Design Patterns
Common patterns and anti-patterns for building scalable actor systems.
How Actors Scale
Actors are inherently scalable because of how they’re designed:
- Isolated state: Each actor manages its own private data. No shared state means no conflicts and no locks, so actors run concurrently without coordination.
- Actor-to-actor communication: Actors interact through actions and events, so they don’t need to coordinate access to shared data. This makes it easy to distribute them across machines.
- Small, focused units: Each actor handles a limited scope (a single user, document, or chat room), so load naturally spreads across many actors rather than concentrating in one place.
- Horizontal scaling: Adding more machines automatically distributes actors across them.
These properties form the foundation for the patterns described below.
Actor Per Entity
The core pattern is creating one actor per entity in your system. Each actor represents a single user, document, chat room, or other distinct object. This keeps actors small, independent, and easy to scale.
Good examples
User: Manages user profile, preferences, and authenticationDocument: Handles document content, metadata, and versioningChatRoom: Manages participants and message history
Bad examples
Application: Too broad, handles everythingDocumentWordCount: Too granular, should be part of Document actor
Coordinator & Data Actors
Actors scale by splitting state into isolated entities. However, it’s common to need to track and coordinate actors in a central place. This is where coordinator actors come in.
Data actors handle the main logic in your application. Examples: chat rooms, user sessions, game lobbies.
Coordinator actors track other actors. Think of them as an index of data actors. Examples: a list of chat rooms, a list of active users, a list of game lobbies.
Example: Chat Room Coordinator
import { actor, setup } from "rivetkit";
// Data actor: handles messages and connections
const chatRoom = actor({
state: { messages: [] as { sender: string; text: string }[] },
actions: {
sendMessage: (c, sender: string, text: string) => {
const message = { sender, text };
c.state.messages.push(message);
c.broadcast("newMessage", message);
return message;
},
getHistory: (c) => c.state.messages,
},
});
// Coordinator: indexes chat rooms
const chatRoomList = actor({
state: { chatRoomIds: [] as string[] },
actions: {
createChatRoom: async (c, name: string) => {
const client = c.client<typeof registry>();
// Create the chat room actor and get its ID
const handle = await client.chatRoom.create([name]);
const actorId = await handle.resolve();
// Track it in the list
c.state.chatRoomIds.push(actorId);
return actorId;
},
listChatRooms: (c) => c.state.chatRoomIds,
},
});
const registry = setup({
use: { chatRoom, chatRoomList },
});
import { actor, setup } from "rivetkit";
import { createClient } from "rivetkit/client";
const chatRoom = actor({
state: { messages: [] as { sender: string; text: string }[] },
actions: {
sendMessage: (c, sender: string, text: string) => {
const message = { sender, text };
c.state.messages.push(message);
return message;
},
getHistory: (c) => c.state.messages,
},
});
const chatRoomList = actor({
state: { chatRoomIds: [] as string[] },
actions: {
createChatRoom: async (c, name: string) => "room-id",
listChatRooms: (c) => c.state.chatRoomIds,
},
});
const registry = setup({ use: { chatRoom, chatRoomList } });
const client = createClient<typeof registry>("http://localhost:8080");
// Create a new chat room via coordinator
const coordinator = client.chatRoomList.getOrCreate(["main"]);
const actorId = await coordinator.createChatRoom("general");
// Get list of all chat rooms
const chatRoomIds = await coordinator.listChatRooms();
// Connect to a chat room using its ID
const chatRoomHandle = client.chatRoom.getForId(actorId);
await chatRoomHandle.sendMessage("alice", "Hello!");
const history = await chatRoomHandle.getHistory();
Sharding
Sharding splits a single actor’s workload across multiple actors based on a key. Use this when one actor can’t handle all the load or data for an entity.
How it works:
- Partition data using a shard key (user ID, region, time bucket, or random)
- Requests are routed to shards based on the key
- Shards operate independently without coordination
Example: Sharding by Time
import { actor, setup } from "rivetkit";
interface Event {
type: string;
url: string;
}
const hourlyAnalytics = actor({
state: { events: [] as Event[] },
actions: {
trackEvent: (c, event: Event) => {
c.state.events.push(event);
},
getEvents: (c) => c.state.events,
},
});
export const registry = setup({
use: { hourlyAnalytics },
});
import { actor, setup } from "rivetkit";
import { createClient } from "rivetkit/client";
interface Event {
type: string;
url: string;
}
const hourlyAnalytics = actor({
state: { events: [] as Event[] },
actions: {
trackEvent: (c, event: Event) => {
c.state.events.push(event);
},
},
});
const registry = setup({ use: { hourlyAnalytics } });
const client = createClient<typeof registry>("http://localhost:8080");
// Shard by hour: hourlyAnalytics:2024-01-15T00, hourlyAnalytics:2024-01-15T01
const shardKey = new Date().toISOString().slice(0, 13); // "2024-01-15T00"
const analytics = client.hourlyAnalytics.getOrCreate([shardKey]);
await analytics.trackEvent({ type: "page_view", url: "/home" });
Example: Random Sharding
import { actor, setup } from "rivetkit";
const rateLimiter = actor({
state: { requests: {} as Record<string, number> },
actions: {
checkLimit: (c, userId: string, limit: number) => {
const count = c.state.requests[userId] ?? 0;
if (count >= limit) return false;
c.state.requests[userId] = count + 1;
return true;
},
},
});
export const registry = setup({
use: { rateLimiter },
});
import { actor, setup } from "rivetkit";
import { createClient } from "rivetkit/client";
const rateLimiter = actor({
state: { requests: {} as Record<string, number> },
actions: {
checkLimit: (c, userId: string, limit: number) => {
const count = c.state.requests[userId] ?? 0;
if (count >= limit) return false;
c.state.requests[userId] = count + 1;
return true;
},
},
});
const registry = setup({ use: { rateLimiter } });
const client = createClient<typeof registry>("http://localhost:8080");
// Shard randomly: rateLimiter:shard-0, rateLimiter:shard-1, rateLimiter:shard-2
const shardKey = `shard-${Math.floor(Math.random() * 3)}`;
const limiter = client.rateLimiter.getOrCreate([shardKey]);
const allowed = await limiter.checkLimit("user-123", 100);
Choose shard keys that distribute load evenly. Note that cross-shard queries require coordination.
Fan-In & Fan-Out
Fan-in and fan-out are patterns for distributing work and aggregating results.
Fan-Out: One actor spawns work across multiple actors. Use for parallel processing or broadcasting updates.
Fan-In: Multiple actors send results to one aggregator. Use for collecting results or reducing data.
Example: Map-Reduce
import { actor, setup } from "rivetkit";
interface Task {
id: string;
data: string;
}
interface Result {
taskId: string;
output: string;
}
// Coordinator fans out tasks, then fans in results
const coordinator = actor({
state: { results: [] as Result[] },
actions: {
// Fan-out: distribute work in parallel
startJob: async (c, tasks: Task[]) => {
const client = c.client<typeof registry>();
await Promise.all(
tasks.map(task => client.worker.getOrCreate(task.id).process(task))
);
},
// Fan-in: collect results
reportResult: (c, result: Result) => {
c.state.results.push(result);
},
getResults: (c) => c.state.results,
},
});
const worker = actor({
state: {},
actions: {
process: async (c, task: Task) => {
const result = { taskId: task.id, output: `Processed ${task.data}` };
const client = c.client<typeof registry>();
await client.coordinator.getOrCreate("main").reportResult(result);
},
},
});
export const registry = setup({
use: { coordinator, worker },
});
import { actor, setup } from "rivetkit";
import { createClient } from "rivetkit/client";
interface Task {
id: string;
data: string;
}
interface Result {
taskId: string;
output: string;
}
const coordinator = actor({
state: { results: [] as Result[] },
actions: {
startJob: async (c, tasks: Task[]) => {},
reportResult: (c, result: Result) => { c.state.results.push(result); },
getResults: (c) => c.state.results,
},
});
const worker = actor({
state: {},
actions: {
process: async (c, task: Task) => {},
},
});
const registry = setup({ use: { coordinator, worker } });
const client = createClient<typeof registry>("http://localhost:8080");
const coordinatorHandle = client.coordinator.getOrCreate(["main"]);
// Start a job with multiple tasks
await coordinatorHandle.startJob([
{ id: "task-1", data: "..." },
{ id: "task-2", data: "..." },
{ id: "task-3", data: "..." },
]);
// Results are collected as workers report back
const results = await coordinatorHandle.getResults();
Integrating With External Databases & APIs
Actors can integrate with external resources like databases or external APIs.
Loading State
Load external data during actor initialization using createVars. This keeps your actor’s persisted state clean while caching expensive lookups.
Use this when:
- Fetching user profiles, configs, or permissions from a database
- Loading data that changes externally and shouldn’t be persisted
- Caching expensive API calls or computations
Example: Loading User Profile
import { actor, setup } from "rivetkit";
interface User {
id: string;
email: string;
name: string;
}
// Mock database interface for demonstration
const db = {
users: {
findById: async (id: string): Promise<User> => ({ id, email: "user@example.com", name: "User" }),
update: async (id: string, data: Partial<User>) => {},
},
};
const userSession = actor({
state: { requestCount: 0 },
// createVars runs on every wake (after restarts, crashes, or sleep), so
// external data stays fresh.
createVars: async (c): Promise<{ user: User }> => {
// Load from database on every wake
const user = await db.users.findById(c.key.join("-"));
return { user };
},
actions: {
getProfile: (c) => {
c.state.requestCount++;
return c.vars.user;
},
updateEmail: async (c, email: string) => {
c.state.requestCount++;
await db.users.update(c.key.join("-"), { email });
// Refresh cached data
c.vars.user = await db.users.findById(c.key.join("-"));
},
},
});
const registry = setup({
use: { userSession },
});
import { actor, setup } from "rivetkit";
import { createClient } from "rivetkit/client";
interface User {
id: string;
email: string;
name: string;
}
const userSession = actor({
state: { requestCount: 0 },
createVars: () => ({ user: null as User | null }),
actions: {
getProfile: (c) => c.vars.user,
updateEmail: async (c, email: string) => {},
},
});
const registry = setup({ use: { userSession } });
const client = createClient<typeof registry>("http://localhost:8080");
const session = client.userSession.getOrCreate(["user-123"]);
// Get profile (loaded from database on actor wake)
const profile = await session.getProfile();
// Update email (writes to database and refreshes cache)
await session.updateEmail("alice@example.com");
Syncing State Changes
Use onStateChange to automatically sync actor state changes to external resources. This hook is called whenever the actor’s state is modified.
Use this when:
- You need to mirror actor state in an external database
- Triggering external side effects when state changes
- Keeping external systems in sync with actor state
Example: Syncing to Database
import { actor, setup } from "rivetkit";
// Mock database interface for demonstration
const db = {
users: {
insert: async (data: { id: string; email: string; createdAt: number }) => {},
update: async (id: string, data: { email: string; lastActive: number }) => {},
},
};
const userActor = actor({
state: {
email: "",
lastActive: 0,
},
onCreate: async (c, input: { email: string }) => {
// Insert into database on actor creation
await db.users.insert({
id: c.key.join("-"),
email: input.email,
createdAt: Date.now(),
});
},
onStateChange: async (c, newState) => {
// Sync any state changes to database
await db.users.update(c.key.join("-"), {
email: newState.email,
lastActive: newState.lastActive,
});
},
actions: {
updateEmail: (c, email: string) => {
c.state.email = email;
c.state.lastActive = Date.now();
},
getUser: (c) => ({
email: c.state.email,
lastActive: c.state.lastActive,
}),
},
});
const registry = setup({
use: { userActor },
});
import { actor, setup } from "rivetkit";
import { createClient } from "rivetkit/client";
const userActor = actor({
state: { email: "", lastActive: 0 },
actions: {
updateEmail: (c, email: string) => {
c.state.email = email;
c.state.lastActive = Date.now();
},
getUser: (c) => ({
email: c.state.email,
lastActive: c.state.lastActive,
}),
},
});
const registry = setup({ use: { userActor } });
const client = createClient<typeof registry>("http://localhost:8080");
const user = await client.userActor.create(["user-123"], {
input: { email: "alice@example.com" },
});
// Updates state and triggers onStateChange
await user.updateEmail("alice2@example.com");
const userData = await user.getUser();
onStateChange is called after every state modification, ensuring external resources stay in sync.
Anti-Patterns
”God” Actor
Avoid creating a single actor that handles everything. This defeats the purpose of the actor model and creates a bottleneck.
Problem:
import { actor } from "rivetkit";
// Bad: one actor doing everything
const app = actor({
state: { users: {}, orders: {}, inventory: {}, analytics: {} },
actions: {
createUser: (c, user) => { /* ... */ },
processOrder: (c, order) => { /* ... */ },
updateInventory: (c, item) => { /* ... */ },
trackEvent: (c, event) => { /* ... */ },
},
});
Solution: Split into focused actors per entity (User, Order, Inventory, Analytics).
Actor-Per-Request
Actors are designed to maintain state across multiple requests. Creating a new actor for each request wastes resources and loses the benefits of persistent state.
Problem:
import { actor, setup } from "rivetkit";
import { createClient } from "rivetkit/client";
import { Hono } from "hono";
const processor = actor({
state: {},
actions: {
process: (c, body: unknown) => ({ processed: true }),
destroy: (c) => {},
},
});
const registry = setup({ use: { processor } });
const client = createClient<typeof registry>("http://localhost:8080");
const app = new Hono();
// Bad: creating an actor for each API request
app.post("/process", async (c) => {
const actorHandle = client.processor.getOrCreate([crypto.randomUUID()]);
const result = await actorHandle.process(await c.req.json());
await actorHandle.destroy();
return c.json(result);
});
Solution: Use actors for entities that persist (users, sessions, documents), not for one-off operations. For stateless request handling, use regular functions.
API Reference
ActorDefinition- Interface for pattern examplesActorContext- Context usage patternsActionContext- Action patterns