agentsclimarketplace

Redis patterns

Skill pekral/cursor-rules/skills/redis-patterns

PHP and Laravel Cursor rules — coding standards, testing, and conventions for the Cursor editor. Install via Composer.

Install
npx -y skills add pekral/cursor-rules --skill redis-patterns

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 5 stars5 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Use when using Redis in a Laravel app — caching strategies, atomic/distributed locks, rate limiting, stampede protection, pub/sub, pipelines, and key/TTL design beyond raw query tuning.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

7.7 KB, ~1.9k tokens by cl100k_base, as published. Nobody here has run it

Redis Patterns

Constraints

  • Apply @rules/laravel/laravel.mdc — use the framework's facades (Cache, RateLimiter, Redis), not a raw client.
  • Apply @rules/laravel/queue-debouncing.mdc for queue/job coalescing concerns when Redis backs the queue.
  • Cross-link @rules/sql/optimalize.mdc (DB-level caching) — Redis caching sits in front of the query tuning that rule owns; cache the result, do not paper over an unindexed query.
  • final classes, declare(strict_types=1), Pest tests (use the array cache driver in tests unless asserting Redis-specific behavior).
  • Always set a TTL. Keys without expiry accumulate and cause memory pressure.

Use when

  • Adding caching, rate limiting, distributed coordination, or pub/sub to a Laravel app.
  • Choosing a cache strategy, protecting a cold cache from stampede, or designing key/TTL conventions.
  • Configuring Redis as the session, cache, or queue store.

Use Laravel facades throughout. Reach for raw Redis::command(...) only for structures the Cache abstraction does not expose (sorted sets, streams).

Caching Strategies

Cache-Aside (default for read-heavy data)

$product = Cache::remember("product:{$id}", now()->addMinutes(10), fn () =>
    Product::findOrFail($id),
);

remember() is read-through cache-aside: returns the cached value or runs the closure, stores it, and returns it. Use rememberForever() only with an explicit invalidation path.

Write-Through (consistency required)

$product->update($data);
Cache::put("product:{$product->id}", $product->fresh(), now()->addMinutes(10));
// Or simply invalidate so the next read repopulates:
Cache::forget("product:{$product->id}");

Invalidate (forget) rather than rewrite when the cached shape may differ from the model.

Cache Tags (grouped invalidation)

Cache::tags(['products', "category:{$categoryId}"])
    ->remember("product:{$id}", now()->addMinutes(10), fn () => Product::findOrFail($id));

Cache::tags(["category:{$categoryId}"])->flush(); // drop the whole group at once

Tags require the redis (or memcached) store — not file/database. They add key overhead; use for genuine groups, not single keys.

Stampede Protection

A cold/expired hot key can trigger many concurrent rebuilds (thundering herd). Guard the rebuild with an atomic lock so only one worker recomputes.

public function getReport(string $key): array
{
    return Cache::get($key) ?? Cache::lock("rebuild:{$key}", seconds: 10)->block(5, function () use ($key) {
        // Re-check inside the lock — another worker may have just populated it.
        return Cache::get($key) ?? tap($this->computeReport(), fn ($v) =>
            Cache::put($key, $v, now()->addMinutes(15)),
        );
    });
}
  • Cache::lock() is an atomic SET NX PX lock; block(5, ...) waits up to 5s to acquire.
  • Alternative for very hot keys: stale-while-revalidate — serve the slightly stale value while one worker refreshes in the background, avoiding any blocking.

Distributed Locks

Coordinate exclusive access across workers/requests.

$lock = Cache::lock('payment:'.$orderId, seconds: 30);
if ($lock->get()) {
    try {
        $this->processPayment($orderId);
    } finally {
        $lock->release(); // always release in finally
    }
}
  • The TTL must exceed the expected work; on crash the lock auto-expires so it never wedges permanently.
  • Only the owner may release — Laravel tracks the owner token, so release() is safe. Use forceRelease() only deliberately.
  • For bounded concurrency (N parallel, not 1), use Redis::funnel('job')->limit(3)->then(fn () => ...).

Rate Limiting

Prefer the framework limiter over hand-rolled counters.

use Illuminate\Support\Facades\RateLimiter;

$executed = RateLimiter::attempt("send:{$user->id}", maxAttempts: 5, function (): void {
    $this->sendMessage();
}, decaySeconds: 60);

if (! $executed) {
    abort(429); // or RateLimiter::availableIn($key) for retry hint
}
  • HTTP routes: define a named limiter (RateLimiter::for('api', fn ($r) => Limit::perMinute(60)->by($r->user()?->id ?: $r->ip()))) and apply throttle:api middleware.
  • For high-throughput throttling, Redis::throttle('key')->allow(60)->every(60)->then($ok, $tooMany) runs the check in a single atomic Redis call.

Key Naming & TTL Discipline

{app}:{resource}:{id}            myapp:product:123
{app}:{resource}:{id}:{field}    myapp:order:456:status
{app}:{resource}:{date}          myapp:stats:pageviews:2026-06-14
DataSuggested TTL
API/query response cache5–15 min
User session24h
Rate-limit window= window size
Short-lived token5–10 min
Reference/static data1h–1 week
  • Use Laravel's cache.prefix for the app namespace; do not hand-prefix every key.
  • Never run KEYS * in production (O(N), blocks the server) — use SCAN via Redis::scan().

Eviction Policy

Set maxmemory + maxmemory-policy in redis.conf per role:

PolicyUse for
allkeys-lruGeneral cache (evict least-recently-used)
volatile-lruMixed cache + must-keep data (only evict keys with TTL)
allkeys-lfuSkewed access (hot keys survive)
noevictionQueue / session store — errors instead of dropping data

Critical: do not point a Redis queue/session connection at an allkeys-lru instance — it will silently evict jobs/sessions. Separate the cache instance/DB from the queue instance.

Pub/Sub

Fire-and-forget broadcast; no delivery guarantee or replay.

Redis::publish('orders', json_encode(['id' => $order->id]));

// Long-running listener (artisan command):
Redis::subscribe(['orders'], function (string $message): void {
    $this->handle(json_decode($message, true));
});

If you need durability, consumer groups, or replay, use the Laravel queue (below) or Redis Streams via Redis::command('XADD', ...) — Pub/Sub drops messages for absent subscribers.

Pipelines & Transactions

Batch many commands in one round trip; use a transaction when they must apply atomically.

Redis::pipeline(function ($pipe) use ($ids): void {
    foreach ($ids as $id) {
        $pipe->del("product:{$id}");
    }
}); // one round trip, NOT atomic

Redis::transaction(function ($tx) use ($key): void {
    $tx->incr($key);
    $tx->expire($key, 60);
}); // MULTI/EXEC — all-or-nothing

Pipelines cut latency for bulk ops; transactions add atomicity. Do not loop single commands when a pipeline fits.

Queues, Sessions & Stores

  • Queues: set QUEUE_CONNECTION=redis. Run Laravel Horizon for Redis queues — it gives supervisor config, metrics, and a dashboard. For coalescing bursty jobs see @rules/laravel/queue-debouncing.mdc.
  • Sessions / cache: SESSION_DRIVER=redis, CACHE_STORE=redis. Keep sessions/queue on a noeviction instance and cache on an allkeys-lru instance (or distinct DB indexes) so cache eviction never drops a session or job.
  • Size the predis/phpredis pool and set socket_timeout / read_timeout so a stalled Redis fails fast instead of hanging requests.

Done when

  • Every key has an intentional TTL and follows the naming convention.
  • Hot/cold cache rebuilds are stampede-protected with Cache::lock.
  • Cache and queue/session use separate instances or DBs with matching eviction policies.
  • Rate limiting uses RateLimiter / Redis::throttle, not ad-hoc counters.
  • Pest tests cover cache hit/miss and lock paths; no KEYS * in production code.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.