Prefetching based on historical use and real-time signals

Methods, systems and computer program products are provided for prefetching based on historical use and real-time signals. Forecast models may be configured to forecast whether to prefetch information (e.g. keys responsive to queries) for future time intervals based on historical use and internal or external signals that may influence forecasts, such as prevailing conditions. Historical use of keys may be analyzed for patterns and trends with multiple seasonalities per category and/or per key. Time series data and forecasts may be indexed by cache categories and time intervals. Forecast models may be trainable, optimizable, configurable and/or auto-correcting on a per-category and/or a per-key basis. Forecast precision indicators, confidence indicators and configurable thresholds may be used to optimize performance. Operations may be distributed among multiple servers. Tasks may be time-distributed by offsets. Cached information may be assigned a time to live (TTL) independent of other cached information.