Figma 的下一代数据缓存平台

Figma's next-generation data caching platform

Figma 的下一代数据缓存平台

Colorful, intertwined transit-like lines converge into a central tunnel or portal on a bright yellow background.

In recent years, Figma's growth has tested the scalability limits of our storage infrastructure. In 2024, we rearchitected our durable metadata storage systems

近年来,Figma 的增长考验了我们存储基础设施的可扩展性极限。在 2024 年,我们重构了我们的持久元数据存储系统

How Figma’s databases team lived to tell the scale

Figma’s databases team 如何幸存并讲述其规模

Our nine month journey to horizontally shard Figma’s Postgres stack, and the key to unlocking (nearly) infinite scalability.

我们九个月的旅程,将 Figma’s Postgres 堆栈水平分片,这是解锁(几乎)无限可扩展性的关键。

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; in 2025, we expanded our ambitions to include our ephemeral storage and caching layer, built on top of Redis.

; 在 2025 年,我们扩展了我们的雄心,涵盖了我们的临时存储和缓存层,该层构建在 Redis 之上。

We built FigCache: a stateless, RESP-wire-protocol proxy service that acts as a unified Redis data plane, complemented by a suite of first-party client libraries. FigCache decouples connection scalability on Redis from fleet capacity volatility in client services, centralizes traffic routing, uplevels our security posture, and delivers comprehensive, end-to-end observability across Figma's entire caching stack. Since its rollout for Figma's main API service in the second half of 2025, Figma's caching layer has achieved six nines of uptime—a new reliability milestone.

我们构建了 FigCache:一个无状态的 RESP-wire-protocol 代理服务,它充当统一的 Redis 数据平面,并辅以一套第一方客户端库。FigCache 将 Redis 上的连接可扩展性与客户端服务中的机队容量波动解耦,集中化流量路由,提升我们的安全姿态,并为 Figma 的整个缓存栈提供全面的端到端可观测性。自 2025 年下半年为其 Figma 主 API 服务 rollout 以来,Figma 的缓存层已实现六个九的正常运行时间——一个新的可靠性里程碑。

Growing pains in caching

缓存中的成长之痛

As our infrastructure footprint grew, Redis evolved from a simple, non-critical component into a critical-path dependency for site availability.

随着我们的基础设施足迹的增长,Redis 从一个简单的、非关键组件演变为站点可用性的关键路径依赖。

Before our rearchitecture, we had to contend with evolving structural challenges around operating a massive system at scale. Redis clusters faced growing connection volumes, slowly approaching hard limits. Rapid scale-ups of client services could trigger thundering herds of co...

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