Cachet

A composable, multi-tier caching library with stampede protection, background refresh, and built-in OpenTelemetry telemetry.

Why Multi-Tier Caching?

A single cache is a single point of failure and a capacity ceiling. Multi-tier caching layers fast, small caches in front of slower, larger ones:

• L1 (primary) - an in-process memory cache: microsecond latency, bounded capacity, evicts under pressure.
• L2 (fallback) - a remote or larger cache: millisecond latency, much larger capacity, survives process restarts.

On a miss in L1, cachet transparently queries L2 and optionally promotes the value back into L1 so the next request is fast again. The result is lower average latency, reduced load on the backing store, and resilience when either tier is temporarily unavailable.

Why Background Refresh?

TTL-based expiration causes a synchronous miss every time an entry ages out: the next caller blocks while the value is recomputed. Background refresh (time-to-refresh, TTR) decouples freshness from latency:

• While an entry is still within its TTR, all callers receive the cached value immediately (a “refresh hit”).
• Once the TTR elapses, the next caller still receives the stale value, but a background task is spawned to pull a fresh value from the fallback tier.
• Subsequent callers continue to hit the cache while the refresh happens, so latency never spikes.

Use TimeToRefresh together with a fallback tier to enable this pattern.

Cache Stampede Protection

A cache stampede (also called a thundering herd) occurs when many concurrent requests all miss the cache at the same time - for example, after a cold start or after a popular entry expires. Every request independently computes the value, spiking load on the backing store.

cachet avoids this with request coalescing via the uniflight crate: when stampede protection is enabled, all concurrent requests for the same key are merged so that only one computes the value. The rest wait and share the result, including any error. Enable it with CacheBuilder::stampede_protection.

Flexibility

cachet is designed to adapt to your infrastructure rather than the other way around:

• Any storage backend - implement CacheTier to plug in Redis, Memcached, a database, or any other store.
• Service middleware - with the service feature, any Service<CacheOperation> becomes a CacheTier, so you can compose retry, timeout, and circuit-breaker middleware around your storage using standard Tower or layered patterns.
• Dynamic dispatch - when a fallback tier is configured, the builder automatically type-erases both tiers into a DynamicCache<K, V> so the primary and fallback don’t need to be the same concrete type.
• Configurable insert policy - choose whether, and under what conditions, values are inserted into a tier (InsertPolicy).
• Clock injection - all time-based logic (TTL, TTR, timestamps) goes through a tick::Clock, making caches fully controllable in tests without sleeping.

Why Use This Instead of Moka/Other Caches?

Moka (and similar crates) are excellent single-tier in-process caches. cachet builds on top of them and adds:

If you only need a single in-process cache with no telemetry requirements, moka directly may be simpler. If you need any of the above, cachet is the right choice.

Major Types

How Tiers Compose

Tiers are composed at build time using the builder:

Cache::builder::<K, V>(clock)
    .memory()                          // L1: fast in-process store
    .ttl(Duration::from_secs(30))      // entries expire from L1 after 30 s
    .fallback(                         // on L1 miss, consult L2
        Cache::builder::<K, V>(clock)
            .memory()                  // L2: a second in-process store (or a remote service)
            .ttl(Duration::from_secs(300))
    )
    .insert_policy(InsertPolicy::always())  // control when values are inserted into L1
    .time_to_refresh(TimeToRefresh::new(Duration::from_secs(20), spawner))  // refresh L1 in background
    .build()

On a get:

1. Check L1. If hit and not stale, return immediately.
2. If hit but stale (TTR elapsed), return the stale value and spawn a background task to fetch from L2 and repopulate L1.
3. If miss or expired (TTL elapsed), check L2. If found, optionally promote to L1, then return.
4. If both miss, return Ok(None).

Note: expired entries are not automatically removed from storage. The wrapper uses lazy expiration - it returns None but leaves cleanup to the storage backend (e.g. moka built-in eviction).

TO-DO add an ExpirationPolicy that would make this configurable.

Invalidation and clear are sent to all tiers concurrently.

Companion Crates

cachet is the main entry point. The ecosystem is split into focused crates:

You rarely need to depend on companion crates directly - cachet re-exports the most commonly used types from all of them.

Cargo Features

Examples

Basic In-Memory Cache

use cachet::{Cache, CacheEntry};
use tick::Clock;

let clock = Clock::new_tokio();
let cache = Cache::builder::<String, i32>(clock).memory().build();

cache.insert("key".to_string(), CacheEntry::new(42)).await?;
let value = cache.get("key").await?;
assert_eq!(*value.unwrap().value(), 42);

Multi-Tier Cache with Fallback

use std::time::Duration;

use cachet::Cache;
use tick::Clock;

let clock = Clock::new_tokio();
let l2 = Cache::builder::<String, String>(clock.clone()).memory();

let cache = Cache::builder::<String, String>(clock)
    .memory()
    .ttl(Duration::from_secs(60))
    .fallback(l2)
    .build();

Telemetry

Enable with metrics and/or logs features. Configure via .enable_metrics() and .enable_logs().

Metrics (OpenTelemetry)

Attributes: cache.name, cache.operation, cache.activity

Operations: cache.get, cache.insert, cache.invalidate, cache.clear

Activities: cache.hit, cache.miss, cache.expired, cache.inserted, cache.invalidated, cache.refresh_hit, cache.refresh_miss, cache.fallback, cache.rejected, cache.error, cache.ok

Logs (tracing)

Event name: cache.event with fields cache.name, cache.operation, cache.activity, cache.duration_ns.