BlogsStripeDatabase Fleet Auto-Remediation

Database Fleet Auto-Remediation

Database Fleet Auto-Remediation

2
posts
2024–2026

This feature thread tracks Stripe's advancements in automating the management and remediation of its global database fleet. The initial post introduced a novel approach using graph search and state machines to model MongoDB infrastructure as a traversable graph. This allows for dynamic computation and execution of recovery plans, significantly reducing manual intervention, pager alerts, and unhealthy shard states. The system is designed to support new shard layouts with zero manual effort, highl. This post details how Stripe's document databases, specifically their implementation of the Data Movement Platform, enabled zero-downtime data migrations while maintaining 99.999% uptime, showcasing advanced strategies for database infrastructure management and reliability.

2026

How Stripe uses graph search and state machines to auto-remediate a global database fleet

7/16/2026

This post elaborates on the technical details of how Stripe uses graph search and state machines to auto-remediate its global database fleet. It explains the process of modeling MongoDB infrastructure as a traversable graph and utilizing pathfinding algorithms to dynamically compute and execute recovery plans. The post highlights the impact of this automated approach, including a 30% reduction in pager volume, elimination of unhealthy shard states, and the ability to support new shard layouts with zero manual effort.

2024

How Stripe’s document databases supported 99.999% uptime with zero-downtime data migrations

6/6/2024

This post details how Stripe's document databases, specifically their implementation of the Data Movement Platform, enabled zero-downtime data migrations while maintaining 99.999% uptime, showcasing advanced strategies for database infrastructure management and reliability.