46:"/_next/static/chunks/2g8w-80ml0qgh.js" 47:"/_next/static/chunks/0iv56yrji_20j.js" 48:"/_next/static/chunks/07n38_x1c5ol5.js" 49:"/_next/static/chunks/3i6o_ezb7k38p.js" 4a:"/_next/static/chunks/2pzht2w_wvlxv.js" 4b:"/_next/static/chunks/09f5cfkroz048.js" 4c:"/_next/static/chunks/0wa9m1-tphf9u.js" 4d:"/_next/static/chunks/1jl6tco-uuy-j.js" 4e:"/_next/static/chunks/0lc44eilyyvky.js" 4f:"/_next/static/chunks/44eddfb82mqw7.js" 50:"/_next/static/chunks/0rh88mo92_eun.js" 51:"/_next/static/chunks/19bc9syhv3w28.js" 52:"/_next/static/chunks/3inwsphehwqfi.js" 53:"/_next/static/chunks/1nyz-fz1mk3y6.js" 54:"/_next/static/chunks/2ozcrjb_hh74t.js" 55:"/_next/static/chunks/1kjhudvr8aesf.js" 56:"/_next/static/chunks/1ot1rbfa0d_n4.js" 57:"/_next/static/chunks/20k3408cq3fwt.js" 58:"/_next/static/chunks/1_lo_qve3gu86.js" 59:"/_next/static/chunks/3di53f0fz7pw_.js" 5a:"/_next/static/chunks/3m1xjj5kw5fie.js" 5b:"/_next/static/chunks/0oag6lffx7d01.js" 5c:"/_next/static/chunks/082jo-0ajazgr.js" 5d:"/_next/static/chunks/0-a64pg0hn7g7.js" 5e:"/_next/static/chunks/09nq57stwzkgf.js" 5f:"/_next/static/chunks/253gnmj0-cj17.js" 60:"/_next/static/chunks/3k2gyg36fnag_.js" 61:"/_next/static/chunks/0so1i35v7xcta.js" 62:"/_next/static/chunks/0i3-eynrkvqi7.js" 63:"/_next/static/chunks/0o80ztgn9c32o.js" 64:"/_next/static/chunks/2ef57x_ulp7g8.js" 65:"/_next/static/chunks/40mq7ggq-ozo4.js" 66:"/_next/static/chunks/1tn-0fivsxsv1.js" 67:"/_next/static/chunks/0hlb44ca7-4a2.js" 68:"/_next/static/chunks/3w3w0o8onfo6c.js" 69:"/_next/static/chunks/1k6nz21j59212.js" 6a:"/_next/static/chunks/0vq-rot4_1_4v.js" 6b:"/_next/static/chunks/2k8pepwc4pxns.js" 6c:"/_next/static/chunks/3tkuay-4u7wpt.js" 6d:"/_next/static/chunks/18ggtgz2yf759.js" 6e:"/_next/static/chunks/249z4re91ru3g.js" 6f:"/_next/static/chunks/20329i6m_04t6.js" 70:I[593304,["$2d","$2e","$2f","$30","$31","$32","$46","$47","$48","$49","$4a","$4b","$4c","$4d","$4e","$4f","$50","$51","$52","$53","$54","$55","$56","$57","$58","$59","$5a","$5b","$5c","$5d","$5e","$5f","$60","$61","$62","$63","$64","$65","$66","$67","$68","$69","$6a","$6b","$6c","$6d","$6e","$6f"],"OwnedHydration"] 71:T4fb,// Hierarchical key examples const productKey = "catalog:product:12345:details:en-US"; const userKey = "auth:user:67890:profile"; const searchKey = "search:results:electronics:page:1:size:20"; const cartKey = "commerce:cart:user:12345:items"; // Benefits: // 1. Visual hierarchy aids debugging // 2. Pattern matching for bulk invalidation: "catalog:product:12345:*" // 3. Clear ownership/namespace boundaries // 4. Self-documenting structure class CacheKeyBuilder { private parts: string[] = []; private readonly separator = ":"; constructor(private namespace: string) { this.parts.push(namespace); } entity(type: string, id: string | number): this { this.parts.push(type, String(id)); return this; } aspect(name: string): this { this.parts.push(name); return this; } variation(key: string, value: string): this { this.parts.push(`${key}=${value}`); return this; } build(): string { return this.parts.join(this.separator); } } // Usage const key = new CacheKeyBuilder("catalog") .entity("product", 12345) .aspect("details") .variation("locale", "en-US") .build(); // Result: "catalog:product:12345:details:locale=en-US"72:T775,import crypto from 'crypto'; interface QueryCacheParams { sql: string; params: unknown[]; userId?: string; permissions?: string[]; } class QueryCacheKey { private readonly prefix: string; constructor(prefix: string) { this.prefix = prefix; } /** * Generates a deterministic hash-based cache key. * Uses SHA-256 for collision resistance. */ generate(params: QueryCacheParams): string { // Canonicalize the input for deterministic hashing const canonical = this.canonicalize(params); // Generate hash const hash = crypto .createHash('sha256') .update(canonical) .digest('hex') .substring(0, 32); // Use first 32 chars (128 bits) return `${this.prefix}:${hash}`; } /** * Canonicalizes input to ensure deterministic hash generation. * Critical: Object key ordering must be stable! */ private canonicalize(params: QueryCacheParams): string { // Sort object keys for deterministic serialization return JSON.stringify(params, Object.keys(params).sort()); } /** * For debugging: returns both the key and a human-readable version. */ generateWithMetadata(params: QueryCacheParams): { key: string; debugInfo: string; } { const key = this.generate(params); return { key, debugInfo: `SQL: ${params.sql.substring(0, 100)}...`, }; } } // Usage const keyGenerator = new QueryCacheKey("db:query"); const params: QueryCacheParams = { sql: "SELECT * FROM products WHERE category = ? AND price < ?", params: ["electronics", 500], userId: "user-123", permissions: ["read:products", "read:prices"], }; const key = keyGenerator.generate(params); // Result: "db:query:a7f3b2c1d4e5f6789..."73:T934,import crypto from 'crypto'; interface APIRequest { endpoint: string; method: string; userId?: string; queryParams: Record; body?: unknown; } class APICacheKey { /** * Generates a composite key with readable prefix and hashed suffix. * * Structure: {service}:{entity}:{id}:{hash-of-request-variations} */ static generate(request: APIRequest): string { // Extract hierarchical components const pathParts = request.endpoint.split('/').filter(Boolean); const service = pathParts[0] || 'api'; const entity = pathParts[1] || 'unknown'; const id = pathParts[2] || 'list'; // Generate hash for variable parts const variableHash = this.hashVariableParts({ method: request.method, userId: request.userId, queryParams: request.queryParams, body: request.body, }); return `${service}:${entity}:${id}:${variableHash}`; } private static hashVariableParts(parts: Record): string { // Remove undefined values and sort keys for determinism const cleaned = Object.fromEntries( Object.entries(parts) .filter(([_, v]) => v !== undefined) .sort(([a], [b]) => a.localeCompare(b)) ); return crypto .createHash('sha256') .update(JSON.stringify(cleaned)) .digest('hex') .substring(0, 16); // 64 bits sufficient for typical use } /** * Parse a composite key back into components for debugging. */ static parse(key: string): { service: string; entity: string; id: string; variationHash: string; } { const [service, entity, id, variationHash] = key.split(':'); return { service, entity, id, variationHash }; } } // Usage const key = APICacheKey.generate({ endpoint: '/products/electronics/12345', method: 'GET', userId: 'user-456', queryParams: { locale: 'en-US', currency: 'USD' }, }); // Result: "products:electronics:12345:a7f3b2c1de8f9012" // Debugging const parsed = APICacheKey.parse(key); console.log(parsed); // { service: 'products', entity: 'electronics', id: '12345', variationHash: 'a7f3b2c1de8f9012' }74:Ta90,/** * Production-grade namespace management for cache keys. */ interface NamespaceConfig { environment: string; service: string; schemaVersion?: number; } class CacheNamespace { private readonly prefix: string; constructor(config: NamespaceConfig) { const parts = [ config.environment, config.service, ]; if (config.schemaVersion) { parts.push(`v${config.schemaVersion}`); } this.prefix = parts.join(':'); } /** * Creates a fully-qualified cache key within this namespace. */ key(...parts: (string | number)[]): string { return [this.prefix, ...parts.map(String)].join(':'); } /** * Returns a pattern for matching all keys in this namespace. * Useful for cache invalidation. */ pattern(): string { return `${this.prefix}:*`; } /** * Creates a sub-namespace for a specific entity type. */ entity(entityType: string): EntityNamespace { return new EntityNamespace(this.prefix, entityType); } } class EntityNamespace { private readonly prefix: string; constructor(parentPrefix: string, entityType: string) { this.prefix = `${parentPrefix}:${entityType}`; } /** * Key for a specific entity by ID. */ byId(id: string | number): string { return `${this.prefix}:${id}`; } /** * Key for an entity with additional aspects. */ byIdWithAspect(id: string | number, aspect: string): string { return `${this.prefix}:${id}:${aspect}`; } /** * Pattern for all entities of this type. */ pattern(): string { return `${this.prefix}:*`; } /** * Pattern for a specific entity (all aspects). */ patternForId(id: string | number): string { return `${this.prefix}:${id}:*`; } } // Production usage const config: NamespaceConfig = { environment: process.env.NODE_ENV === 'production' ? 'prod' : 'dev', service: 'user-service', schemaVersion: 2, }; const cache = new CacheNamespace(config); const users = cache.entity('user'); // Generate keys const userKey = users.byId(12345); // "prod:user-service:v2:user:12345" const profileKey = users.byIdWithAspect(12345, 'profile'); // "prod:user-service:v2:user:12345:profile" const preferencesKey = users.byIdWithAspect(12345, 'preferences'); // "prod:user-service:v2:user:12345:preferences" // Invalidation patterns const allUsers = users.pattern(); // "prod:user-service:v2:user:*" const userMike = users.patternForId(12345); // "prod:user-service:v2:user:12345:*"75:Tdb4,/** * Collision-resistant cache key generation. */ interface CacheKeyConfig { // All parameters that affect cached value params: Record; // Type tag to prevent cross-entity collisions entityType: string; // Version to handle schema changes version?: number; } class CollisionResistantKey { /** * Generates a collision-resistant key with multiple safeguards. */ static generate(config: CacheKeyConfig): string { // 1. Canonicalize parameters const canonicalParams = this.canonicalize(config.params); // 2. Include type tag to prevent cross-entity collisions const payload = { _type: config.entityType, _version: config.version ?? 1, ...canonicalParams, }; // 3. Use strong hash (SHA-256) const hash = this.strongHash(JSON.stringify(payload)); // 4. Include type in key for debuggability return `${config.entityType}:v${config.version ?? 1}:${hash}`; } /** * Canonicalizes object for deterministic serialization. * Handles nested objects, arrays, and various types. */ private static canonicalize(obj: Record): Record { if (obj === null || typeof obj !== 'object') { return obj; } if (Array.isArray(obj)) { return obj.map(item => typeof item === 'object' ? this.canonicalize(item as Record) : item ) as unknown as Record; } // Sort keys and recursively canonicalize const sortedKeys = Object.keys(obj).sort(); const result: Record = {}; for (const key of sortedKeys) { const value = obj[key]; // Normalize types if (value === undefined) { continue; // Skip undefined } if (typeof value === 'object' && value !== null) { result[key] = this.canonicalize(value as Record); } else { // Convert to string to handle number/string type issues result[key] = String(value); } } return result; } private static strongHash(input: string): string { const crypto = require('crypto'); return crypto .createHash('sha256') .update(input, 'utf8') .digest('hex') .substring(0, 32); } } // Demonstrate collision prevention // These would collide with naive approaches but don't with our solution const key1 = CollisionResistantKey.generate({ entityType: 'product', params: { id: 123, category: 'electronics' }, }); const key2 = CollisionResistantKey.generate({ entityType: 'product', params: { category: 'electronics', id: 123 }, // Different order }); const key3 = CollisionResistantKey.generate({ entityType: 'product', params: { id: '123', category: 'electronics' }, // String vs number }); console.log(key1 === key2); // true - order doesn't matter console.log(key1 === key3); // true - type coercion handled // Different entity type prevents collision const key4 = CollisionResistantKey.generate({ entityType: 'order', params: { id: 123, category: 'electronics' }, }); console.log(key1 === key4); // false - different entity types76:T653,/** * Memory impact analysis for cache key length. */ interface KeyLengthAnalysis { avgKeyLength: number; keyCount: number; redisOverheadPerKey: number; // Redis metadata overhead } function analyzeMemoryImpact(analysis: KeyLengthAnalysis): { keyMemory: number; totalMemory: number; memoryPerMillionKeys: number; } { const keyMemory = analysis.avgKeyLength * analysis.keyCount; const overheadMemory = analysis.redisOverheadPerKey * analysis.keyCount; const totalMemory = keyMemory + overheadMemory; return { keyMemory, totalMemory, memoryPerMillionKeys: totalMemory / (analysis.keyCount / 1_000_000), }; } // Scenario 1: Short keys const shortKeys = analyzeMemoryImpact({ avgKeyLength: 50, // "prod:user:12345:profile" keyCount: 10_000_000, redisOverheadPerKey: 70, // Redis internal overhead }); // Scenario 2: Long keys const longKeys = analyzeMemoryImpact({ avgKeyLength: 300, // Full URL + params + hash keyCount: 10_000_000, redisOverheadPerKey: 70, }); console.log("Short keys:", { keyMemory: `${(shortKeys.keyMemory / 1e9).toFixed(2)} GB`, totalMemory: `${(shortKeys.totalMemory / 1e9).toFixed(2)} GB`, }); // keyMemory: 0.50 GB, totalMemory: 1.20 GB console.log("Long keys:", { keyMemory: `${(longKeys.keyMemory / 1e9).toFixed(2)} GB`, totalMemory: `${(longKeys.totalMemory / 1e9).toFixed(2)} GB`, }); // keyMemory: 3.00 GB, totalMemory: 3.70 GB // Impact: 250 extra bytes per key = 2.5GB additional memory // At $0.10/GB/hour in cloud, that's $2,190/year just for key overhead77:T7fe,/** * Key compression utilities for high-volume caches. */ class KeyCompressor { // Abbreviation mapping (maintain in shared configuration) private static readonly abbreviations: Record = { 'product': 'p', 'category': 'c', 'user': 'u', 'session': 's', 'order': 'o', 'profile': 'pf', 'preferences': 'pr', }; /** * Base62 encoding for numeric IDs. * Reduces "12345678" (8 chars) to "3gBa2" (5 chars). */ static encodeId(id: number): string { const chars = '0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz'; let result = ''; let n = id; while (n > 0) { result = chars[n % 62] + result; n = Math.floor(n / 62); } return result || '0'; } static decodeId(encoded: string): number { const chars = '0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz'; let result = 0; for (const char of encoded) { result = result * 62 + chars.indexOf(char); } return result; } /** * Compresses a key using abbreviations and ID encoding. */ static compress(parts: { type: string; id?: number; aspects?: string[] }): string { const typeAbbrev = this.abbreviations[parts.type] || parts.type.charAt(0); const idEncoded = parts.id ? this.encodeId(parts.id) : ''; const aspectsAbbrev = parts.aspects?.map( a => this.abbreviations[a] || a.charAt(0) ).join('') || ''; return [typeAbbrev, idEncoded, aspectsAbbrev].filter(Boolean).join(''); } } // Examples const longKey = "product:12345678:profile:preferences"; // 35 characters const shortKey = KeyCompressor.compress({ type: 'product', id: 12345678, aspects: ['profile', 'preferences'], }); // Result: "p3gBa2pfpr" - 10 characters (71% reduction) // For 10M keys, that's ~250MB saved just on key strings78:T51f,/** * Schema-based cache versioning. * Version increments when data structure changes. */ interface UserCacheV1 { id: number; name: string; email: string; } interface UserCacheV2 { id: number; name: string; email: string; phoneNumber?: string; // New field in v2 createdAt: Date; // New field in v2 } class UserCacheManager { // Increment this when UserCache structure changes private static readonly SCHEMA_VERSION = 2; private static keyFor(userId: number): string { return `user:v${this.SCHEMA_VERSION}:${userId}:profile`; } async getUser(userId: number): Promise { const key = UserCacheManager.keyFor(userId); const cached = await this.cache.get(key); if (cached) { return JSON.parse(cached) as UserCacheV2; } // Cache miss - fetch and cache const user = await this.fetchUserFromDB(userId); await this.cache.set(key, JSON.stringify(user), 3600); return user; } } // When SCHEMA_VERSION changes: // - Old keys (user:v1:*) are orphaned (natural expiration) // - New keys (user:v2:*) are populated with correct schema // - No explicit cache flush required // - Gradual migration as old entries expire79:T5ac,/** * Deployment-based cache versioning. * Cache automatically refreshes on each deployment. */ class DeployVersionedCache { // Injected from build/deployment process private readonly deployVersion: string; constructor() { // Build process sets this environment variable this.deployVersion = process.env.DEPLOY_VERSION || process.env.GIT_COMMIT?.substring(0, 8) || 'dev'; } /** * Creates a key with built-in deployment version. */ key(...parts: string[]): string { return [`d:${this.deployVersion}`, ...parts].join(':'); } /** * For data that should persist across deploys. */ persistentKey(...parts: string[]): string { return ['persist', ...parts].join(':'); } } // Usage const cache = new DeployVersionedCache(); // This key changes every deployment const sessionKey = cache.key('user', '12345', 'session'); // "d:a1b2c3d4:user:12345:session" // This key persists across deployments const prefsKey = cache.persistentKey('user', '12345', 'preferences'); // "persist:user:12345:preferences" // Benefits: // 1. Code changes immediately reflect (no stale computed values) // 2. Zero-effort cache invalidation on deploy // 3. Blue-green deployments work naturally // Drawbacks: // 1. Cache cold-starts after every deploy // 2. Increased database load during cache warming // 3. May not be necessary for stable data7a:T702,/** * Content-hash based versioning for computed/derived data. */ class ContentHashedCache { /** * For computed results that depend on source config. */ async getCachedComputation( computationId: string, sourceDataHash: string, computeFn: () => Promise ): Promise { // Key includes hash of source data const key = `compute:${computationId}:src:${sourceDataHash}`; const cached = await this.cache.get(key); if (cached) { return JSON.parse(cached); } // Compute and cache with very long TTL (content-addressed) const result = await computeFn(); await this.cache.set(key, JSON.stringify(result), 86400 * 30); // 30 days return result; } } // Example: Caching compiled configuration class ConfigCache extends ContentHashedCache { async getCompiledConfig(rawConfig: object): Promise { // Hash the raw config const configHash = this.hashObject(rawConfig); return this.getCachedComputation( 'compiled-config', configHash, async () => this.compileConfig(rawConfig) ) as Promise; } private hashObject(obj: object): string { const crypto = require('crypto'); return crypto .createHash('sha256') .update(JSON.stringify(obj)) .digest('hex') .substring(0, 16); } } // Benefits: // 1. Cache entries never go stale (content-addressed) // 2. Long TTLs reduce cache churn // 3. Same input always hits cache, even across deploys // Use cases: // - Compiled templates // - Processed images // - Computed analytics // - Transformed data7b:Ta61,/** * Security-conscious cache key generation. */ class SecureCacheKey { /** * INSECURE: PII exposed in key */ static insecureUserKey(email: string): string { // DON'T DO THIS - email visible in logs/monitoring return `user:email:${email}:profile`; } /** * SECURE: Use opaque identifiers */ static secureUserKey(userId: string): string { // User ID is opaque, doesn't reveal PII return `user:${userId}:profile`; } /** * Include authorization context to prevent cross-user access. */ static authorizedDataKey( userId: string, resourceId: string, permissionLevel: string ): string { // Different permission levels get different cache entries return `data:${resourceId}:auth:${userId}:${permissionLevel}`; } /** * Sanitize user input to prevent cache key injection. */ static sanitizedKey(userInput: string): string { // Remove or encode dangerous characters const sanitized = userInput .replace(/[:\/\*\?]/g, '_') // Remove control chars .substring(0, 100); // Limit length return sanitized; } /** * Generate unpredictable keys for sensitive data. */ static unpredictableKey( userId: string, resourceType: string, resourceId: string ): string { const crypto = require('crypto'); // Include a secret to prevent key prediction const secret = process.env.CACHE_KEY_SECRET!; const hmac = crypto .createHmac('sha256', secret) .update(`${userId}:${resourceType}:${resourceId}`) .digest('hex') .substring(0, 16); return `${resourceType}:${resourceId}:${hmac}`; } } // Example: Multi-tenant cache isolation class TenantIsolatedCache { constructor(private readonly tenantId: string) {} /** * All keys automatically scoped to tenant. * Even if tenant A guesses tenant B's user ID, * they can't access the cache entry. */ key(...parts: string[]): string { return ['tenant', this.tenantId, ...parts].join(':'); } } // Usage const tenantACache = new 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Learn cache key design, size management, eviction policies, distributed vs local caching, and cache warming strategies that power high-performance applications.","difficulty":"INTERMEDIATE","estimatedMinutes":90,"pages":[{"id":"seed_41eac1b57178a0b30da4808fcfa82752","title":"Cache Key Design","order":0,"content":[{"id":"opening-hook","title":"The Foundation of Every Cache Lookup","content":[{"data":{"content":"Every cache operation—whether a read, write, or invalidation—begins with a single question: **What is the key?**\n\nThe cache key is the identifier that maps your request to the stored data. It might seem trivially simple: just use the user ID, or the URL, or some combination of parameters. But this apparent simplicity conceals profound complexity. A poorly designed key scheme can lead to cache pollution, stale data nightmares, memory exhaustion, security vulnerabilities, and performance pathologies that only manifest at scale.\n\nPrincipal engineers at companies like Netflix, Google, and Meta spend considerable effort designing cache key schemes. They understand that the key isn't just an identifier—it's the **contract** between your application and your caching layer. Get it right, and caching becomes invisible infrastructure that simply works. Get it wrong, and you'll spend countless hours debugging mysterious cache misses, inconsistencies, and performance cliffs."},"type":"text"},{"data":{"icon":"Target","title":"What You Will Learn","content":"By the end of this page, you will understand how to design cache keys that are precise, efficient, and maintainable. You'll learn composition strategies, namespace conventions, collision prevention, versioning techniques, and security considerations that separate amateur caching from production-grade caching infrastructure.","variant":"info"},"type":"callout"}]},{"id":"effective-cache-keys","title":"What Makes a Cache Key Effective","content":[{"data":{"content":"An effective cache key satisfies several critical properties simultaneously. Understanding these properties is essential before diving into specific design techniques.\n\n**The Five Properties of an Effective Cache Key:**"},"type":"text"},{"data":{"items":["**Uniqueness** — The key must uniquely identify the cached data. Two different pieces of data must never share the same key, or cache corruption occurs.","**Determinism** — Given the same inputs, the key generation must always produce the same key. Non-deterministic keys lead to cache misses for data that's already cached.","**Completeness** — The key must incorporate all factors that affect the cached value. If user preferences affect output, those preferences must be part of the key.","**Minimality** — The key should include only the factors that affect the cached value—nothing more. Overspecification reduces cache hit rates.","**Efficiency** — Key generation and comparison should be fast. Complex key computation can negate caching benefits."],"title":{"icon":"Target","text":"Essential Cache Key Properties","type":"icon","color":"primary","variant":"outline-circle"},"variant":"accent"},"type":"list"},{"data":{"content":"**The Uniqueness-Minimality Tension:**\n\nThe most common design tension in cache keys is between uniqueness and minimality. Overly unique keys (including too many parameters) fragment the cache, reducing hit rates. Insufficiently unique keys cause cache pollution, where one user's data corrupts another's view.\n\nConsider caching API responses for a product catalog:"},"type":"text"},{"data":{"left":[{"data":{"items":["`product:123:user:456:session:789:timestamp:1234567890`","Includes user ID, session, and timestamp","Every request generates a new cache entry","Effectively disables caching entirely","Cache hit rate: ~0%"],"title":{"icon":"XCircle","text":"Over-Specified Key","type":"icon","color":"destructive","variant":"outline-circle"},"variant":"accent"},"type":"list"}],"right":[{"data":{"items":["`product:123:locale:en-US:currency:USD`","Includes only factors affecting product display","Same product/locale/currency shares cache entry","Maximizes cache hit rate while maintaining correctness","Cache hit rate: 85%+ typical"],"title":{"icon":"CheckCircle","text":"Appropriately-Specified Key","type":"icon","color":"primary","variant":"outline-circle"},"variant":"accent"},"type":"list"}]},"type":"two-column"},{"data":{"icon":"AlertCircle","title":"The Cost of Getting Keys Wrong","content":"Over-specified keys waste memory and compute by storing redundant copies. Under-specified keys serve incorrect data to users. Both failures can be subtle—you won't see exceptions, just degraded performance or confused users. Always validate your key scheme against real access patterns.","variant":"warning"},"type":"callout"}],"titleType":"number","titleNumber":1},{"id":"key-composition-strategies","title":"Key Composition Strategies","content":[{"data":{"content":"Cache key composition is the process of constructing keys from component parts. A well-designed composition strategy makes keys predictable, debuggable, and maintainable.\n\n**The Three Key Composition Approaches:**"},"type":"text"},{"data":{"tabs":[{"id":"hierarchical","badge":"Recommended","label":"Hierarchical Keys","content":[{"data":{"content":"**Hierarchical keys** structure components from general to specific, using a delimiter (typically `:` or `/`). This approach mirrors how we think about data relationships and enables pattern-based operations.\n\n**Pattern:** `{service}:{entity}:{id}:{aspect}:{variation}`\n\n**Examples:**"},"type":"text"},{"data":{"code":"$71","fileName":"hierarchical-keys.ts","showLineNumbers":true},"type":"code"},{"data":{"icon":"Lightbulb","title":"Hierarchical Key Best Practices","content":"Start with the most stable component (service name) and progress to the most variable (specific variations). This enables efficient pattern-based operations like wildcard deletion in Redis: `DEL catalog:product:12345:*`","variant":"tip"},"type":"callout"}],"titleIcon":"Target"},{"id":"hash-based","badge":"For Complex Inputs","label":"Hash-Based Keys","content":[{"data":{"content":"**Hash-based keys** generate a fixed-length hash from input parameters. This approach handles complex inputs (like full request bodies or SQL queries) that would create unwieldy literal keys.\n\n**Pattern:** `{prefix}:{hash-of-parameters}`\n\n**When to Use:**\n- Input parameters are large or variable-length\n- Exact structure of inputs is complex (nested objects)\n- Key length limits are a concern\n- Human readability is secondary to efficiency"},"type":"text"},{"data":{"code":"$72","fileName":"hash-based-keys.ts","showLineNumbers":true},"type":"code"},{"data":{"icon":"AlertCircle","title":"Hash Key Pitfalls","content":"Hash-based keys sacrifice debuggability. When investigating cache issues, you can't tell what a key like `db:query:a7f3b2c1...` represents. Always maintain a way to reconstruct the debug info, and consider storing metadata alongside cached values.","variant":"warning"},"type":"callout"}],"titleIcon":"Code2"},{"id":"composite","badge":"Hybrid Approach","label":"Composite Keys","content":[{"data":{"content":"**Composite keys** combine hierarchical prefixes with hashed suffixes. This provides the best of both worlds: human-readable prefixes for routing and debugging, with hash-based suffixes for complex parameters.\n\n**Pattern:** `{hierarchical-prefix}:{hash-of-variable-parts}`\n\n**This is often the production-optimal approach for APIs.**"},"type":"text"},{"data":{"code":"$73","fileName":"composite-keys.ts","showLineNumbers":true},"type":"code"},{"data":{"icon":"CheckCircle","title":"Production Recommendation","content":"Composite keys are the recommended approach for most production systems. They enable efficient pattern-based invalidation (by prefix), maintain debuggability, and handle arbitrary request complexity through hashing.","variant":"success"},"type":"callout"}],"titleIcon":"Zap"}]},"type":"tabs"}],"titleType":"number","titleNumber":2},{"id":"namespace-conventions","title":"Namespace and Prefix Conventions","content":[{"data":{"content":"Namespacing is the practice of organizing cache keys into logical groups. Proper namespacing prevents collisions between different parts of your system and enables targeted cache management.\n\n**Why Namespacing Matters:**\n\nIn a typical production system, multiple services share the same cache infrastructure. Without namespacing:\n- Service A's `user:123` collides with Service B's `user:123`\n- There's no way to flush one service's cache without affecting others\n- Debugging becomes impossible—you can't tell who owns a key\n- Metrics are meaningless without per-service breakdown"},"type":"text"},{"data":{"rows":[["Environment","Separate dev/staging/prod","`prod:`, `staging:`","Multi-environment shared cache"],["Service","Isolate microservices","`user-service:`, `catalog:`","Always in microservices"],["Domain","Group related entities","`auth:`, `commerce:`","Large monoliths or domains"],["Entity","Identify data type","`user:`, `product:`","Always"],["Version","Handle schema changes","`v2:`, `schema:3:`","During migrations"]],"caption":"Namespace Hierarchy Levels","headers":["Level","Purpose","Example","When to Use"]},"type":"table"},{"data":{"code":"$74","fileName":"namespace-conventions.ts","showLineNumbers":true},"type":"code"},{"data":{"icon":"Lightbulb","title":"Namespace Design Guidelines","content":"1. **Be explicit** — Use full service names, not abbreviations (\"user-service\" not \"us\")\n2. **Be consistent** — Establish conventions and enforce them through shared libraries\n3. **Document patterns** — Maintain a key pattern registry for debugging\n4. **Monitor by namespace** — Track hit rates, memory usage per namespace","variant":"tip"},"type":"callout"}],"titleType":"number","titleNumber":3},{"id":"key-collisions","title":"Handling Key Collisions","content":[{"data":{"content":"Key collisions occur when two different inputs produce the same cache key. This leads to cache corruption where one piece of data is returned for an unrelated request. Understanding and preventing collisions is critical for cache correctness.\n\n**Types of Key Collisions:**"},"type":"text"},{"data":{"items":["**Hash Collisions** — Two different inputs hash to the same value. Rare with cryptographic hashes but possible with weak hash functions.","**Missing Parameters** — Key generation ignores a parameter that affects the cached value (e.g., forgetting to include user locale).","**Canonical Ordering Issues** — Same parameters in different orders generate different keys (e.g., `{a:1, b:2}` vs `{b:2, a:1}`).","**Type Coercion Problems** — `user:123` (number) collides with `user:123` (string) if not handled consistently.","**Namespace Leakage** — Incomplete namespace prefixes allow cross-service collisions."],"title":{"icon":"AlertCircle","text":"Collision Sources","type":"icon","color":"destructive","variant":"outline-circle"},"variant":"glass"},"type":"list"},{"data":{"content":"**Collision Prevention Strategies:**"},"type":"text"},{"data":{"code":"$75","fileName":"collision-prevention.ts","showLineNumbers":true},"type":"code"},{"data":{"icon":"AlertCircle","title":"Real-World Collision Disasters","content":"In 2020, a major e-commerce platform accidentally served personalized pricing from one user to another due to a cache key collision. The key didn't include currency conversion parameters. A user in Europe saw US prices cached for an American user. This led to pricing disputes, refunds, and regulatory scrutiny. Always audit keys for completeness.","variant":"error"},"type":"callout"}],"titleType":"number","titleNumber":4},{"id":"key-length-performance","title":"Key Length and Performance Considerations","content":[{"data":{"content":"Cache key length directly impacts memory consumption and lookup performance. While modern caches handle long keys efficiently, understanding the tradeoffs helps optimize high-throughput systems.\n\n**Why Key Length Matters:**"},"type":"text"},{"data":{"rows":[["Memory per key","Lower baseline","Significant overhead at scale"],["Network transfer","Negligible","Adds latency on every operation"],["Hash computation","Faster","Milliseconds for very long keys"],["Debuggability","May be too terse","May be unwieldy in logs"],["Index efficiency","Better tree/hash performance","Degraded in some databases"]],"caption":"Key Length Impact Analysis","headers":["Factor","Short Keys (< 100 chars)","Long Keys (> 500 chars)"]},"type":"table"},{"data":{"content":"**Calculating Memory Impact:**\n\nConsider a Redis cache with 10 million keys:"},"type":"text"},{"data":{"code":"$76","fileName":"key-length-analysis.ts","showLineNumbers":true},"type":"code"},{"data":{"content":"**Key Length Optimization Strategies:**"},"type":"text"},{"data":{"items":["**Hash variable components** — Use a hash for long/variable parts while keeping prefixes readable","**Use abbreviations consistently** — Define a mapping: `product` → `p`, `category` → `c`","**Omit obvious delimiters** — `p12345` instead of `product:12345` (if un-ambiguous)","**Compress IDs** — Use base62 encoding for numeric IDs: `12345` → `3D7`","**Remove redundant prefixes** — If using separate Redis databases, skip environment prefix"],"variant":"accent"},"type":"list"},{"data":{"code":"$77","fileName":"key-compression.ts","showLineNumbers":true},"type":"code"},{"data":{"icon":"Info","title":"When to Optimize Key Length","content":"Key length optimization is a micro-optimization. Prioritize correctness and debuggability first. Only compress keys when profiling shows memory pressure from key storage, or when network bandwidth is constrained. At fewer than 1 million keys, the savings rarely justify the complexity.","variant":"note"},"type":"callout"}],"titleType":"number","titleNumber":5},{"id":"versioning-strategies","title":"Versioning Strategies in Keys","content":[{"data":{"content":"Cache key versioning is essential for managing schema changes, code deployments, and data migrations. When the structure of cached data changes, old cached values become invalid—but the cache doesn't know that. Versioning solves this problem.\n\n**Why Version Cache Keys:**"},"type":"text"},{"data":{"items":["**Schema changes** — Adding or removing fields from cached objects","**Serialization changes** — Switching from JSON to MessagePack or Protocol Buffers","**Business logic changes** — Computed values that now calculate differently","**Blue-green deployments** — Old and new code versions running simultaneously","**A/B testing** — Different cached representations for different experiments","**Hotfix deployments** — Forcing cache refresh for bug fixes"],"title":{"icon":"Zap","text":"Versioning Use Cases","type":"icon","color":"primary","variant":"outline-circle"},"variant":"accent"},"type":"list"},{"data":{"content":"**Three Versioning Approaches:**"},"type":"text"},{"data":{"tabs":[{"id":"schema-version","badge":"Planned Changes","label":"Schema Version","content":[{"data":{"content":"**Schema versioning** includes an explicit version number in the key that changes when the data structure changes. This is ideal for planned, deliberate migrations."},"type":"text"},{"data":{"code":"$78","fileName":"schema-versioning.ts","showLineNumbers":true},"type":"code"},{"data":{"icon":"Lightbulb","title":"Schema Version Best Practices","content":"Store the schema version in configuration, not code. This allows emergency version bumps without code deployments. Also consider maintaining a CHANGELOG for cache schema versions to help debugging.","variant":"tip"},"type":"callout"}],"titleIcon":"Target"},{"id":"deploy-version","badge":"CD Integration","label":"Deploy Version","content":[{"data":{"content":"**Deploy versioning** uses the application deployment version (commit hash, build number, or release tag) in the key. This automatically invalidates cache on every deployment."},"type":"text"},{"data":{"code":"$79","fileName":"deploy-versioning.ts","showLineNumbers":true},"type":"code"},{"data":{"icon":"AlertCircle","title":"Deploy Versioning Trade-offs","content":"Deploy versioning causes complete cache invalidation on every release. For high-traffic systems, this creates a \"thundering herd\" of database requests post-deploy. Use selectively, or combine with cache warming strategies.","variant":"warning"},"type":"callout"}],"titleIcon":"Zap"},{"id":"content-hash","badge":"Immutable Data","label":"Content Hash","content":[{"data":{"content":"**Content hashing** includes a hash of the source data in the key. This enables infinite caching of immutable data while automatically invalidating when source changes."},"type":"text"},{"data":{"code":"$7a","fileName":"content-hash-versioning.ts","showLineNumbers":true},"type":"code"},{"data":{"icon":"CheckCircle","title":"Content-Addressed Caching","content":"Content-hash versioning enables aggressive, long-lived caching. If the source doesn't change, the cached result is guaranteed correct. This is the same principle behind CDN asset caching with content hashes in filenames.","variant":"success"},"type":"callout"}],"titleIcon":"Code2"}]},"type":"tabs"}],"titleType":"number","titleNumber":6},{"id":"security-considerations","title":"Security Considerations for Cache Keys","content":[{"data":{"content":"Cache key design has significant security implications. Poorly designed keys can leak sensitive information, enable cache poisoning attacks, or allow unauthorized access to cached data.\n\n**Security Risks in Cache Keys:**"},"type":"text"},{"data":{"items":["**PII in keys** — Including emails, SSNs, or names in keys exposes them in logs and monitoring","**Predictable keys** — Sequential or easily-guessed keys enable enumeration attacks","**Missing authorization** — Keys that don't encode access level allow privilege escalation","**Shared keys** — Same key for different users enables data leakage","**Injection vulnerabilities** — User input directly in keys enables cache poisoning"],"title":{"icon":"AlertCircle","text":"Security Anti-Patterns","type":"icon","color":"destructive","variant":"outline-circle"},"variant":"glass"},"type":"list"},{"data":{"code":"$7b","fileName":"secure-cache-keys.ts","showLineNumbers":true},"type":"code"},{"data":{"icon":"AlertCircle","title":"Cache Key Security Checklist","content":"Before deploying cache keys to production, verify:\n1. No PII appears in keys (check logs to confirm)\n2. Keys include tenant/user context where needed\n3. User input is sanitized before inclusion\n4. Sensitive data uses unpredictable key components\n5. Cache expiration limits exposure window","variant":"error"},"type":"callout"},{"data":{"icon":"AlertCircle","title":"Cache Poisoning Prevention","content":"If an attacker can control any part of a cache key, they may perform cache poisoning: storing malicious data under a predictable key. Always validate and sanitize any user-controlled input that becomes part of a cache key. Treat cache key construction with the same rigor as SQL query construction.","variant":"warning"},"type":"callout"}],"titleType":"number","titleNumber":7},{"id":"summary","title":"Summary: Cache Key Design Principles","content":[{"data":{"content":"Cache key design is foundational to building effective caching systems. Let's consolidate the essential principles:"},"type":"text"},{"data":{"type":"ordered","items":["**Effective keys balance uniqueness and minimality** — Include all factors that affect cached value, but nothing more.","**Composition strategies matter** — Hierarchical keys aid debugging, hash-based keys handle complexity, composite keys combine benefits.","**Namespacing prevents collisions** — Service/entity/version prefixes isolate cache spaces and enable targeted invalidation.","**Collision prevention requires discipline** — Canonicalize inputs, include type tags, use strong hashes, validate key uniqueness.","**Key length impacts performance** — Optimize only when profiling shows memory or network pressure from key overhead.","**Versioning enables safe migrations** — Schema version, deploy version, or content hash depending on use case.","**Security is non-negotiable** — No PII in keys, sanitize input, include authorization context, prevent enumeration."],"title":{"icon":"CheckCircle","text":"Key Takeaways","type":"icon","color":"primary","variant":"outline-circle"},"variant":"accent"},"type":"list"},{"data":{"content":"**What's Next:**\n\nWith cache key design mastered, we'll explore **cache size and eviction policies** in the next page. You'll learn how to determine appropriate cache sizes, implement LRU/LFU/FIFO eviction, handle memory pressure gracefully, and tune eviction parameters for different workload patterns."},"type":"text"},{"data":{"icon":"CheckCircle","title":"Page Complete","content":"You now understand the principles and techniques for designing effective cache keys. This foundational skill enables you to build caching systems that are correct, performant, maintainable, and secure. 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