What if your database could clean itself and save important old data without you doing a thing?
Why TTL with Streams for archival in DynamoDB? - Purpose & Use Cases
Imagine you have a huge list of old records stored in your database that you no longer need daily but must keep for legal reasons. You try to manually check each record's date and move or delete them one by one.
This manual process is slow and tiring. You might miss some records or accidentally delete important data. It's hard to keep track of what to archive or delete, especially as the data grows every day.
TTL (Time To Live) with Streams automatically marks records to expire after a set time. When a record expires, a stream captures this event so you can archive the data safely before it disappears. This makes managing old data easy and error-free.
Scan table for old records
Manually copy to archive
Delete old recordsSet TTL attribute on records Use Streams to trigger archival Records auto-delete after TTL
You can automatically archive and clean up old data without lifting a finger, keeping your database fast and organized.
A company keeps customer logs for 90 days. Using TTL with Streams, logs older than 90 days are archived to cheaper storage automatically, freeing up space and ensuring compliance.
Manual data cleanup is slow and risky.
TTL with Streams automates expiry and archival.
This keeps data organized and compliant effortlessly.
Practice
Solution
Step 1: Understand TTL function
TTL marks items with an expiration timestamp so DynamoDB can delete them automatically after expiry.Step 2: Identify TTL's main benefit
This automatic deletion helps keep the table clean without manual intervention.Final Answer:
Automatically delete expired items to keep the table clean -> Option DQuick Check:
TTL = automatic deletion [OK]
- Confusing TTL with encryption
- Thinking TTL creates backups
- Assuming TTL increases capacity
Solution
Step 1: Recall AWS CLI TTL command
The correct command is 'update-time-to-live' with parameters for table name and TTL specification.Step 2: Match correct syntax
aws dynamodb update-time-to-live --table-name MyTable --time-to-live-specification Enabled=true,AttributeName=expiryDate uses the exact syntax: --time-to-live-specification Enabled=true,AttributeName=expiryDate.Final Answer:
aws dynamodb update-time-to-live --table-name MyTable --time-to-live-specification Enabled=true,AttributeName=expiryDate -> Option CQuick Check:
Correct CLI command = aws dynamodb update-time-to-live --table-name MyTable --time-to-live-specification Enabled=true,AttributeName=expiryDate [OK]
- Using non-existent commands like enable-ttl
- Wrong parameter names
- Missing 'time-to-live-specification' flag
Solution
Step 1: Understand TTL deletion effect on streams
When TTL deletes an item, DynamoDB Streams capture this as a REMOVE event because the item is removed.Step 2: Identify correct event type
INSERT and MODIFY happen on new or updated items, not deletions. REMOVE is the correct event for deletions.Final Answer:
REMOVE -> Option BQuick Check:
TTL deletion = REMOVE event [OK]
- Choosing INSERT or MODIFY for deletions
- Confusing UPDATE with MODIFY
- Assuming TTL triggers no stream events
Solution
Step 1: Check stream configuration
If the Lambda never receives events, the stream might be disabled or not configured to capture REMOVE events, which TTL deletions generate.Step 2: Verify other causes
TTL must be enabled, but if streams are off or missing REMOVE events, Lambda won't get notifications. Permissions or missing primary key would cause other errors.Final Answer:
The stream is not enabled or not set to capture REMOVE events -> Option AQuick Check:
Missing REMOVE events in stream = The stream is not enabled or not set to capture REMOVE events [OK]
- Ignoring stream settings
- Assuming permissions cause no events
- Overlooking TTL enablement
Solution
Step 1: Understand archival with TTL and streams
TTL deletes expired items, streams capture REMOVE events. Lambda triggered by these events can archive data safely.Step 2: Ensure reliability and no data loss
Processing REMOVE events and writing to S3 with retries ensures data is archived even if Lambda fails temporarily.Step 3: Evaluate other options
Use TTL to delete items, ignore streams, and periodically scan table for expired items ignores streams and risks missing data. Disable TTL and manually delete items after archiving disables TTL, losing automatic cleanup. Process INSERT events in Lambda and archive items before expiration archives before expiration, which is not TTL-based archival.Final Answer:
Process REMOVE events in Lambda and write directly to S3, retrying on failure -> Option AQuick Check:
Reliable archival = Process REMOVE events in Lambda and write directly to S3, retrying on failure [OK]
- Ignoring stream REMOVE events
- Disabling TTL unnecessarily
- Archiving on INSERT instead of REMOVE
Ready to prove it?
Pass the test and this pattern moves unknown
