Senior LevelCloud Computing (AWS/GCP/Azure)
How does AWS Database Migration Service (DMS) execute heterogeneous zero-downtime database migrations?
❓ Interview Prompt: Explain AWS DMS replication tasks, Schema Conversion Tool (SCT), Change Data Capture (CDC), and zero-downtime database cutovers.
Migrating multi-terabyte production databases across heterogeneous engines (e.g. Oracle on-premise $\rightarrow$ Amazon Aurora PostgreSQL) requires Zero-Downtime Migration.
Execution Pipeline:
1
Schema Conversion (AWS SCT): AWS Schema Conversion Tool automatically converts source database schemas, views, and stored procedures into PostgreSQL target DDL.
2
Full Load Phase: AWS DMS reads initial table snapshots and populates the target Aurora database.
3
CDC Continuous Replication Phase: DMS reads source database transaction logs (Oracle Redo Logs / Postgres WAL) in real time via Change Data Capture (CDC), streaming ongoing write mutations to Aurora.
4
Final Cutover: When replication lag drops to zero, switch application connection strings to Aurora with zero downtime!
Code Implementation Example
hcl
# AWS DMS Replication Task executing Full Load + Ongoing CDC
resource "aws_dms_replication_task" "migration" {
migration_type = "full-load-and-cdc" # Full snapshot + real-time CDC
replication_instance_arn = aws_dms_replication_instance.dms.arn
source_endpoint_arn = aws_dms_endpoint.oracle_source.arn
target_endpoint_arn = aws_dms_endpoint.aurora_target.arn
table_mappings = jsonencode({ rules: [{ rule_type: "selection", rule_action: "include", value: "%" }] })
replication_task_id = "oracle-to-aurora-task"
}💡Terraform AWS DMS replication task configured for Full Load and CDC.
🎯 Interview Key Takeaway
AWS DMS uses Change Data Capture (CDC) to stream real-time transaction log mutations, achieving zero-downtime heterogeneous database migrations.
#AWS DMS#Database Migration#CDC#Aurora#Senior
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