Automating Data Purging in DynamoDB for IoT Applications

Answer: A.

Option A is CORRECT because Time to Live (TTL) for Amazon DynamoDB is functionality that enables automatic deletion of items after a specified expiration time defined by a timestamp in the TTL attribute.

Option B is incorrect because this is not the optimal solution as it requires implementation and deployment for custom code inside a Lambda function.

Option C is incorrect because it would delete items newer than 30 days.

Option D is incorrect because this does not satisfy the original requirement.It would not purge data in the table.

Reference:

Sure, I'll provide a detailed explanation of each option to help you understand the pros and cons of each approach.

Option A: Enable TTL on the DynamoDB table and store the expiration timestamp in the TTL attribute in the epoch time format.

TTL (Time To Live) is a feature in DynamoDB that automatically deletes expired items from the table. When you enable TTL on a DynamoDB table, you can specify an attribute name that contains the expiration time for each item. DynamoDB checks this attribute against the current time and automatically deletes items that have expired.

In this option, you would enable TTL on the DynamoDB table and store the expiration timestamp in the TTL attribute in the epoch time format. You could use a Lambda function to write the current time plus 30 days to the TTL attribute when inserting new items into the table. DynamoDB would automatically delete expired items when their TTL attribute matches or exceeds the current time.

Pros:

• The TTL feature is a built-in feature in DynamoDB, so you don't have to write any custom code to implement this requirement.
• DynamoDB automatically deletes expired items, so you don't have to worry about manually purging old data.

Cons:

• You would need to write a Lambda function to update the TTL attribute when inserting new items into the table.
• You would need to make sure that the current time plus 30 days is accurate, as TTL deletes items based on the current time.

Option B: Implement a Lambda function to perform a query and delete on the table for items with a timestamp greater than 30 days. Use CloudWatch events to trigger the Lambda function.

In this option, you would write a Lambda function to query the DynamoDB table for items with a timestamp greater than 30 days. The Lambda function would then delete these items from the table. You would use CloudWatch events to trigger the Lambda function on a regular schedule.

Pros:

• You have more control over the data purging process, as you can write custom code to query and delete items from the table.
• You can schedule the Lambda function to run on a regular schedule using CloudWatch events.

Cons:

• You would need to write custom code to implement this requirement.
• You would need to make sure that the Lambda function is triggered on a regular schedule to purge old data.

Option C: Create a new DynamoDB table every 30 days. Delete the old DynamoDB table.

In this option, you would create a new DynamoDB table every 30 days and copy the data from the old table to the new table. You would then delete the old table to purge old data.

Pros:

• You have more control over the data purging process, as you can create a new table and copy data to the new table.
• You can archive the old table for backup purposes.

Cons:

• You would need to write custom code to create new tables and copy data to the new tables.
• You would need to manage multiple tables, which could be complex and costly.

Option D: Enable DynamoDB streams on the table. Implement a Lambda function to read events from the stream and delete expired items.

DynamoDB streams capture a time-ordered sequence of item-level modifications in a DynamoDB table. In this option, you would enable DynamoDB streams on the table and write a Lambda function to read events from the stream. The Lambda function would delete expired items based on their timestamp.

Pros:

• DynamoDB streams capture all modifications to the table, so you can delete expired items as soon as they are detected.
• You can write custom code to implement this requirement.

Cons:

• You would need to write custom code to read events from the stream and delete expired items.
• You would need to make sure that the Lambda function is triggered on a regular schedule to purge old data