epic-caching

Development

Guide on caching with cachified, SQLite cache, and LRU cache for Epic Stack

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Epic Stack: Caching

When to use this skill

Use this skill when you need to:

Cache results of expensive queries
Cache responses from external APIs
Optimize performance of data that doesn't change frequently
Implement stale-while-revalidate
Manage cache invalidation
Integrate cache with server timing

Patterns and conventions

Caching Philosophy

Following Epic Web principles:

Weigh the cost-benefit of performance optimizations - Caching adds complexity. Only add cache when there's a clear, measurable benefit. Don't cache "just in case" - cache when you have a real performance problem that caching solves.

When NOT to use cache:

Data that changes frequently (cache invalidation becomes a problem)
Data that's already fast to fetch (no measurable benefit)
Data that's only fetched once (no benefit from caching)
Simple queries that don't need optimization
When cache invalidation logic becomes more complex than the problem it solves

Example - Evaluating cost-benefit:

// ✅ Good - Cache expensive external API call
export async function getGitHubEvents({
	username,
	timings,
}: {
	username: string
	timings?: Timings
}) {
	return await cachified({
		key: `github:${username}:events`,
		cache,
		timings,
		getFreshValue: async () => {
			// Expensive: External API call, rate limits, network latency
			const response = await fetch(
				`https://api.github.com/users/${username}/events/public`,
			)
			return await response.json()
		},
		checkValue: GitHubEventSchema.array(),
		ttl: 1000 * 60 * 60, // 1 hour - reasonable for external data
	})
}

// ❌ Avoid - Caching simple, fast database query
export async function getUser({ userId }: { userId: string }) {
	// This query is already fast - caching adds complexity without benefit
	return await cachified({
		key: `user:${userId}`,
		cache,
		getFreshValue: async () => {
			// Simple query, already fast
			return await prisma.user.findUnique({
				where: { id: userId },
				select: { id: true, username: true },
			})
		},
		ttl: 1000 * 60 * 5,
	})
	// Better: Just query directly without cache
}

Two Types of Cache

Epic Stack provides two types of cache:

SQLite Cache - Long-lived, replicated with LiteFS
- Persistent across restarts
- Replicated across all instances
- Ideal for data that changes infrequently
LRU Cache - Short-lived, in-memory
- Cleared on restart
- Not replicated (only on current instance)
- Ideal for deduplication and temporary cache

Using cachified

Epic Stack uses @epic-web/cachified as an abstraction for cache management.

Basic import:

import { cachified, cache } from '#app/utils/cache.server.ts'
import { type Timings } from '#app/utils/timing.server.ts'

Basic structure:

export async function getCachedData({
	timings,
}: {
	timings?: Timings
} = {}) {
	return await cachified({
		key: 'my-cache-key',
		cache,
		timings,
		getFreshValue: async () => {
			// Get fresh data
			return await fetchDataFromAPI()
		},
		checkValue: z.object({
			/* schema */
		}), // Validation with Zod
		ttl: 1000 * 60 * 60 * 24, // 24 hours
		staleWhileRevalidate: 1000 * 60 * 60 * 24 * 30, // 30 days
	})
}

Cache Keys

Naming conventions:

Use format: entity:identifier:data
Examples:
- user:${userId}:profile
- note:${noteId}:full
- api:github:events
- tito:scheduled-events

Avoid:

Keys that are too long
Keys with special characters
Keys that don't clearly identify the content

TTL (Time To Live)

Define TTL:

await cachified({
	key: 'my-key',
	cache,
	getFreshValue: () => fetchData(),
	ttl: 1000 * 60 * 60 * 24, // 24 hours in milliseconds
})

Null TTL to never expire:

ttl: null, // Never expires (not recommended unless necessary)

Stale-While-Revalidate (SWR)

SWR allows returning stale data while fresh data is fetched in the background.

Example:

await cachified({
	key: 'my-key',
	cache,
	getFreshValue: () => fetchData(),
	ttl: 1000 * 60 * 60 * 24, // 24 hours - after this it's considered stale
	staleWhileRevalidate: 1000 * 60 * 60 * 24 * 30, // 30 days - up to here returns stale while revalidating
})

Behavior:

Less than 24h: Returns cache, no request made
24h - 30 days: Returns stale cache immediately, updates in background
More than 30 days: Waits for fresh data before returning

Validation with Zod

Always validate cached data with Zod:

import { z } from 'zod'

const EventSchema = z.object({
	id: z.string(),
	title: z.string(),
	date: z.string(),
})

export async function getEvents({ timings }: { timings?: Timings } = {}) {
	return await cachified({
		key: 'events:all',
		cache,
		timings,
		getFreshValue: async () => {
			const response = await fetch('https://api.example.com/events')
			return await response.json()
		},
		checkValue: EventSchema.array(), // Validates it's an array of events
		ttl: 1000 * 60 * 60 * 24, // 24 hours
	})
}

If cached data doesn't pass validation, fresh data is fetched.

Server Timing Integration

Integrate cache with server timing for monitoring:

import { type Timings } from '#app/utils/timing.server.ts'

export async function loader({ request }: Route.LoaderArgs) {
	const timings: Timings = {}

	const events = await getEvents({ timings })

	// Timings are automatically added to headers
	return json(
		{ events },
		{
			headers: combineServerTimings(timings),
		},
	)
}

Cache Invalidation

Invalidate by key:

import { cache } from '#app/utils/cache.server.ts'

await cache.delete('user:123:profile')

Invalidate multiple keys:

// Search and delete matching keys
import { searchCacheKeys } from '#app/utils/cache.server.ts'

const keys = await searchCacheKeys('user:123', 100)
await Promise.all(keys.map((key) => cache.delete(key)))

Invalidate entire SQLite cache:

// Use admin dashboard or
await cache.clear() // If available

Using LRU Cache

For temporary data, use LRU cache directly:

import { lru } from '#app/utils/cache.server.ts'

// LRU cache is useful for:
// - Request deduplication
// - Very temporary cache (< 5 minutes)
// - Data that doesn't need to persist

const cachedValue = lru.get('temp-key')
if (!cachedValue) {
	const freshValue = await computeExpensiveValue()
	lru.set('temp-key', freshValue, { ttl: 1000 * 60 * 5 }) // 5 minutes
	return freshValue
}
return cachedValue

Multi-Region Cache

With LiteFS, SQLite cache is automatically replicated:

Behavior:

Only the primary instance writes to cache
Replicas can read from cache
Writes are automatically synchronized

Best practices:

Don't assume all writes are immediate
Use ensurePrimary() if you need to guarantee writes

import { ensurePrimary } from '#app/utils/litefs.server.ts'

export async function action({ request }: Route.ActionArgs) {
	await ensurePrimary() // Ensure we're on primary instance

	// Invalidate cache
	await cache.delete('my-key')

	// ...
}

Error Handling

Handle errors in getFreshValue:

await cachified({
	key: 'my-key',
	cache,
	getFreshValue: async () => {
		try {
			return await fetchData()
		} catch (error) {
			console.error('Failed to fetch fresh data:', error)
			throw error // Re-throw so cachified handles it
		}
	},
	// If getFreshValue fails and there's stale cache, it returns it
	fallbackToCache: true, // Default: true
})

Cache Admin Dashboard

Epic Stack includes a dashboard to manage cache:

Route: /admin/cache

Features:

View all cache keys
Search keys
View details of a key
Delete keys
Clear entire cache

Common examples

Example 1: Cache external API response

// app/utils/api.server.ts
import { cachified, cache } from '#app/utils/cache.server.ts'
import { type Timings } from '#app/utils/timing.server.ts'
import { z } from 'zod'

const GitHubEventSchema = z.object({
	id: z.string(),
	type: z.string(),
	actor: z.object({
		login: z.string(),
	}),
	created_at: z.string(),
})

export async function getGitHubEvents({
	username,
	timings,
}: {
	username: string
	timings?: Timings
}) {
	return await cachified({
		key: `github:${username}:events`,
		cache,
		timings,
		getFreshValue: async () => {
			const response = await fetch(
				`https://api.github.com/users/${username}/events/public`,
			)
			if (!response.ok) {
				throw new Error(`GitHub API error: ${response.statusText}`)
			}
			const data = await response.json()
			return data
		},
		checkValue: GitHubEventSchema.array(),
		ttl: 1000 * 60 * 60, // 1 hour
		staleWhileRevalidate: 1000 * 60 * 60 * 24, // 24 hours
	})
}

Example 2: Cache Prisma query

// app/utils/user.server.ts
import { cachified, cache } from '#app/utils/cache.server.ts'
import { prisma } from '#app/utils/db.server.ts'
import { z } from 'zod'

const UserStatsSchema = z.object({
	totalNotes: z.number(),
	totalLikes: z.number(),
	joinDate: z.string(),
})

export async function getUserStats({
	userId,
	timings,
}: {
	userId: string
	timings?: Timings
}) {
	return await cachified({
		key: `user:${userId}:stats`,
		cache,
		timings,
		getFreshValue: async () => {
			const [totalNotes, totalLikes, user] = await Promise.all([
				prisma.note.count({ where: { ownerId: userId } }),
				prisma.like.count({ where: { userId } }),
				prisma.user.findUnique({
					where: { id: userId },
					select: { createdAt: true },
				}),
			])

			return {
				totalNotes,
				totalLikes,
				joinDate: user?.createdAt.toISOString() ?? '',
			}
		},
		checkValue: UserStatsSchema,
		ttl: 1000 * 60 * 5, // 5 minutes
		staleWhileRevalidate: 1000 * 60 * 60, // 1 hour
	})
}

Example 3: Invalidate cache after mutation

// app/routes/users/$username/notes/new.tsx
export async function action({ request }: Route.ActionArgs) {
	const userId = await requireUserId(request)
	const formData = await request.formData()

	// ... validate and create note

	const note = await prisma.note.create({
		data: {
			title,
			content,
			ownerId: userId,
		},
		include: { owner: true },
	})

	// Invalidate related cache
	await Promise.all([
		cache.delete(`user:${userId}:notes`),
		cache.delete(`user:${userId}:stats`),
		cache.delete(`note:${note.id}:full`),
	])

	return redirect(`/users/${note.owner.username}/notes/${note.id}`)
}

Example 4: Cache with dependencies

export async function getUserWithNotes({
	userId,
	timings,
}: {
	userId: string
	timings?: Timings
}) {
	const user = await cachified({
		key: `user:${userId}:profile`,
		cache,
		timings,
		getFreshValue: async () => {
			return await prisma.user.findUnique({
				where: { id: userId },
				select: {
					id: true,
					username: true,
					name: true,
				},
			})
		},
		checkValue: z
			.object({
				id: z.string(),
				username: z.string(),
				name: z.string().nullable(),
			})
			.nullable(),
		ttl: 1000 * 60 * 30, // 30 minutes
	})

	const notes = await cachified({
		key: `user:${userId}:notes`,
		cache,
		timings,
		getFreshValue: async () => {
			return await prisma.note.findMany({
				where: { ownerId: userId },
				select: {
					id: true,
					title: true,
					updatedAt: true,
				},
				orderBy: { updatedAt: 'desc' },
			})
		},
		checkValue: z.array(
			z.object({
				id: z.string(),
				title: z.string(),
				updatedAt: z.date(),
			}),
		),
		ttl: 1000 * 60 * 10, // 10 minutes
	})

	return { user, notes }
}

Example 5: Use LRU for deduplication

// Avoid multiple simultaneous requests to the same URL
const requestCache = new Map<string, Promise<any>>()

export async function fetchWithDedup(url: string) {
	if (requestCache.has(url)) {
		return requestCache.get(url)
	}

	const promise = fetch(url).then((res) => res.json())
	requestCache.set(url, promise)

	// Clean up after 1 second
	setTimeout(() => {
		requestCache.delete(url)
	}, 1000)

	return promise
}

Common mistakes to avoid

❌ Caching without measuring benefit: Only add cache when there's a clear, measurable performance problem
❌ Caching simple, fast queries: Don't cache data that's already fast to fetch - it adds complexity without benefit
❌ Caching frequently changing data: Cache invalidation becomes more complex than the problem it solves
❌ Caching sensitive data: Never cache passwords, tokens, or sensitive personal data
❌ TTL too long: Avoid very long TTLs (> 1 week) unless absolutely necessary
❌ Not validating cached data: Always use checkValue with Zod to validate data
❌ Forgetting to invalidate cache: Invalidate cache after mutations
❌ Assuming cache always works: Cache can fail, always handle errors
❌ Keys too long or ambiguous: Use consistent and descriptive format
❌ Not using timings: Integrate with server timing for monitoring
❌ Forgetting stale-while-revalidate: Use SWR for better UX when appropriate
❌ Over-caching: Too much caching makes the system harder to understand and debug

References

Epic Stack Caching Docs
Epic Web Principles
@epic-web/cachified
app/utils/cache.server.ts - Cache implementation
app/routes/admin/cache/ - Admin dashboard
app/utils/timing.server.ts - Server timing utilities