In this article, we will look at how Airbnb implemented this design and the challenges they faced.

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Airbnb deployed distributed SQL databases across multiple Kubernetes clusters, each mapped to a different AWS Availability Zone, to achieve high availability and fault tolerance. They built custom Kubernetes operators to safely manage stateful workloads, coordinate node replacements, and maintain quorum during failures. Using AWS EBS for persistent storage, PVCs for volume management, and techniques like replica reads and stale reads, they mitigated latency issues while maintaining consistency. Their largest production cluster handles 3 million queries per second across 150 nodes with 300TB of data, achieving 99.95% availability through careful sequencing of upgrades, canary deployments, and overprovisioning for resilience.

How Airbnb Runs Distributed Databases on Kubernetes at Scale

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Multi-Cluster Deployment for Fault Tolerance

<p>it’s refreshing reading about the feats of other engineering minds that are wayy smarter than me. i’ve only passively thought about these topics conceptually but these guys have actually DONE it 🤯</p>
