DialCache

Fine-grained TypeScript caching with explicit enabled contexts, request-local memoization, process-local and Redis TTL caching, stable key construction, runtime rollout controls, request coalescing, adapter-based observability, and Redis watermark-based targeted invalidation.

Install

pnpm add dialcache
# Choose a Redis client when using the remote layer:
pnpm add redis@~4.7.1
# or
pnpm add @valkey/valkey-glide@^2.4.2
# Add a metrics client only when using its adapter:
pnpm add prom-client@^15.1.3
# or
pnpm add hot-shots@^17.0.0

DialCache requires Node.js 20 or Node.js 22 and newer.

Quick start

import { DialCache, DialCacheKeyConfig } from "dialcache";

const dialcache = new DialCache();

const getUser = dialcache.cached(
  (userId: string) => db.fetchUser(userId),
  {
    keyType: "user_id",
    useCase: "GetUser",
    cacheKey: (userId) => userId,
    defaultConfig: DialCacheKeyConfig.enabled(60),
  },
);

// Caching is OFF outside an enable() scope (see "Enabled context"), so this runs the fn uncached:
await getUser("123");

// Inside enable(), reads are cached:
const user = await dialcache.enable(() => getUser("123"));

Request-local cache

Set requestLocal: true to memoize resolved values for the lifetime of the outermost enable() scope:

import { DialCache, DialCacheKeyConfig } from "dialcache";

const dialcache = new DialCache();
const getUser = dialcache.cached(
  (userId: string) => db.fetchUser(userId),
  {
    keyType: "user_id",
    useCase: "GetUser",
    cacheKey: (userId) => userId,
    defaultConfig: new DialCacheKeyConfig({ requestLocal: true }),
  },
);

requestLocal is a runtime boolean rather than a TTL/ramp-controlled CacheLayer. The cacheConfigProvider can turn it on or off for each invocation. DialCacheKeyConfig.enabled(ttlSec) continues to enable only process-local and Redis caching, so request-local caching must be selected explicitly.

DialCache resolves the runtime config once per enabled invocation and uses it for the entire lookup. When requestLocal is missing or false, the invocation skips request-local lookup and storage without deleting an entry already memoized in the scope. A later invocation that enables request-local caching can reuse that entry.

The outermost enable() call owns the request-local lifetime, and nested enable() calls reuse that scope. Request-local state is allocated lazily, only when an invocation enables the layer, so scopes that use only process-local or Redis caching do not allocate it.

Wrap the complete Node HTTP handler so the request-local scope matches the handler's lifetime:

import { createServer } from "node:http";

const server = createServer((req, res) => {
  void dialcache
    .enable(async () => {
      const user = await getUser(readUserId(req));
      res.setHeader("content-type", "application/json");
      res.end(JSON.stringify(user));
    })
    .catch((error: unknown) => handleRequestError(error, res));
});

Request-local storage has no capacity limit, eviction, or overflow mode. Entries are retained until the outermost enable() callback settles. Use it for short-lived scopes with bounded key cardinality; split long-running streams or large batch jobs into smaller scopes when necessary.

Process-local cache

The process-local layer (CacheLayer.LOCAL) uses one LRU per DialCache instance. It keeps at most 10,000 entries by default across all use cases while retaining each entry's configured TTL. Set localMaxSize to a nonnegative safe integer to change the global entry cap; 0 disables process-local storage:

const dialcache = new DialCache({ localMaxSize: 25_000 });

The limit counts entries rather than estimating JavaScript object memory. Recently read entries stay resident ahead of less recently used entries when the limit is reached.

Redis-backed TTL cache

Register DialCache's native node-redis scripts when creating the client, then pass that client to DialCache:

import { createClient } from "redis";
import { DialCache } from "dialcache";
import { createNodeRedisDialCacheClient, dialcacheRedisScripts } from "dialcache/node-redis";

const redisClient = createClient({
  url: process.env.REDIS_URL,
  scripts: dialcacheRedisScripts,
});
await redisClient.connect();

const dialcache = new DialCache({
  namespace: "users-api",
  redis: { client: createNodeRedisDialCacheClient(redisClient) },
});

async function shutdown(): Promise<void> {
  // Stop new work and await every outstanding cached call and invalidation first.
  await redisClient.quit();
}

redis.client is required when Redis is configured and accepts the semantic DialCacheRedisClient interface. Create and connect the underlying client before constructing DialCache. Node-redis users should register the supplied scripts and wrap their client with createNodeRedisDialCacheClient as shown above.

Valkey GLIDE users pass an already-created standalone or cluster client to the GLIDE adapter:

import { GlideClient } from "@valkey/valkey-glide";
import { DialCache } from "dialcache";
import { createValkeyGlideDialCacheClient } from "dialcache/valkey-glide";

const glideClient = await GlideClient.createClient({
  addresses: [{ host: "127.0.0.1", port: 6379 }],
});
const redisClient = createValkeyGlideDialCacheClient(glideClient);
const dialcache = new DialCache({
  namespace: "users-api",
  redis: { client: redisClient },
});

function shutdown(): void {
  // After draining cached calls and invalidations, release scripts before closing GLIDE.
  redisClient.dispose();
  glideClient.close();
}

The application owns the complete Redis lifecycle. It creates and connects the underlying client and passes the semantic adapter to DialCache. During shutdown, stop starting DialCache-backed work and await every outstanding cached-function and invalidateRemote() promise, including calls still running fallbacks that may later write Redis. Then dispose adapter-owned resources and close the underlying connection. DialCache only borrows redis.client; it has no close or drain method and never disposes or closes caller resources.

The node-redis adapter owns no additional resources, so the application closes the underlying node-redis client after draining work. The GLIDE adapter owns five native Script handles but not the wrapped connection. After outstanding operations finish, call its idempotent dispose() before closing GLIDE as shown above; disposal while an adapter operation is in flight throws rather than releasing a live script.

redis.createClient and the RedisClientFactory type were removed. Move lazy factory work to application startup, retain the underlying client and adapter handles, and pass the resulting adapter as redis.client. Because redis.client was already supported and this change does not alter Redis keys or the wire protocol, migrated application construction works with both older and newer DialCache versions during rollout or rollback.

When caching is enabled, reads flow through:

request-local cache -> process-local cache -> Redis cache -> fallback function

Request-local hits return the value memoized in the current outermost enable() scope.
Results from the lower chain are memoized request-locally when that layer is enabled.
Process-local hits return immediately.
Process-local misses try Redis and populate the process-local cache on a Redis hit.
Redis misses call the fallback and write both Redis and the process-local cache.
Redis cache read/write failures are logged, counted in metrics, and fail open; fallback results still return when fallback succeeds. invalidateRemote logs/counts Redis failures and rethrows them so callers do not assume invalidation succeeded.
Missing process-local/Redis TTL or ramp config disables that layer, records a disabled reason, and falls through to the next layer/fallback.

Node-redis computes each script's SHA, uses EVALSHA, and retries with EVAL after NOSCRIPT. Its cluster client routes scripts by their first key and performs that fallback on the selected shard. The GLIDE adapter uses GLIDE's native Script lifecycle and byte decoder; GLIDE routes scripts from their declared keys. Tracked reads are deliberately routed to primaries so a lagging replica cannot hide an invalidation watermark.

Serialization

The core Redis boundary is the client-agnostic DialCacheRedisClient interface. It exchanges serialized values as string | Buffer and does not expose client commands or wire encodings. Distinct untracked/tracked read and write Lua sources, the invalidation source, and wire constants are available from dialcache/redis-protocol. Custom adapters can throw the root-exported DialCacheRedisPayloadError, DialCacheRedisPayloadEncodingError, and DialCacheRedisProtocolError classes to distinguish malformed payloads, unsupported encodings, and Lua reply-domain violations in logs. DialCache records bounded cache_read, cache_write, or invalidation metrics by failure site.

Redis values use a compact binary frame:

byte 1      format version
bytes 2-9   Redis-created timestamp in milliseconds (uint64, big-endian)
byte 10     payload encoding (0 = UTF-8, 1 = raw binary)
bytes 11... serialized payload

Redis's Lua struct library packs and unpacks the timestamp. Redis TTL is authoritative, so expiry metadata is not duplicated in the frame. payload is produced by the cached function's serializer, or by JsonSerializer by default. Custom serializers can return either string or Buffer; strings are stored as UTF-8 and Buffers are stored byte-for-byte without base64 expansion. Adapters restore the same representation before calling serializer.load.

DialCache uses native JSON.stringify and JSON.parse by default. There is no runtime validation pass, so the default adds no traversal beyond JSON serialization itself. A top-level undefined result is supported with an internal sentinel.

When serializer.load rejects a Redis payload, DialCache records a serialization_load error, counts the read as a remote cache miss, runs the fallback, and attempts to replace the rejected payload. A validating custom serializer can therefore treat an incompatible cached value as a refreshable miss without adding a schema version to the cache key.

JsonSerializer validates JSON syntax only. It cannot detect that a structurally valid payload came from an incompatible application value schema. Applications that keep the same useCase across deployments must keep default-JSON values backward compatible. For an incompatible change, either provide a serializer whose load method validates and rejects the old shape, or change useCase to isolate the new cache entries. During a mixed deployment, mutually incompatible validating serializers can repeatedly reject and replace each other's values; correctness is preserved, but expect additional fallback and Redis-write load until the rollout converges.

When a cached function's resolved return type is statically JSON-compatible, serializer remains optional. This includes JSON primitives, arrays, plain object/interface shapes, optional object fields, and a top-level undefined. Types known not to survive the default round trip require a per-function Serializer<T>:

import { DialCache, type Serializer } from "dialcache";

const dialcache = new DialCache();
const dateSerializer: Serializer<Date> = {
  dump: (value) => value.toISOString(),
  load: (value) => new Date(Buffer.isBuffer(value) ? value.toString("utf8") : value),
};

const getUpdatedAt = dialcache.cached(
  (userId: string) => db.fetchUpdatedAt(userId),
  {
    keyType: "user_id",
    useCase: "GetUpdatedAt",
    cacheKey: (userId) => userId,
    serializer: dateSerializer,
  },
);

The compile-time guard rejects known incompatible shapes such as Date, Map, Set, bigint, symbols, functions, Buffers, typed arrays, method-bearing class instances, required nested undefined, unknown, and any. It applies to every cached() declaration because active layers are selected at runtime. A global Redis serializer is not parameterized by each cached return type, so it cannot discharge this requirement; non-JSON functions must select a typed per-function serializer.

This guard is deliberately conservative and is not a proof of runtime data. TypeScript cannot detect non-finite numbers, cyclic/shared references, runtime getter or toJSON behavior, or data-only class instances that look like plain objects. Opaque, generic, or deeply recursive types may also require an explicit serializer. Providing Serializer<T> (including an explicitly typed JsonSerializer<T>) is a trusted caller assertion; DialCache does not serialize-and-deserialize again to validate it.

Targeted invalidation and watermarks

Mutable Redis-backed use cases can opt into targeted invalidation by setting trackForInvalidation: true in the options and calling dialcache.invalidateRemote(keyType, id, futureBufferMs) after writes. The buffer is an application-owned safety value; DialCache cannot choose a universally safe nonzero value:

import { CacheLayer, DialCache, DialCacheKeyConfig } from "dialcache";
import { createNodeRedisDialCacheClient } from "dialcache/node-redis";

const dialcache = new DialCache({
  namespace: "users-api",
  redis: { client: createNodeRedisDialCacheClient(redisClient) },
});

// Chosen from this application's clock-skew bound and measured worst-case source/fallback timings.
const USER_INVALIDATION_BUFFER_MS = 5_000;

const getUser = dialcache.cached(
  (userId: string) => db.fetchUser(userId),
  {
    keyType: "user_id",
    useCase: "GetMutableUser",
    cacheKey: (userId) => userId,
    trackForInvalidation: true,
    // Strongly invalidated mutable data should disable request-local and process-local caching.
    defaultConfig: new DialCacheKeyConfig({
      ttlSec: { [CacheLayer.REMOTE]: 300 },
      ramp: { [CacheLayer.REMOTE]: 100 },
    }),
  },
);

await updateUser("123", patch);
await dialcache.invalidateRemote("user_id", "123", USER_INVALIDATION_BUFFER_MS);

Invalidation writes a Redis watermark at {encodedNamespace:encodedKeyType:encodedId}#watermark. Tracked Redis cache entries use the same Redis Cluster hash tag, for example {users-api:user_id:123}?locale=en#GetMutableUser:dialcache-frame-v1, so the value key and watermark key live in the same slot. Key components are percent-encoded before joining so delimiters inside IDs or args cannot collide with delimiters in the key format. Components may not contain { or } because those characters would corrupt the hash tag.

The internal :dialcache-frame-v1 suffix identifies values written with DialCache's binary protocol. Watermarks are stored as decimal timestamps.

A cached Redis value whose Redis-created timestamp is older than or equal to the watermark is treated as stale and refreshed through fallback. invalidateRemote(keyType, id, futureBufferMs) sets the watermark to the greater of its existing value and Redis's current time plus the buffer. While that future window is active, an invocation that reaches the tracked Redis read treats the covered value as a miss. If its fallback then reaches the tracked Redis write, Redis rejects the write and DialCache also suppresses the corresponding process-local population; the fallback value still returns to its caller. Request-local memoization remains unconditional, and invocations whose remote layer is disabled or ramped out do not consult the watermark and are not fenced by it.

The bundled timestamp protocol assumes that system clocks are synchronized across every Redis node eligible for primary promotion. Redis does not guarantee that TIME is monotonic across nodes, and DialCache does not detect or compensate for cross-node clock skew. If this deployment assumption is violated, failover can temporarily suppress tracked cache fills or allow a pre-invalidation value to remain readable until it expires or a later invalidation advances the watermark past its timestamp.

Tracked writes create a baseline watermark and extend its TTL to at least the value TTL plus one minute. Invalidation preserves that lifetime and extends it to cover the future buffer. DEFAULT_WATERMARK_TTL_SEC (4 hours) remains a configurable floor rather than a maximum, and reads do not extend watermark lifetime.

futureBufferMs must be a nonnegative safe integer. The default remains zero for backward compatibility, but zero provides no stale-publication protection once Redis time advances. Every production invalidation should pass a named, application-owned nonzero value based on that application's measured or conservatively bounded timings; there is no universally safe library value.

Size the buffer to cover the maximum expected negative clock skew between promotion-eligible Redis nodes plus the complete interval in which stale data could still reach the Redis write: source visibility or replication lag, the full remaining tail of any fallback that may already have observed the pre-mutation value, serializer.dump, Redis client queue and network latency, Lua script execution, the write itself, and a safety margin. Invalidate only after the source mutation commits. Underestimating this interval can allow a delayed stale fallback to repopulate Redis after the watermark window ends. Overestimating it lengthens the tracked Redis miss/write-suppression window described above, increasing fallback load without publishing stale values. A larger buffer does not delay or suppress returning fallback values to callers.

This is a timing contract rather than a cancellation or acquisition fence: the buffer prevents stale fallback results from passing that tracked Redis write only while the configured window remains active, and it does not force a fallback to read from an authoritative source.

Targeted invalidation is remote-only and enforced by Redis watermarks. invalidateRemote does not evict existing request-local or process-local entries. Strongly invalidated mutable data should disable request-local and process-local caching (or use a very short process-local TTL only when stale reads are acceptable).

Runtime config and ramp controls

Every cached function can provide a per-use-case defaultConfig; a cacheConfigProvider can override it at runtime. If the provider returns null, DialCache falls back to the cached function's defaultConfig. If neither exists, or a layer's TTL/ramp is missing or disabled, only that layer is skipped.

cacheConfigProvider is called for every enabled cached-function invocation before DialCache performs any cache lookup. Keep it cheap, cache any remote/config-store reads inside the provider, and avoid work that would erase the benefit of a cache hit.

import { CacheLayer, DialCache, DialCacheKeyConfig } from "dialcache";

const dialcache = new DialCache({
  cacheConfigProvider: async (key) => {
    if (key.useCase === "GetUser") {
      return new DialCacheKeyConfig({
        ttlSec: { [CacheLayer.LOCAL]: 30, [CacheLayer.REMOTE]: 300 },
        ramp: { [CacheLayer.LOCAL]: 100, [CacheLayer.REMOTE]: 25 },
      });
    }
    return null; // use the cached function's defaultConfig
  },
  rampSampler: ({ key, layer }) => deterministicPercentFor(`${key.urn}:${layer}`),
});

ramp values are percentages from 0 to 100. 0 disables the layer, 100 enables it, and intermediate values use rampSampler; the default sampler is deterministic by cache key and layer, so the same key is consistently sampled in or out of a partial rollout. Provider errors fail open and execute the fallback function.

Request coalescing

DialCache coalesces in-flight work at the lifetime of the first active cache layer:

When request-local caching is enabled, same-key callers in one outermost enable() scope share request-scoped in-flight work before the request-local lookup. Its resolved value is then memoized for later sequential calls in that scope.
When process-local or Redis caching is enabled, same-key callers share in-flight work within one DialCache instance before the first active shared layer. This is reported as scope="process", still applies when request-local caching is off, and can combine leaders from separate request scopes using the same instance.

With Redis configured, an instance-scoped leader that misses the process-local cache runs the Redis read and, on miss, the fallback/cache write; followers await that result. Process-local-only misses share the leader's fallback/cache write. This protects Redis and the source of truth from a thundering herd on hot keys.

Coalescing only applies when at least one cache layer is active. Calls outside enable() are true pass-through, and calls where request-local, process-local, and Redis are all disabled are true pass-through.

Because coalescing is keyed by cacheKey, concurrent calls with the same key share the leader's execution. Any argument ignored by cacheKey must be safe to share this way; include inputs such as locale, auth context, or cancellation behavior in the key when they can change the returned value or whether the underlying function should run separately.

const getUser = dialcache.cached(
  (userId: string) => db.fetchUser(userId),
  {
    keyType: "user_id",
    useCase: "GetUser",
    cacheKey: (userId) => userId,
    defaultConfig: DialCacheKeyConfig.enabled(60),
  },
);

Enabled context

Caching is off by default and only active inside a dialcache.enable(...) scope. This is deliberate: it lets you turn caching off in write paths so a stale read can't be cached around a write. DialCache uses Node AsyncLocalStorage to keep enabled state scoped to the current asynchronous call chain.

Enable once at your request boundary (e.g. a middleware that wraps read-request handling) so individual call sites don't each need it; wrap mutation handlers in disable():

await dialcache.enable(async () => {
  await getUser("123"); // cached

  await dialcache.disable(async () => {
    await updateUser("123", patch); // reads here are uncached
  });

  await getUser("123"); // cached again
});

Default is disabled — a cached function called outside any enable() scope simply runs uncached (no error), so wrap your read paths to actually cache.
Enabled state is async-scope-local, not process-global.
Nested enable / disable scopes restore the previous behavior when the callback completes. Nested enable() calls reuse the outer request-local scope rather than creating a new one.

Keys, ids, and extra dimensions

cached(fn, options) wraps a function; the wrapped callable has the same parameters and always returns a Promise. The cache key comes from a required cacheKey selector whose parameters are inferred from fn. Return a bare id, or return { id, args } to extract a field or add secondary dimensions:

The cacheKey selector is the value identity contract. It must include every input dimension that can affect the returned value; otherwise distinct calls can reuse the same cached value or share the same in-flight fallback through request coalescing.

const searchPosts = dialcache.cached(
  (userId: string, page: number, filter: string) => db.searchPosts(userId, page, filter),
  {
    keyType: "user_id",
    useCase: "SearchPosts",
    cacheKey: (userId, page, filter) => ({ id: userId, args: { page, filter } }),
    defaultConfig: DialCacheKeyConfig.enabled(60),
  },
);
await dialcache.enable(() => searchPosts("u1", 2, "active"));

DialCacheConfig.namespace is the logical cache namespace and the first component of every key. It defaults to "urn", so omitting it preserves keys such as urn:user_id:123#GetUser. Set a stable application-specific value when multiple applications may use the same Redis deployment:

const dialcache = new DialCache({
  namespace: "users-api",
  redis: { client: redisClient },
});

That produces Redis keys beginning with users-api:..., or {users-api:...} for invalidation-tracked values. namespace is DialCache's single cache-identity and key-partitioning setting: it participates in request-local, process-local, Redis, coalescing, deterministic ramp, invalidation, and metrics. It may not contain { or } because DialCache reserves those characters for Redis Cluster hash tags.

keyType + id is the invalidation unit for tracked Redis entries. dialcache.invalidateRemote("user_id", "123", USER_INVALIDATION_BUFFER_MS) writes one watermark for that user; any trackForInvalidation Redis entry with the same keyType and id is refreshed across all args variants when Redis is read. Existing request-local and process-local hits follow the limitation above, and untracked Redis entries do not consult the watermark. useCase identifies the individual cache (it's the metrics label and part of the stored key).
args are part of the cache key — different args produce different entries — but invalidation is by id only.
Scalar key equality is string-based. Runtime type is not an identity dimension: for matching surrounding dimensions, numeric 1, string "1", and bigint 1n identify the same key; argument values null and "null" also match. -0 matches 0, and an undefined argument is omitted. If a deployment changes the logical meaning represented by a scalar, change an explicit identity dimension such as keyType, useCase, or an argument name/value.
Non-key inputs (for example a db handle) are simply parameters the cacheKey selector ignores. They still reach fn for non-coalesced executions, but concurrent same-key cache misses share the leader's execution, so do not ignore values like AbortSignal, auth context, locale, or other request-scoped inputs unless sharing one result is correct.
Methods: pass obj.method.bind(obj) (or (...a) => obj.method(...a)) — a bare obj.method reference loses this.

Migrating to `namespace`

The public urnPrefix option and DialCacheKey.urnPrefix property were renamed to namespace. For callers that did not configure redis.keyPrefix, replacing the property name while keeping the same value preserves generated key bytes, invalidation watermarks, deterministic ramp cohorts, and cache behavior:

// Before
new DialCache({ urnPrefix: "users-api", redis: { client: redisClient } });

// After
new DialCache({ namespace: "users-api", redis: { client: redisClient } });

Callers that omitted urnPrefix can continue omitting namespace; both defaults are "urn". TypeScript rejects the removed property. The DialCache constructor throws DialCacheConfig.urnPrefix was renamed to "namespace", and direct DialCacheKey construction throws DialCacheKeyInit.urnPrefix was renamed to "namespace", when an untyped or JavaScript caller still supplies it. These errors prevent a custom legacy value from silently falling back to urn.

redis.keyPrefix was removed so namespace is the only public cache-partitioning control. TypeScript rejects the removed Redis option, and untyped or JavaScript construction throws RedisConfig.keyPrefix was removed; use DialCacheConfig.namespace for cache identity. Move any required application or environment separation into a stable namespace such as production-users-api.

Changing the namespace value intentionally creates a cold-cache boundary across every layer. Removing a previous Redis key prefix also changes the remote key bytes even if the namespace value stays the same. Old and new keyspaces do not share Redis values or invalidation watermarks. During an overlapping deployment, an invalidation handled by one version is invisible to the other, which can continue serving a stale tracked value until its value TTL expires. If remote invalidation correctness matters, a normal rolling deployment is unsafe: use a coordinated no-overlap cutover, or an operational bridge that prevents both versions from serving remote cache across mutations (for example, temporarily disable and clear remote caching during the transition). After the cutover, provision for fallback/refill load and allow old Redis keys to expire by TTL.

Cached-value ownership

Treat values returned by cached functions as immutable. DialCache does not clone or freeze values stored in request-local or process-local memory. Mutating a cached object can therefore be observed by later callers in the same request, callers in other requests that hit the process-local cache, or callers that coalesced onto the same in-flight result.

This contract includes nested objects and arrays, Map, Set, Buffer, typed arrays, and class instances. Redis deserialization can produce a different reference from an in-memory hit, so reference identity is layer-dependent and is not part of the API contract; never rely on a specific layer cloning a value before mutation.

If a caller needs a mutable value, copy it explicitly before changing it:

const sharedUser = await getUser("123");
const editableUser = structuredClone(sharedUser);
editableUser.displayName = "New name";

Use a narrower copy when its semantics are sufficient; the ownership boundary is the caller's responsibility.

Metrics

Metrics are disabled unless a DialCacheMetricsAdapter is passed to the constructor. new DialCache() does not import a metrics backend, register collectors, or emit metrics.

Prometheus

Install prom-client separately, create the registry your application owns, and pass the explicit Prometheus adapter to DialCache:

pnpm add prom-client@^15.1.3

import { Registry } from "prom-client";
import { DialCache } from "dialcache";
import { createPrometheusDialCacheMetrics } from "dialcache/prometheus";

const registry = new Registry();
const dialcache = new DialCache({
  namespace: "users-api",
  metrics: createPrometheusDialCacheMetrics({
    registry,
    prefix: "myapp_", // myapp_dialcache_request_counter, etc.
  }),
});

app.get("/metrics", async (_req, res) => {
  res.type(registry.contentType).send(await registry.metrics());
});

The adapter requires a caller-owned Registry; it never uses the global default registry and does not clear or otherwise own the registry lifecycle. Multiple adapters with the same registry and prefix reuse existing collectors when their type, help, labels, histogram buckets, and exemplar mode match. Adapter construction fails before registering anything if a same-name collector has an incompatible schema; use a unique prefix or a separate registry to resolve the collision.

The Prometheus adapter emits:

Metric	Type	Labels	Description
`dialcache_request_counter`	Counter	`cache_namespace`, `use_case`, `key_type`, `layer`	Cache-layer requests that reached an enabled layer
`dialcache_miss_counter`	Counter	`cache_namespace`, `use_case`, `key_type`, `layer`	Cache misses
`dialcache_disabled_counter`	Counter	`cache_namespace`, `use_case`, `key_type`, `layer`, `reason`	Cache skips (`context`, `missing_config`, `invalid_ttl`, `ramped_down`, `config_error`)
`dialcache_error_counter`	Counter	`cache_namespace`, `use_case`, `key_type`, `layer`, `error`, `in_fallback`	Cache/fallback errors classified by a bounded failure site
`dialcache_invalidation_counter`	Counter	`cache_namespace`, `key_type`, `layer`	Invalidation calls for the layers touched today
`dialcache_coalesced_counter`	Counter	`cache_namespace`, `use_case`, `key_type`, `scope`	Coalesced requests split by `request_local` or `process` scope
`dialcache_get_timer`	Histogram	`cache_namespace`, `use_case`, `key_type`, `layer`	Cache get latency in seconds
`dialcache_fallback_timer`	Histogram	`cache_namespace`, `use_case`, `key_type`, `layer`	Time spent in the underlying function
`dialcache_serialization_timer`	Histogram	`cache_namespace`, `use_case`, `key_type`, `layer`, `operation`	Redis serializer dump/load latency
`dialcache_size_histogram`	Histogram	`cache_namespace`, `use_case`, `key_type`, `layer`	Serialized Redis payload size in bytes

Every metric carries cache_namespace, including disabled-context, key-construction, coalescing, and invalidation paths that do not have a constructed key. Its value is DialCacheConfig.namespace, defaulting to urn. The layer label is request_local, local (process-local), or remote. Disabled-context, key-construction, and config-provider failures use noop because no cache layer was reached. The bounded scope label on dialcache_coalesced_counter distinguishes request-local from instance-scoped single-flight work. scope="process" coordinates calls only within one DialCache instance; separate instances in the same process do not share in-flight state.

Metric names are unchanged, but cache_namespace is a new required label/tag on every series. Update dashboards and alerts that enumerate exact label sets. A Prometheus registry containing collectors created by an older DialCache adapter has an incompatible schema; construct the upgraded adapter in a fresh registry/process, or use a new adapter prefix during an in-process migration.

Datadog

Install hot-shots separately, create the DogStatsD client your application owns, and pass it to the Datadog adapter:

pnpm add hot-shots@^17.0.0

import StatsD from "hot-shots";
import { DialCache } from "dialcache";
import { createDatadogDialCacheMetrics } from "dialcache/datadog";

const dogStatsD = new StatsD({
  host: process.env.DD_AGENT_HOST,
  globalTags: { service: "users-api", env: process.env.DD_ENV ?? "development" },
  errorHandler: (error) => logger.warn("DogStatsD error", { error }),
});

const dialcache = new DialCache({
  namespace: "users-api", // cache identity and cache_namespace tag
  metrics: createDatadogDialCacheMetrics({
    client: dogStatsD,
    observationMetricType: "distribution",
    namespace: "dialcache", // metric-name prefix: dialcache.request.count, etc.
  }),
});

// After outstanding cache operations finish during application shutdown:
dogStatsD.close();

hot-shots is the supported and tested client, but the adapter depends only on the exported DatadogDogStatsDClient structural interface. DialCache does not import or install hot-shots, create a client, flush buffers, close sockets, or otherwise own the client lifecycle.

observationMetricType is required. "distribution" is recommended when latency and size percentiles must aggregate across hosts; enable the desired distribution percentiles and aggregations in Datadog. Choose "histogram" when host-level histogram aggregation matches your existing Datadog setup. The choice applies uniformly to all four duration/size metrics. Both modes produce Datadog custom metrics. Distribution volume scales with unique tag-value combinations: Datadog counts five baseline aggregations per combination, and enabling percentile aggregations adds five more. Review Datadog's custom-metrics billing guidance before rollout. Do not send both types under the same namespace: when changing types, use a new namespace during migration so one metric identity never mixes histogram and distribution points.

DatadogMetricsOptions.namespace is the metric-name namespace and defaults to dialcache. It is separate from DialCacheConfig.namespace, the logical cache namespace emitted as the cache_namespace tag. The Datadog metric namespace must start with a letter and contain only letters, numbers, underscores, and dot-separated non-empty segments. The adapter rejects invalid metric namespaces and final metric names longer than 200 characters rather than relying on client-side normalization. A hot-shots prefix is applied after the adapter constructs the name, so include that prefix when checking the final length and avoid combining it with the metric namespace accidentally. Client-level globalTags are appended by hot-shots; the table below lists the tags added by the adapter.

The Datadog adapter emits exact increments of 1 for counters and preserves seconds and bytes without unit conversion:

Metric	Type	Tags	Description
`dialcache.request.count`	Count	`cache_namespace`, `use_case`, `key_type`, `layer`	Cache-layer requests that reached an enabled layer
`dialcache.miss.count`	Count	`cache_namespace`, `use_case`, `key_type`, `layer`	Cache misses
`dialcache.disabled.count`	Count	`cache_namespace`, `use_case`, `key_type`, `layer`, `reason`	Cache skips by bounded reason
`dialcache.error.count`	Count	`cache_namespace`, `use_case`, `key_type`, `layer`, `error`, `in_fallback`	Cache/fallback errors by bounded failure site
`dialcache.invalidation.count`	Count	`cache_namespace`, `key_type`, `layer`	Invalidation calls for the layers touched
`dialcache.coalesced.count`	Count	`cache_namespace`, `use_case`, `key_type`, `scope`	Coalesced requests by sharing scope
`dialcache.get.duration`	Distribution or histogram	`cache_namespace`, `use_case`, `key_type`, `layer`	Cache get latency in seconds
`dialcache.fallback.duration`	Distribution or histogram	`cache_namespace`, `use_case`, `key_type`, `layer`	Time spent in the underlying function in seconds
`dialcache.serialization.duration`	Distribution or histogram	`cache_namespace`, `use_case`, `key_type`, `layer`, `operation`	Redis serializer dump/load latency in seconds
`dialcache.serialization.size`	Distribution or histogram	`cache_namespace`, `use_case`, `key_type`, `layer`	Serialized Redis payload size in bytes

Synchronous client throws are isolated by DialCache's fail-open metrics boundary. Buffered transport failures happen outside that synchronous call, so configure the DogStatsD client's error handling and shutdown behavior as part of application ownership.

Error categories

The error label reports where an operation failed rather than copying the thrown value's class or Error.name:

`error`	Meaning
`key_construction`	The cache-key selector or `DialCacheKey` construction failed
`config_resolution`	Runtime or layer configuration, or ramp resolution, failed
`cache_read`	A local-cache or Redis read failed
`cache_write`	A local-cache or Redis write failed
`serialization_load`	Deserializing a Redis payload failed
`serialization_dump`	Serializing a value for Redis failed
`invalidation`	Writing an invalidation watermark failed
`fallback`	The wrapped application function failed
`unknown`	Reserved for an otherwise unclassified future failure site

These values are defined by the backend-neutral core and are identical for every metrics adapter. Raw thrown values, error names, messages, cache IDs, arguments, and Redis keys are never included in metric labels. Operational errors are still passed to the configured logger where the existing failure path logs them. in_fallback remains the explicit cache-plumbing-versus-application distinction for existing dashboards.

Applications upgrading from exception-name labels must update alerts and dashboards to match these failure-site values.

Custom adapters

For other telemetry backends, implement DialCacheMetricsAdapter and pass the adapter through new DialCache({ metrics }). Every backend-neutral label object exposes the logical namespace as camel-case cacheNamespace; adapters should map it to their backend's cache_namespace label/tag. This field is present even when no key or cache layer was reached. Synchronous adapter failures are isolated from cache behavior and application fallbacks. Omit metrics to disable metrics.

Migrating from implicit Prometheus metrics

Before	After
`new DialCache()` registered Prometheus collectors	`new DialCache()` has metrics disabled
`new DialCache({ metrics: false })`	`new DialCache()`
`new DialCache({ metricsRegistry, metricsPrefix })`	`new DialCache({ metrics: createPrometheusDialCacheMetrics({ registry, prefix }) })`
Prometheus imports from `dialcache`	Prometheus imports from `dialcache/prometheus`

Current scope

Included:

Request-local caching for the lifetime of the outermost enabled context
Process-local TTL/LRU cache with a global entry-count bound
Redis TTL cache
Request-local → process-local → Redis → fallback read-through chain
Lua-backed Redis reads and writes with Redis-generated timestamps
Versioned binary Redis frames for UTF-8 and Buffer serializer output
Native node-redis script registration with automatic NOSCRIPT recovery
Native Valkey GLIDE adapter with explicit script disposal and automatic script-cache recovery
Standalone Redis, Valkey, and Redis Cluster support
JSON and custom serializer support for Redis values
Duplicate and reserved use-case validation
Fail-open behavior for key/config/cache read-write errors; explicit invalidation mutations surface failures
Runtime config provider with fallback to cached-function defaultConfig
Per-layer TTL and ramp controls
Deterministic default ramp sampler with injectable override hooks
Missing config disables only the relevant layer and falls through
Optional Prometheus adapter with caller-owned registries and duplicate-registration safety
Optional Datadog DogStatsD adapter with caller-owned clients and explicit distribution/histogram semantics
Backend-neutral custom metrics adapter hook; metrics are disabled when omitted
Cache-vs-fallback error classification through the in_fallback label
Serialization latency and cached payload size metrics for Redis values
Logger injection for cache operational failures
trackForInvalidation on cached functions
invalidateRemote(keyType, id, futureBufferMs) Redis watermark API
Redis Cluster hash-tagged value/watermark keys for invalidation-tracked entries
Dynamically extended watermark TTL with a configurable DEFAULT_WATERMARK_TTL_SEC floor
Future-buffer behavior that avoids cache writes during active invalidation windows
Request-scoped and instance-scoped coalescing for active cache work

Not included yet:

Framework middleware helpers/integrations
cachedObject
Expanded examples

Request-local benchmark

From a repository checkout, run the semantic microbenchmark after installing dependencies:

pnpm benchmark:request-local

The command builds dist before reporting request-local sequential-hit throughput plus request-local and instance-scoped coalescing fan-out. The benchmark is a maintainer tool and is not included in the published package. It asserts fallback counts and returned values but deliberately applies no timing threshold. Override its work sizes with DIALCACHE_BENCH_ITERATIONS and DIALCACHE_BENCH_FANOUT.

Releasing

Publishing is driven manually from the Release workflow in GitHub Actions. Run it from main; the workflow rejects any other ref or a stale main commit. Semantic Release selects the next version from Conventional Commits since the highest stable vX.Y.Z tag. Breaking changes bump major, feat bumps minor, and every other allowed PR-title type (fix, perf, docs, style, refactor, test, build, chore, ci, and revert) bumps patch. The highest required bump wins.

After validating, building, and package-testing the release artifact, Semantic Release stamps the package version, creates the Git tag, publishes the public npm package with provenance, and publishes the GitHub release. The repository's package.json remains at its development seed version between releases.

The workflow retains the NPM_TOKEN secret as a publishing fallback. After configuring lan17/DialCache and release.yaml as the package's trusted GitHub publisher, remove the long-lived token; the workflow's OIDC permission then provides npm authentication and provenance.

Name		Name	Last commit message	Last commit date
Latest commit History 217 Commits
.github		.github
scripts		scripts
src		src
test		test
.gitignore		.gitignore
AGENTS.md		AGENTS.md
LICENSE		LICENSE
README.md		README.md
package.json		package.json
pnpm-lock.yaml		pnpm-lock.yaml
release.config.mjs		release.config.mjs
tsconfig.json		tsconfig.json
vitest.config.ts		vitest.config.ts
vitest.integration.config.ts		vitest.integration.config.ts

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DialCache

Install

Quick start

Request-local cache

Process-local cache

Redis-backed TTL cache

Serialization

Targeted invalidation and watermarks

Runtime config and ramp controls

Request coalescing

Enabled context

Keys, ids, and extra dimensions

Migrating to namespace

Cached-value ownership

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Prometheus

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Custom adapters

Migrating from implicit Prometheus metrics

Current scope

Request-local benchmark

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