs for one year, archive them, then delete,” with the service feature that moves or removes data. The trap is usually a lifecycle rule that conflicts with a lock or with a minimum storage duration.
Lifecycle features
S3 Lifecycle rules transition current or noncurrent object versions to cheaper storage classes after a set number of days, and expire objects at the end of their life. Expiring noncurrent versions cleans up old copies in a versioned bucket.
Minimum storage durations apply to archive and some infrequent-access classes. Deleting an object early still bills the remaining minimum, which matters for short-lived data.
Object Lock blocks expiration. Lifecycle waits until the retention period ends and any legal hold is removed.
S3 Intelligent-Tiering moves objects between access tiers based on use, without rules you write.
EFS lifecycle management moves files that have not been accessed for a set period to the Infrequent Access or Archive storage class, and can move them back to Standard when they are accessed again.
CloudWatch Logs keeps log events for a retention period you set per log group. Export or stream logs to S3 for longer, cheaper storage.
FSx backups run on a daily schedule with retention settings. AWS Backup can copy them to another account or Region with a longer retention.
How to choose
Scenario wording
Pick
Move objects to archive after 90 days and delete them after seven years
S3 Lifecycle transitions and expiration
Clean up old copies in a versioned bucket
Noncurrent version expiration
Access pattern is unknown and cost should follow use
S3 Intelligent-Tiering
Keep logs for years at low cost
Set log group retention, then export to S3 with lifecycle rules
Move old files on a shared file system to cheaper storage
EFS lifecycle management
Keep FSx backups longer, in another account
AWS Backup copy with its own retention
Common traps
Expecting lifecycle to delete locked data. Locked objects stay until retention ends.
Forgetting noncurrent versions. Without a rule for them, storage keeps growing after every overwrite.
Early deletion charges when objects leave an archive class before its minimum duration.
Assuming expiring source data expires backups. Backups have their own retention.
Setting a delete rule and stopping there. When a rule requires deletion, the scenario may also expect verification, such as an audit record of the deletion.
A hospital keeps application audit logs in an S3 bucket with versioning turned on. Clinicians rarely read logs after 30 days, but the compliance policy requires that logs be kept for seven years and then deleted.
Engineers sometimes re-upload corrected log files, which creates noncurrent versions. Finance wants storage costs kept low, and noncurrent copies must be deleted 30 days after they stop being current. Incomplete multipart uploads should not accumulate either.
Which lifecycle configuration meets these requirements with the LEAST operational overhead?
Choose one answer.
AA. Create a lifecycle rule that moves current objects to S3 Glacier Flexible Retrieval after 30 days and never expires them. Keep noncurrent versions in the same storage class for as long as the bucket exists.
BB. Transition current objects to Glacier Flexible Retrieval at 30 days and expire them at 2,555 days. Expire noncurrent versions 30 days after they become noncurrent, and abort incomplete uploads after seven days.
CC. Create a rule that expires current objects after 2,555 days, and leave noncurrent versions alone so engineers can restore older logs at any time. Upload new logs in the Standard-IA storage class to reduce costs.
DD. Keep the lifecycle rules as they are, and run a scheduled Lambda function each month that lists the bucket and deletes logs older than seven years along with noncurrent versions older than 30 days.
Show the answer and explanation
Answer: B
A. Wrong: Objects are archived at a lower cost, but nothing is deleted after seven years, which breaks the deletion rule. Noncurrent versions also stay indefinitely, so costs keep growing and the 30-day requirement is missed.
B. Right: Correct. The transition lowers storage costs, the expiration deletes logs after seven years, and the noncurrent rule removes replaced versions on schedule. The multipart rule stops abandoned uploads from piling up, all without custom code. Learn more: Managing your storage lifecycle (opens in a new tab)
C. Wrong: Expiring current objects deletes logs on schedule, but noncurrent versions remain and keep costing money. Standard-IA lowers the price per gigabyte only a little for rarely read data, and it does not move logs into an archive class.
D. Wrong: The function would work, but the team must write, test, and run it indefinitely. A bucket lifecycle configuration does the same job with no code, so this option adds overhead the team does not need.
Explanation
S3 lifecycle rules can transition objects to cheaper classes, expire current and noncurrent versions on set schedules, and abort incomplete multipart uploads. One set of rules covers the retention, cost, and cleanup requirements without custom code. The other options keep logs forever, skip noncurrent versions, or add a scheduled function.
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