Cache Invalidation Basics

Cache invalidation is the work of making sure a cached copy stops being used when it is no longer correct. Real applications change products, prices, permissions, settings, pages, and files, so every cache needs a plan for becoming fresh again.

The main skill is tying each cached value to the data that can make it stale. A junior PHP developer should be able to choose a TTL, delete affected keys after writes, use versioned keys where helpful, and avoid clearing far more cache than a change requires.

Start With The Risk Of Stale Data

Before caching a value, ask what happens if it is wrong for 10 seconds, 5 minutes, or an hour.

<?php

declare(strict_types=1);

function staleRisk(string $dataType): string
{
    return match ($dataType) {
        'product_price' => 'high: stale prices can affect orders',
        'user_permissions' => 'high: stale permissions can leak access',
        'blog_sidebar' => 'low: brief staleness is usually acceptable',
        default => 'unknown: decide how stale this data may be',
    };
}

echo staleRisk('product_price') . PHP_EOL;

// Prints:
// high: stale prices can affect orders

A blog sidebar can often tolerate a longer TTL. Permissions and prices usually need targeted invalidation and a short fallback TTL.

TTL-Based Invalidation

A TTL is the simplest invalidation strategy. The cache entry expires after a fixed number of seconds.

<?php

declare(strict_types=1);

function ttlForCachedValue(string $valueType): int
{
    return match ($valueType) {
        'homepage_featured_products' => 300,
        'shipping_rate_quote' => 60,
        'product_price' => 30,
        'compiled_templates' => 0,
        default => 120,
    };
}

echo ttlForCachedValue('shipping_rate_quote') . PHP_EOL;

// Prints:
// 60

TTL-only caching is resilient and easy to reason about. Its tradeoff is that users can see stale data until expiry. A TTL of 0 should be reserved for data with a deliberate manual or deployment-based invalidation path.

Delete Affected Keys After Writes

When source data changes, remove the cache keys that depend on it. This is explicit invalidation.

<?php

declare(strict_types=1);

function productCacheKeysToDelete(int $productId, string $categorySlug): array
{
    return [
        'product:detail:' . $productId,
        'product:summary:' . $productId,
        'homepage:featured_products',
        'category_products:' . $categorySlug . ':page:1',
    ];
}

print_r(productCacheKeysToDelete(42, 'lighting'));

// Prints:
// Array
// (
//     [0] => product:detail:42
//     [1] => product:summary:42
//     [2] => homepage:featured_products
//     [3] => category_products:lighting:page:1
// )

The difficult part is knowing every cache entry that depends on changed data. Central key builders and clear naming conventions reduce missed keys.

Centralise Key Builders

If reads and invalidation construct keys differently, stale values survive.

<?php

declare(strict_types=1);

function productDetailKey(int $productId): string
{
    return 'product:detail:' . $productId;
}

function categoryProductsKey(string $categorySlug, int $page): string
{
    return 'category_products:' . $categorySlug . ':page:' . $page;
}

echo productDetailKey(42) . PHP_EOL;
echo categoryProductsKey('lighting', 1) . PHP_EOL;

// Prints:
// product:detail:42
// category_products:lighting:page:1

Small key-builder functions make cache reads, writes, deletes, logs, and tests use the same key shape.

Invalidate After The Source Changes

The database or durable storage is the source of truth. Update it first, then invalidate the cache.

<?php

declare(strict_types=1);

function productUpdatePlan(bool $databaseUpdateSucceeded): array
{
    if (!$databaseUpdateSucceeded) {
        return [
            'invalidate_cache' => false,
            'reason' => 'source update failed, so the cached value still matches',
        ];
    }

    return [
        'invalidate_cache' => true,
        'reason' => 'delete dependent keys after the source update succeeds',
    ];
}

print_r(productUpdatePlan(true));

// Prints:
// Array
// (
//     [invalidate_cache] => 1
//     [reason] => delete dependent keys after the source update succeeds
// )

If cache deletion fails after a successful database update, stale data may still be served. Log the failure and retry when the value is important. A short TTL limits the damage if explicit invalidation fails.

Versioned Keys

A versioned key changes when the underlying record changes. The application naturally reads a fresh key without needing to find and delete every old entry immediately.

<?php

declare(strict_types=1);

function versionedProductKey(int $productId, string $updatedAt): string
{
    return 'product:detail:' . $productId . ':v' . sha1($updatedAt);
}

echo versionedProductKey(42, '2026-05-20T10:30:00Z') . PHP_EOL;

// Prints:
// product:detail:42:ve228f6b90aca7a91c15142dea92d3ff260ff6851

Old entries may remain until their TTL expires or cleanup removes them. Versioning prevents stale reads, but it does not remove the need to control memory usage.

Dependency Tags

Some cache libraries support tags. A rendered product page might be tagged with product:42 and category:lighting, allowing related entries to be removed together.

<?php

declare(strict_types=1);

function cacheTagsForProduct(int $productId, string $categorySlug): array
{
    return [
        'product:' . $productId,
        'category:' . $categorySlug,
    ];
}

print_r(cacheTagsForProduct(42, 'lighting'));

// Prints:
// Array
// (
//     [0] => product:42
//     [1] => category:lighting
// )

Even when a backend does not support tags directly, thinking in dependencies helps identify which keys need deleting.

Avoid Broad Cache Clears

Clearing an entire cache can hide a weak invalidation design. It removes unrelated entries, triggers expensive rebuilds, and can create a sudden spike in database or API traffic.

<?php

declare(strict_types=1);

function invalidationScope(string $changeType): string
{
    return match ($changeType) {
        'single_product_saved' => 'delete product detail, summary, and affected listing keys',
        'template_format_changed' => 'clear rendered fragments during deployment',
        'global_tax_rate_changed' => 'invalidate affected price and quote keys',
        default => 'identify dependent keys before clearing cache',
    };
}

echo invalidationScope('single_product_saved') . PHP_EOL;

// Prints:
// delete product detail, summary, and affected listing keys

Prefer targeted invalidation. Use broad clears deliberately for cases such as deployments, emergency repairs, or global format changes.

Cache Stampedes

When a popular key expires, many requests may try to rebuild it at once. This is called a cache stampede.

Common mitigations include:

• adding a short lock around rebuilding;
• serving stale data briefly while one request refreshes it;
• adding small random TTL differences so keys do not all expire together;
• warming important entries after deployment.

<?php

declare(strict_types=1);

function ttlWithJitter(int $baseTtl, int $jitterSeconds): int
{
    return $baseTtl + intdiv($jitterSeconds, 2);
}

echo ttlWithJitter(300, 40) . PHP_EOL;

// Prints:
// 320

The example is deterministic so it is easy to run. Real code may use a small random offset.

Choose Read And Write Ordering Explicitly

Cache-aside reads usually check the cache, load the source after a miss, then store the result. Writes require a policy. A common sequence is:

1. Commit the source-of-truth database change.
2. Delete or replace affected cache entries.
3. Return success only according to the application's consistency contract.

Deleting before the database commit creates a race. Another request can miss the cache, read the old database value, and repopulate stale data before the write commits.

Updating the cache before the database also risks publishing a value whose source write later fails. Source first, invalidation second is usually the understandable default.

There remains a failure gap: the database can commit and cache deletion can fail. Use a bounded TTL, retries or an outbox-backed invalidation worker when staleness is important. Record the failed key and source version rather than logging sensitive cached content.

Decide Whether To Delete Or Replace

Deleting is simple. The next reader reloads authoritative data. Replacing can avoid a miss but requires the writer to construct exactly the same representation as the read path.

Delete when many code paths can change the record, the cached representation is complex, or rebuilding is cheap. Replace when the new complete value is already available and the update can preserve key version and serialization rules.

Partial mutation of cached documents is risky. If a cached product contains price, categories, stock summary, and display text, changing only the price may leave other fields stale. Prefer rebuilding the full value or deleting it.

Handle Multi-Layer Caches

A response may pass through APCu, Redis, an application framework, a reverse proxy, a CDN, and a browser. Invalidating Redis does not purge a CDN response, and changing a CDN key does not reset an in-process APCu entry.

Document each layer:

Browser: Cache-Control max-age=60
CDN: surrogate key product-42
Redis: product:detail:42:v3
APCu: process-local parsed configuration

For a product update, identify which layers contain product-dependent data and which can expire naturally. Use response cache headers and surrogate-key purges deliberately. Avoid caching personalized responses in a shared layer unless the cache key and privacy controls are proven correct.

Protect Security-Sensitive Decisions

Permissions, account suspension, subscription entitlement, and feature access can become security issues when stale. A long TTL may let revoked access continue.

Prefer authoritative checks or very short, explicitly invalidated caches for high-risk decisions. Include tenant, user, resource, permission, and policy version in the key where relevant. Never let a missing tenant dimension share one customer's authorization result with another.

A cache outage should not automatically grant access. Define fail-closed or authoritative fallback behavior. Availability requirements do not justify silently bypassing authorization.

Prevent Old Writers From Restoring Stale Data

Concurrent cache rebuilds can finish out of order:

Request A reads source version 10 slowly
Source changes to version 11
Request B caches version 11
Request A finishes and overwrites the key with version 10

Versioned keys avoid the overwrite because each source version uses a different key. Another option stores a version in the value and uses a compare-and-set or script so an older version cannot replace a newer one.

Locks used for stampede control need expiry and ownership tokens. A process can pause beyond the lock TTL; it must not delete a lock now owned by another worker.

Observe Cache Correctness

Track more than hit rate. A high hit rate can mean the application serves stale data efficiently.

Useful metrics include:

• hit, miss, and error rates;
• rebuild duration;
• invalidation attempts and failures;
• age or source version of served entries;
• stampede-lock contention;
• fallback database load;
• memory usage and evictions;
• CDN purge failures;
• authorization-cache bypass or rejection counts.

Add a safe diagnostic path that compares a sampled cached value's source version with authoritative data. Do not compare or log sensitive payloads unnecessarily.

Test The Failure Cases

Tests should cover:

• source update failure causes no invalidation;
• successful source update deletes the expected keys;
• deletion failure is recorded and bounded by TTL;
• old serialized versions are rejected;
• two tenants never share a key;
• a stampede lock allows one rebuild;
• stale-while-revalidate never exceeds the permitted stale window;
• cache unavailability follows the documented fallback;
• broad clears are not used for one-record changes.

Time-dependent tests are more reliable with an injected clock than real sleep calls. A fake cache can record operations, but integration tests should also verify the actual backend's TTL and atomic-operation semantics.

What To Check

Before moving on, make sure you can:

• judge how dangerous stale data would be for a cached value;
• choose a TTL based on acceptable staleness;
• delete specific keys after a successful source-of-truth update;
• centralise key builders so reads and deletes agree;
• explain when versioned keys and dependency tags help;
• avoid broad cache clears unless there is a deliberate reason;
• recognize cache stampede risk for popular keys;
• order database writes and invalidation safely;
• map dependencies across process, Redis, proxy, CDN, and browser caches;
• protect authorization and tenant-specific cache keys;
• monitor freshness and invalidation failures, not only hit rate.

The ordering and stampede cases are developed further in Cache Races, Stampedes, And Fencing.