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## Problem Neon currently implements several features that guarantee high uptime of compute nodes: 1. Storage high-availability (HA), i.e. each tenant shard has a secondary pageserver location, so we can quickly switch over compute to it in case of primary pageserver failure. 2. Fast compute provisioning, i.e. we have a fleet of pre-created empty computes, that are ready to serve workload, so restarting unresponsive compute is very fast. 3. Preemptive NeonVM compute provisioning in case of k8s node unavailability. This helps us to be well-within the uptime SLO of 99.95% most of the time. Problems begin when we go up to multi-TB workloads and 32-64 CU computes. During restart, compute looses all caches: LFC, shared buffers, file system cache. Depending on the workload, it can take a lot of time to warm up the caches, so that performance could be degraded and might be even unacceptable for certain workloads. The latter means that although current approach works well for small to medium workloads, we still have to do some additional work to avoid performance degradation after restart of large instances. [Rendered version](https://github.com/neondatabase/neon/blob/alexk/pg-prewarm-rfc/docs/rfcs/2025-03-17-compute-prewarm.md) Part of https://github.com/neondatabase/cloud/issues/19011