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Amazon
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Capture data changes while restoring an Amazon DynamoDB table
- The automated PITR restoration process introduces a new challenge of data changes during the restoration process that needs to be captured and incorporated to maintain data consistency and avoid data loss.
- In this post, we present a solution that automates PITR restoration and handles data changes occurring during the restoration process, providing a smooth transition back to the restored DynamoDB table with near-zero downtime.
- Automated PITR solutions provide not just data recovery but also increased business continuity, data integrity, and operational efficiency.
- Challenges with alternative solutions including version numbers and optimistic locking include the identification of affected items and data loss issues when deployments change several versions of the same item.
- Industries such as e-commerce, content management systems, and IoT data collection systems can benefit from automated PITR solutions.
- The solution architecture uses DynamoDB, DynamoDB Streams, AWS Lambda, Amazon SQS, AWS EventBridge and AWS Step Functions.
- AWS CDK is used to create an AWS EventBridge, Step Functions state machine, SQS queue, and backfilling functions.
- The process consists of the source table serving live traffic, restoration to a timepoint, DynamoDB streams, queuing, and backfilling reproduced changes.
- After deploying the solution, PITR restore can be initiated. The process captures and replicates changes in near real-time during the restore process.
- Additional future upgrades to the solution include an idempotency layer, incremental changes made to the table and retrieval, and processing of CDC writes once.
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