Valkey accepts request and response payloads up to a global bulk-size limit. In practice, however, even moderate increases in payload size can introduce significant overhead. Larger payloads take longer to transmit over the network, require more memory allocation, increase replication pressure, and block the event loop for longer periods.

When these effects stack, overall system performance can degrade well before payloads approach the configured maximum size.

This talk proposes a set of high-level guardrails to make large-payload workloads easier to observe and manage in production.

It covers: Adding lightweight server-side signals to track request and response payload size trends and the frequency of large operations (e.g., Issue #2911, PR #2918); Practical guidance on choosing bulk-size limits that better match different workload patterns; Exploratory runtime safeguards that use signals such as latency or replication lag to temporarily reject or delay expensive operations when the server is under stress.

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