Context & History

Netflix's data platform has evolved from a collection of heterogeneous relational stores to a unified, cloud‑native ecosystem. In early 2024 the Online Data Stores team conducted a company‑wide review of PostgreSQL deployments, weighing functionality, performance, and total cost of ownership. The review concluded that Amazon Aurora PostgreSQL offered the best mix of scalability and operational efficiency, prompting a multi‑year plan to migrate all RDS PostgreSQL clusters to Aurora. This strategic move supports Netflix's rapid feature delivery cadence while keeping data services secure and cost‑effective.

Implementation & Best Practices

The migration framework is built around three phases preparation, continuous synchronization, and cut‑over. First, teams enable automated backups on the source RDS instance and verify network connectivity. Next, an Aurora read replica is provisioned AWS streams write‑ahead logs from the source to keep the replica in near‑real‑time sync. Finally, after the replica catches up, write traffic is briefly paused, the replica is promoted, and traffic is redirected to the new Aurora endpoint. This roadmap ensures that each step can be audited, rolled back if needed, and executed with minimal human interaction.

Migration workflow overview

The self‑service tool guides users through a wizard‑style UI that triggers AWS Step Functions to orchestrate the entire pipeline. Key checkpoints include snapshot validation, replica health monitoring, and automated performance testing against production‑like workloads.

Snapshot‑based approach

In the snapshot method, the source database is frozen, a manual snapshot is taken, and AWS converts it into an Aurora‑compatible image. After the new cluster is launched, a health check suite verifies data integrity before traffic is switched. This approach is simple but requires a longer outage window.

Read‑replica approach

The read‑replica strategy reduces downtime by keeping the Aurora replica synchronized while the source remains online. Once replication lag drops below a defined threshold, a brief pause in writes allows the replica to catch up fully before promotion. This method introduces additional automation complexity but delivers a smoother transition for high‑traffic services.

Key operational safeguards

Automated backups must be active on the source they provide the stable snapshot needed for replica bootstrap and ensure point‑in‑time recovery capabilities. Network policies are enforced via the Data Access Layer, which routes all database traffic through a forward proxy with mutual TLS, preserving credential secrecy during migration.

Best‑practice checklist

• Enable automated backups and verify retention settings.
• Run the migration wizard in a non‑production environment first.
• Monitor replication lag with CloudWatch alarms.
• Perform a read‑only validation run against the Aurora endpoint.
• Document the cut‑over plan and communicate the brief maintenance window.

Real‑world example

One team migrated a 150 TB analytics cluster using the read‑replica flow, achieving a total downtime of under five minutes. The automated tool handled snapshot creation, replica provisioning, and traffic switchover without manual credential handling.

For deeper insights into building large‑scale, automated cloud workflows, see the guide on scalable real‑time payment orchestration on AWS. A complementary perspective on applying well‑architected principles to complex migrations is available in the AWS Well‑Architected Machine Learning Lens article.