Adaptive cache expiration strategy

Design cache expiration policies that align with actual workload patterns rather than arbitrary timeframes. For systems with varying access patterns (e.g., daily vs. monthly workloads), implement configurable TTL settings to prevent premature cache invalidation.

struct CacheConfig {
    // Allow users to configure the cache TTL based on their workload patterns
    /// TTL in seconds for cache persistence. Default value balances
    /// memory usage with performance for typical workloads.
    /// Set to `None` for permanent persistence until explicit deletion.
    pub cache_ttl_sec: Option<i32>,
    
    /// Whether to perform automatic prewarming on restart
    pub auto_prewarm: bool,
    
    /// Custom prewarming strategy for different workload types
    pub prewarm_strategy: PrewarmStrategy,
}

enum PrewarmStrategy {
    /// Minimal prewarming for frequent access patterns
    Basic,
    /// Medium prewarming for daily/weekly workloads
    Standard,
    /// Full prewarming for monthly/infrequent workloads
    Complete,
}

When implementing caching mechanisms, consider adding workload-aware expiration policies rather than fixed TTLs. For systems with infrequent but performance-critical operations (like monthly reporting), overly aggressive cache expiration can cause significant performance degradation.

Cache policies should balance automatic management with user configuration to accommodate both typical use cases and edge cases. Consider adding monitoring to track actual cache hit rates and auto-adjust TTLs based on observed workload patterns.