jac-scale Reference#
jac-scale generates REST endpoints from your Jac walkers and functions. Running jac start with this plugin turns every :pub or :priv walker into an API endpoint backed by FastAPI, with automatic Swagger docs, SQLite persistence, and built-in authentication.
For production, the --scale flag automates Docker image builds and Kubernetes deployment -- generating Dockerfiles, manifests, and service configurations from your code. This reference covers server startup options, endpoint generation, authentication, database persistence, Kubernetes deployment, and the CLI flags for each mode.
Installation#
Starting a Server#
Basic Server#
Server Options#
| Option | Description | Default |
|---|---|---|
--port -p |
Server port (auto-fallback if in use) | 8000 |
--main -m |
Treat as __main__ |
false |
--faux -f |
Print generated API docs only (no server) | false |
--dev -d |
Enable HMR (Hot Module Replacement) mode | false |
--api_port -a |
Separate API port for HMR mode (0=same as port) | 0 |
--no_client -n |
Skip client bundling/serving (API only) | false |
--profile |
Configuration profile to load (e.g. prod, staging) | - |
--client |
Client build target for dev server (web, desktop, pwa) | - |
--scale |
Deploy to a target platform instead of running locally | false |
--build -b |
Build and push Docker image (with --scale) | false |
--experimental -e |
Use experimental mode (install from repo instead of PyPI) | false |
--target |
Deployment target (kubernetes, aws, gcp) | kubernetes |
--registry |
Image registry (dockerhub, ecr, gcr) | dockerhub |
--enable-tls |
Enable HTTPS via Let's Encrypt (run after pointing your domain CNAME to the NLB) | false |
Examples#
# Custom port
jac start app.jac --port 3000
# Development with HMR (requires jac-client)
jac start app.jac --dev
# API only -- skip client bundling
jac start app.jac --dev --no_client
# Preview generated API endpoints without starting
jac start app.jac --faux
# Production with profile
jac start app.jac --port 8000 --profile prod
Default Persistence#
When running locally (without --scale), Jac uses SQLite for graph persistence by default. You'll see "Using SQLite for persistence" in the server output. No external database setup is required for development.
CORS Configuration#
[plugins.scale.cors]
allow_origins = ["https://example.com"]
allow_methods = ["GET", "POST", "PUT", "DELETE"]
allow_headers = ["*"]
API Endpoints#
Automatic Endpoint Generation#
Each walker becomes an API endpoint:
Becomes: POST /walker/get_users
Request Format#
Walker parameters become request body:
curl -X POST http://localhost:8000/walker/search \
-H "Content-Type: application/json" \
-d '{"query": "hello", "limit": 20}'
Response Format#
Walker report values become the response.
Middleware Walkers#
Walkers prefixed with _ act as middleware hooks that run before or around normal request processing.
Request Logging#
walker _before_request {
has request: dict;
can log with Root entry {
print(f"Request: {self.request['method']} {self.request['path']}");
}
}
Authentication Middleware#
walker _authenticate {
has headers: dict;
can check with Root entry {
token = self.headers.get("Authorization", "");
if not token.startswith("Bearer ") {
report {"error": "Unauthorized", "status": 401};
return;
}
# Validate token...
report {"authenticated": True};
}
}
Middleware vs Built-in Auth
The _authenticate middleware pattern gives you custom authentication logic. For standard JWT authentication, use jac-scale's built-in auth endpoints (/user/register, /user/login) instead -- see Authentication below.
@restspec Decorator#
The @restspec decorator customizes how walkers and functions are exposed as REST API endpoints.
Options#
| Option | Type | Default | Description |
|---|---|---|---|
method |
HTTPMethod |
POST |
HTTP method for the endpoint |
path |
str |
"" (auto-generated) |
Custom URL path for the endpoint |
protocol |
APIProtocol |
APIProtocol.HTTP |
Protocol for the endpoint (HTTP, WEBHOOK, or WEBSOCKET) |
broadcast |
bool |
False |
Broadcast responses to all connected WebSocket clients (only valid with WEBSOCKET protocol) |
Note:
APIProtocolandrestspecare builtins and do not require an import statement.HTTPMethodmust be imported withimport from http { HTTPMethod }.
Custom HTTP Method#
By default, walkers are exposed as POST endpoints. Use @restspec to change this:
import from http { HTTPMethod }
@restspec(method=HTTPMethod.GET)
walker :pub get_users {
can fetch with Root entry {
report [];
}
}
This walker is now accessible at GET /walker/get_users instead of POST.
Custom Path#
Override the auto-generated path:
@restspec(method=HTTPMethod.GET, path="/custom/users")
walker :pub list_users {
can fetch with Root entry {
report [];
}
}
Accessible at GET /custom/users.
Path Parameters#
Define path parameters using {param_name} syntax:
import from http { HTTPMethod }
@restspec(method=HTTPMethod.GET, path="/items/{item_id}")
walker :pub get_item {
has item_id: str;
can fetch with Root entry { report {"item_id": self.item_id}; }
}
@restspec(method=HTTPMethod.GET, path="/users/{user_id}/orders")
walker :pub get_user_orders {
has user_id: str; # Path parameter
has status: str = "all"; # Query parameter
can fetch with Root entry { report {"user_id": self.user_id, "status": self.status}; }
}
Parameters are classified as: path (matches {name} in path) → file (UploadFile type) → query (GET) → body (other methods).
Functions#
@restspec also works on standalone functions:
@restspec(method=HTTPMethod.GET)
def :pub health_check() -> dict {
return {"status": "healthy"};
}
@restspec(method=HTTPMethod.GET, path="/custom/status")
def :pub app_status() -> dict {
return {"status": "running", "version": "1.0.0"};
}
Webhook Mode#
See the Webhooks section below.
Authentication#
User Registration#
curl -X POST http://localhost:8000/user/register \
-H "Content-Type: application/json" \
-d '{"email": "user@example.com", "password": "secret"}'
User Login#
curl -X POST http://localhost:8000/user/login \
-H "Content-Type: application/json" \
-d '{"email": "user@example.com", "password": "secret"}'
Returns:
Authenticated Requests#
curl -X POST http://localhost:8000/walker/my_walker \
-H "Authorization: Bearer <token>" \
-H "Content-Type: application/json" \
-d '{}'
JWT Configuration#
Configure JWT authentication via environment variables:
| Variable | Description | Default |
|---|---|---|
JWT_SECRET |
Secret key for JWT signing | supersecretkey |
JWT_ALGORITHM |
JWT algorithm | HS256 |
JWT_EXP_DELTA_DAYS |
Token expiration in days | 7 |
SSO (Single Sign-On)#
jac-scale supports SSO with external identity providers. Currently supported: Google.
Configuration:
| Variable | Description |
|---|---|
SSO_HOST |
SSO callback host URL (default: http://localhost:8000/sso) |
SSO_GOOGLE_CLIENT_ID |
Google OAuth client ID |
SSO_GOOGLE_CLIENT_SECRET |
Google OAuth client secret |
SSO Endpoints:
| Method | Path | Description |
|---|---|---|
| GET | /sso/{platform}/login |
Redirect to provider login page |
| GET | /sso/{platform}/register |
Redirect to provider registration |
| GET | /sso/{platform}/login/callback |
OAuth callback handler |
Frontend Callback Redirect:
For browser-based OAuth flows, configure client_auth_callback_url in jac.toml to redirect the SSO callback to your frontend application instead of returning JSON:
When set, the callback endpoint redirects to the configured URL with query parameters:
- On success:
{client_auth_callback_url}?token={jwt_token} - On failure:
{client_auth_callback_url}?error={error_message}
This enables seamless browser-based OAuth flows where the frontend receives the token via URL parameters.
Example:
Admin Portal#
jac-scale includes a built-in admin portal for managing users, roles, and SSO configurations.
Accessing the Admin Portal#
Navigate to http://localhost:8000/admin to access the admin dashboard. On first server start, an admin user is automatically bootstrapped.
Configuration#
| Option | Type | Default | Description |
|---|---|---|---|
enabled |
bool | true |
Enable/disable admin portal |
username |
string | "admin" |
Admin username |
session_expiry_hours |
int | 24 |
Admin session duration in hours |
require_password_reset |
bool | true |
Force admin to change the default password on first login |
Environment Variables:
| Variable | Description |
|---|---|
ADMIN_USERNAME |
Admin username (overrides jac.toml) |
ADMIN_EMAIL |
Admin email (overrides jac.toml) |
ADMIN_DEFAULT_PASSWORD |
Initial password (overrides jac.toml) |
User Roles#
| Role | Value | Description |
|---|---|---|
ADMIN |
admin |
Full administrative access |
MODERATOR |
moderator |
Limited administrative access |
USER |
user |
Standard user access |
Admin API Endpoints#
| Method | Path | Description |
|---|---|---|
| POST | /admin/login |
Admin authentication |
| GET | /admin/users |
List all users |
| GET | /admin/users/{username} |
Get user details |
| POST | /admin/users |
Create a new user |
| PUT | /admin/users/{username} |
Update user role/settings |
| DELETE | /admin/users/{username} |
Delete a user |
| POST | /admin/users/{username}/force-password-reset |
Force password reset |
| GET | /admin/sso/providers |
List SSO providers |
| GET | /admin/sso/users/{username}/accounts |
Get user's SSO accounts |
Permissions & Access Control#
Access Levels#
| Level | Value | Description |
|---|---|---|
NO_ACCESS |
-1 |
No access to the object |
READ |
0 |
Read-only access |
CONNECT |
1 |
Can traverse edges to/from this object |
WRITE |
2 |
Full read/write access |
Granting Permissions#
To Everyone#
Use perm_grant to allow all users to access an object at a given level:
with entry {
# Allow everyone to read this node
perm_grant(node, READ);
# Allow everyone to write
perm_grant(node, WRITE);
}
To a Specific Root#
Use allow_root to grant access to a specific user's root graph:
with entry {
# Allow a specific user to read this node
allow_root(node, target_root_id, READ);
# Allow write access
allow_root(node, target_root_id, WRITE);
}
Revoking Permissions#
From Everyone#
From a Specific Root#
Secure-by-Default Endpoints#
All walker and function endpoints are protected by default -- they require JWT authentication. You must explicitly opt-in to public access using the :pub modifier. This secure-by-default approach prevents accidentally exposing endpoints without authentication.
# Protected (default) -- requires JWT token
walker get_profile {
can fetch with Root entry { report [-->]; }
}
# Public -- no authentication required
walker :pub health_check {
can check with Root entry { report {"status": "ok"}; }
}
# Private -- requires authentication, per-user isolated
walker :priv internal_process {
can run with Root entry { }
}
Walker Access Levels#
Walkers have three access levels when served as API endpoints:
| Access | Description |
|---|---|
Public (:pub) |
Accessible without authentication |
| Protected (default) | Requires JWT authentication |
Private (:priv) |
Requires JWT authentication; per-user isolated (each user operates on their own graph) |
Permission Functions Reference#
| Function | Signature | Description |
|---|---|---|
perm_grant |
perm_grant(archetype, level) |
Allow everyone to access at given level |
perm_revoke |
perm_revoke(archetype) |
Remove all public access |
allow_root |
allow_root(archetype, root_id, level) |
Grant access to a specific root |
disallow_root |
disallow_root(archetype, root_id, level) |
Revoke access from a specific root |
Webhooks#
Webhooks allow external services (payment processors, CI/CD systems, messaging platforms, etc.) to send real-time notifications to your Jac application. Jac-Scale provides:
- Dedicated
/webhook/endpoints for webhook walkers - API key authentication for secure access
- HMAC-SHA256 signature verification to validate request integrity
- Automatic endpoint generation based on walker configuration
Configuration#
Webhook configuration is managed via the jac.toml file in your project root.
[plugins.scale.webhook]
secret = "your-webhook-secret-key"
signature_header = "X-Webhook-Signature"
verify_signature = true
api_key_expiry_days = 365
| Option | Type | Default | Description |
|---|---|---|---|
secret |
string | "webhook-secret-key" |
Secret key for HMAC signature verification. Can also be set via WEBHOOK_SECRET environment variable. |
signature_header |
string | "X-Webhook-Signature" |
HTTP header name containing the HMAC signature. |
verify_signature |
boolean | true |
Whether to verify HMAC signatures on incoming requests. |
api_key_expiry_days |
integer | 365 |
Default expiry period for API keys in days. Set to 0 for permanent keys. |
Environment Variables:
For production deployments, use environment variables for sensitive values:
Creating Webhook Walkers#
To create a webhook endpoint, use the @restspec(protocol=APIProtocol.WEBHOOK) decorator on your walker definition.
Basic Webhook Walker#
@restspec(protocol=APIProtocol.WEBHOOK)
walker PaymentReceived {
has payment_id: str,
amount: float,
currency: str = 'USD';
can process with Root entry {
# Process the payment notification
report {
"status": "success",
"message": f"Payment {self.payment_id} received",
"amount": self.amount,
"currency": self.currency
};
}
}
This walker will be accessible at POST /webhook/PaymentReceived.
Important Notes#
- Webhook walkers are only accessible via
/webhook/{walker_name}endpoints - They are not accessible via the standard
/walker/{walker_name}endpoint
API Key Management#
Webhook endpoints require API key authentication. Users must first create an API key before calling webhook endpoints.
Note: API key metadata is stored persistently in MongoDB (in the
webhook_api_keyscollection), so keys survive server restarts. Previously, keys were held in memory only.
Creating an API Key#
Endpoint: POST /api-key/create
Headers:
Authorization: Bearer <jwt_token>(required)
Request Body:
Response:
{
"api_key": "eyJhbGciOiJIUzI1NiIs...",
"api_key_id": "a1b2c3d4e5f6...",
"name": "My Webhook Key",
"created_at": "2024-01-15T10:30:00Z",
"expires_at": "2024-02-14T10:30:00Z"
}
Listing API Keys#
Endpoint: GET /api-key/list
Headers:
Authorization: Bearer <jwt_token>(required)
Calling Webhook Endpoints#
Webhook endpoints require two headers for authentication:
X-API-Key: The API key obtained from/api-key/createX-Webhook-Signature: HMAC-SHA256 signature of the request body
Generating the Signature#
The signature is computed as: HMAC-SHA256(request_body, api_key)
cURL Example:
API_KEY="eyJhbGciOiJIUzI1NiIs..."
PAYLOAD='{"payment_id":"PAY-12345","amount":99.99,"currency":"USD"}'
SIGNATURE=$(echo -n "$PAYLOAD" | openssl dgst -sha256 -hmac "$API_KEY" | cut -d' ' -f2)
curl -X POST "http://localhost:8000/webhook/PaymentReceived" \
-H "Content-Type: application/json" \
-H "X-API-Key: $API_KEY" \
-H "X-Webhook-Signature: $SIGNATURE" \
-d "$PAYLOAD"
Webhook vs Regular Walkers#
| Feature | Regular Walker (/walker/) |
Webhook Walker (/webhook/) |
|---|---|---|
| Authentication | JWT Bearer token | API Key + HMAC Signature |
| Use Case | User-facing APIs | External service callbacks |
| Access Control | User-scoped | Service-scoped |
| Signature Verification | No | Yes (HMAC-SHA256) |
| Endpoint Path | /walker/{name} |
/webhook/{name} |
Webhook API Reference#
Webhook Endpoints#
| Method | Path | Description |
|---|---|---|
| POST | /webhook/{walker_name} |
Execute webhook walker |
API Key Endpoints#
| Method | Path | Description |
|---|---|---|
| POST | /api-key/create |
Create a new API key |
| GET | /api-key/list |
List all API keys for user |
| DELETE | /api-key/{api_key_id} |
Revoke an API key |
Required Headers for Webhook Requests#
| Header | Required | Description |
|---|---|---|
Content-Type |
Yes | Must be application/json |
X-API-Key |
Yes | API key from /api-key/create |
X-Webhook-Signature |
Yes* | HMAC-SHA256 signature (*if verify_signature is enabled) |
WebSockets#
Jac Scale provides built-in support for WebSocket endpoints, enabling real-time bidirectional communication between clients and walkers.
Overview#
WebSockets allow persistent, full-duplex connections between a client and your Jac application. Unlike REST endpoints (single request-response), a WebSocket connection stays open, allowing multiple messages to be exchanged in both directions. Jac Scale provides:
- Dedicated
/ws/endpoints for WebSocket walkers - Persistent connections with a message loop
- JSON message protocol for sending walker fields and receiving results
- JWT authentication via query parameter or message payload
- Connection management with automatic cleanup on disconnect
- HMR support in dev mode for live reloading
Creating WebSocket Walkers#
To create a WebSocket endpoint, use the @restspec(protocol=APIProtocol.WEBSOCKET) decorator on an async walker definition.
Basic WebSocket Walker (Public)#
@restspec(protocol=APIProtocol.WEBSOCKET)
async walker : pub EchoMessage {
has message: str;
has client_id: str = "anonymous";
async can echo with Root entry {
report {
"echo": self.message,
"client_id": self.client_id
};
}
}
This walker will be accessible at ws://localhost:8000/ws/EchoMessage.
Authenticated WebSocket Walker#
To create a private walker that requires JWT authentication, simply remove : pub from the walker definition.
Broadcasting WebSocket Walker#
Use broadcast=True to send messages to ALL connected clients of this walker:
@restspec(protocol=APIProtocol.WEBSOCKET, broadcast=True)
async walker : pub ChatRoom {
has message: str;
has sender: str = "anonymous";
async can handle with Root entry {
report {
"type": "message",
"sender": self.sender,
"content": self.message
};
}
}
When a client sends a message, all connected clients receive the response, making it ideal for:
- Chat rooms
- Live notifications
- Real-time collaboration
- Game state synchronization
Private Broadcasting Walker#
To create a private broadcasting walker, remove : pub from the walker definition. Only authenticated users can connect and send messages, and all authenticated users receive broadcasts.
Important Notes#
- WebSocket walkers must be declared as
async walker - Use
: pubfor public access (no authentication required) or omit it to require JWT auth - Use
broadcast=Trueto send responses to ALL connected clients (only valid with WEBSOCKET protocol) - WebSocket walkers are only accessible via
ws://host/ws/{walker_name} - The connection stays open until the client disconnects
Storage#
Jac provides a built-in storage abstraction for file and blob operations. The core runtime ships with a local filesystem implementation, and jac-scale can override it with cloud storage backends -- all through the same store() builtin.
The store() Builtin#
The recommended way to get a storage instance is the store() builtin. It requires no imports and is automatically hookable by plugins:
# Get a storage instance (no imports needed)
glob storage = store();
# With custom base path
glob storage = store(base_path="./uploads");
# With all options
glob storage = store(base_path="./uploads", create_dirs=True);
| Parameter | Type | Default | Description |
|---|---|---|---|
base_path |
str |
"./storage" |
Root directory for all files |
create_dirs |
bool |
True |
Create base directory if it doesn't exist |
Without jac-scale, store() returns a LocalStorage instance. With jac-scale installed, it returns a configuration-driven backend (reading from jac.toml and environment variables).
Storage Interface#
All storage instances provide these methods:
| Method | Signature | Description |
|---|---|---|
upload |
upload(source, destination, metadata=None) -> str |
Upload a file (from path or file object) |
download |
download(source, destination=None) -> bytes\|None |
Download a file (returns bytes if no destination) |
delete |
delete(path) -> bool |
Delete a file or directory |
exists |
exists(path) -> bool |
Check if a path exists |
list_files |
list_files(prefix="", recursive=False) |
List files (yields paths) |
get_metadata |
get_metadata(path) -> dict |
Get file metadata (size, modified, created, is_dir, name) |
copy |
copy(source, destination) -> bool |
Copy a file within storage |
move |
move(source, destination) -> bool |
Move a file within storage |
Usage Example#
import from http { UploadFile }
import from uuid { uuid4 }
glob storage = store(base_path="./uploads");
walker :pub upload_file {
has file: UploadFile;
has folder: str = "documents";
can process with Root entry {
unique_name = f"{uuid4()}.dat";
path = f"{self.folder}/{unique_name}";
# Upload file
storage.upload(self.file.file, path);
# Get metadata
metadata = storage.get_metadata(path);
report {
"success": True,
"storage_path": path,
"size": metadata["size"]
};
}
}
walker :pub list_files {
has folder: str = "documents";
has recursive: bool = False;
can process with Root entry {
files = [];
for path in storage.list_files(self.folder, self.recursive) {
metadata = storage.get_metadata(path);
files.append({
"path": path,
"size": metadata["size"],
"name": metadata["name"]
});
}
report {"files": files};
}
}
walker :pub download_file {
has path: str;
can process with Root entry {
if not storage.exists(self.path) {
report {"error": "File not found"};
return;
}
content = storage.download(self.path);
report {"content": content, "size": len(content)};
}
}
Configuration#
Configure storage in jac.toml:
[storage]
storage_type = "local" # Storage backend type
base_path = "./storage" # Base directory for files
create_dirs = true # Auto-create directories
| Option | Type | Default | Description |
|---|---|---|---|
storage_type |
string | "local" |
Storage backend (local) |
base_path |
string | "./storage" |
Base path for file storage |
create_dirs |
boolean | true |
Automatically create directories |
Environment Variables:
| Variable | Description |
|---|---|
JAC_STORAGE_TYPE |
Storage type (overrides jac.toml) |
JAC_STORAGE_PATH |
Base directory (overrides jac.toml) |
JAC_STORAGE_CREATE_DIRS |
Auto-create directories ("true"/"false") |
Configuration priority: jac.toml > environment variables > defaults.
StorageFactory (Advanced)#
For advanced use cases, you can use StorageFactory directly instead of the store() builtin:
import from jac_scale.factories.storage_factory { StorageFactory }
# Create with explicit type and config
glob config = {"base_path": "./my-files", "create_dirs": True};
glob storage = StorageFactory.create("local", config);
# Create using jac.toml / env var / defaults
glob default_storage = StorageFactory.get_default();
Graph Traversal API#
Traverse Endpoint#
Parameters#
| Parameter | Type | Description | Default |
|---|---|---|---|
source |
str | Starting node/edge ID | root |
depth |
int | Traversal depth | 1 |
detailed |
bool | Include archetype context | false |
node_types |
list | Filter by node types | all |
edge_types |
list | Filter by edge types | all |
Example#
curl -X POST http://localhost:8000/traverse \
-H "Authorization: Bearer <token>" \
-H "Content-Type: application/json" \
-d '{
"depth": 3,
"node_types": ["User", "Post"],
"detailed": true
}'
Async Walkers#
walker async_processor {
has items: list;
async can process with Root entry {
results = [];
for item in self.items {
result = await process_item(item);
results.append(result);
}
report results;
}
}
Direct Database Access (kvstore)#
Direct database operations without graph layer abstraction. Supports MongoDB (document queries) and Redis (key-value with TTL/atomic ops).
import from jac_scale.lib { kvstore }
with entry {
mongo_db = kvstore(db_name='my_app', db_type='mongodb');
redis_db = kvstore(db_name='cache', db_type='redis');
}
Parameters: db_name (str), db_type ('mongodb'|'redis'), uri (str|None - priority: explicit → MONGODB_URI/REDIS_URL env vars → jac.toml)
MongoDB Operations#
Common Methods: get(), set(), delete(), exists()
Query Methods: find_one(), find(), insert_one(), insert_many(), update_one(), update_many(), delete_one(), delete_many(), find_by_id(), update_by_id(), delete_by_id(), find_nodes()
Example:
import from jac_scale.lib { kvstore }
with entry {
db = kvstore(db_name='my_app', db_type='mongodb');
db.insert_one('users', {'name': 'Alice', 'role': 'admin', 'age': 30});
alice = db.find_one('users', {'name': 'Alice'});
admins = list(db.find('users', {'role': 'admin'}));
older = list(db.find('users', {'age': {'$gt': 28}}));
db.update_one('users', {'name': 'Alice'}, {'$set': {'age': 31}});
db.delete_one('users', {'name': 'Bob'});
db.set('user:123', {'status': 'active'}, 'sessions');
}
Query Operators: $eq, $gt, $gte, $lt, $lte, $in, $ne, $and, $or
Querying Persisted Nodes (find_nodes)#
Query persisted graph nodes by type with MongoDB filters. Returns deserialized node instances.
with entry{
db = kvstore(db_name='jac_db', db_type='mongodb');
young_users = list(db.find_nodes('User', {'age': {'$lt': 30}}));
admins = list(db.find_nodes('User', {'role': 'admin'}));
}
Parameters: node_type (str), filter (dict, default {}), col_name (str, default '_anchors')
Redis Operations#
Common Methods: get(), set(), delete(), exists()
Redis Methods: set_with_ttl(), expire(), incr(), scan_keys()
Example:
import from jac_scale.lib { kvstore }
with entry {
cache = kvstore(db_name='cache', db_type='redis');
cache.set('session:user123', {'user_id': '123', 'username': 'alice'});
cache.set_with_ttl('temp:token', {'token': 'xyz'}, ttl=60);
cache.set_with_ttl('cache:profile', {'name': 'Alice'}, ttl=3600);
cache.incr('stats:views');
sessions = cache.scan_keys('session:*');
cache.expire('session:user123', 1800);
}
Note: Database-specific methods raise NotImplementedError on wrong database type.
Database and Dashboards#
Auto-Provisioning#
On the first jac start app.jac --scale, jac-scale automatically deploys Redis and MongoDB as Kubernetes StatefulSets with persistent storage. Subsequent deployments only update the application - databases remain untouched.
What gets provisioned:
- MongoDB - StatefulSet with PersistentVolumeClaim (graph persistence,
kvstorebackend) - Redis - Deployment with persistent storage (cache layer, session management)
- Application Deployment - Your Jac app pod(s)
- NGINX Ingress Controller - Single NodePort entry point; routes traffic to ClusterIP services by path
- Services - ClusterIP services for all components (all traffic goes through the Ingress)
- ConfigMaps - Application configuration
| TOML Key | Default | Description |
|---|---|---|
mongodb_enabled |
true |
Auto-provision MongoDB StatefulSet |
redis_enabled |
true |
Auto-provision Redis Deployment |
mongodb_root_username |
admin |
MongoDB root username - stored as a K8s Secret, injected via secretKeyRef |
mongodb_root_password |
password |
MongoDB root password - stored as a K8s Secret, injected via secretKeyRef |
redis_username |
admin |
Redis auth username - stored as a K8s Secret, injected via secretKeyRef |
redis_password |
password |
Redis auth password - stored as a K8s Secret, injected via secretKeyRef |
Credentials are never hardcoded in pod specs. They are stored as Kubernetes Secret resources ({app}-mongodb-secret, {app}-redis-secret) and referenced via valueFrom.secretKeyRef - kubectl describe pod shows the secret name and key, not the actual value.
To disable (use an external database instead):
[plugins.scale.kubernetes]
mongodb_enabled = false # Don't deploy MongoDB - use MONGODB_URI instead
redis_enabled = false # Don't deploy Redis - use REDIS_URL instead
[plugins.scale.database]
mongodb_uri = "mongodb://user:pass@external-host:27017"
redis_url = "redis://external-redis:6379"
Connection Configuration#
Configure database connection URIs via environment variables or jac.toml. Environment variables take priority over jac.toml.
Option 1 - Environment variables (recommended for secrets):
| Variable | Description |
|---|---|
MONGODB_URI |
MongoDB connection URI |
REDIS_URL |
Redis connection URL |
Option 2 - jac.toml:
[plugins.scale.database]
mongodb_uri = "mongodb://localhost:27017" # External MongoDB URI (skip auto-provisioning)
redis_url = "redis://localhost:6379" # External Redis URL (skip auto-provisioning)
shelf_db_path = ".jac/data/anchor_store.db" # SQLite/shelf path for local dev
MONGODB_URIandREDIS_URLenvironment variables take precedence over thejac.tomlvalues when both are set.
| TOML Key | Default | Description |
|---|---|---|
mongodb_uri |
None | External MongoDB URI. When set, K8s MongoDB StatefulSet is not provisioned. |
redis_url |
None | External Redis URL. When set, K8s Redis is not provisioned. |
shelf_db_path |
.jac/data/anchor_store.db |
Local shelf/SQLite storage path for jac start (no K8s) |
Dashboard Configuration#
Dashboards are off by default and must be explicitly enabled in jac.toml:
[plugins.scale.kubernetes]
redis_dashboard = true # Deploy RedisInsight UI (default: false)
mongodb_dashboard = true # Deploy Mongo Express UI (default: false)
jac.toml key |
Description | Default |
|---|---|---|
redis_dashboard |
Deploy RedisInsight dashboard UI | false |
mongodb_dashboard |
Deploy Mongo Express dashboard UI | false |
Dashboard Credentials#
When dashboards are enabled, they are served through the NGINX Ingress at fixed subpaths. No separate NodePorts are needed.
jac.toml key |
Description | Default |
|---|---|---|
redis_insight_username |
RedisInsight basic-auth username | admin |
redis_insight_password |
RedisInsight basic-auth password | admin |
mongo_express_username |
Mongo Express login username | admin |
mongo_express_password |
Mongo Express login password | admin |
Note: When
redis_dashboard = true, the/cache-dashboardroute is always protected by HTTP basic authentication using the credentials above. Change the defaults before deploying to a shared or public cluster.
Access URLs:
| Dashboard | URL |
|---|---|
| Redis Insight | http://localhost:<ingress_node_port>/cache-dashboard/ |
| Mongo Express | http://localhost:<ingress_node_port>/db-dashboard |
Enable dashboards with custom credentials (RedisInsight + Mongo Express):
# jac.toml
[plugins.scale.kubernetes]
redis_dashboard = true
redis_insight_username = "admin"
redis_insight_password = "strongpassword"
mongodb_dashboard = true
mongo_express_username = "admin"
mongo_express_password = "strongpassword"
Memory Hierarchy#
jac-scale uses a tiered memory system:
| Tier | Backend | Purpose |
|---|---|---|
| L1 | In-memory | Volatile runtime state |
| L2 | Redis | Cache layer |
| L3 | MongoDB | Persistent storage |
graph TD
App["Application"] --- L1["L1: Volatile (in-memory)"]
L1 --- L2["L2: Redis (cache)"]
L2 --- L3["L3: MongoDB (persistent)"]
Kubernetes Deployment#
Deployment Modes#
| Mode | Command | Description |
|---|---|---|
| Development | jac start app.jac --scale |
Deploy without building a Docker image - fast iteration |
| Production | jac start app.jac --scale --build |
Build and push Docker image to registry, then deploy |
| Enable HTTPS | jac start app.jac --scale --enable-tls |
Enable TLS on a live deployment (no redeploy, run after CNAME propagates) |
Production mode requires Docker credentials in .env:
Naming & Namespace#
Controls the application name used for all Kubernetes resource names and the namespace resources are created in.
Defaults:
| TOML Key | Default | Description |
|---|---|---|
app_name |
jaseci |
Prefix for all K8s resource names (deployments, services, secrets, etc.) |
namespace |
default |
Kubernetes namespace to deploy into |
To change in jac.toml:
Ports#
Controls how the application is exposed inside the cluster and externally.
All traffic flows through a single NGINX Ingress controller deployed per app. The Ingress controller listens on one NodePort and routes requests to the correct ClusterIP service based on path. Individual services (app, Grafana, dashboards) are all ClusterIP and not directly reachable from outside the cluster.
Defaults:
| TOML Key | Default | Description |
|---|---|---|
container_port |
8000 |
Port your app listens on inside the pod |
ingress_node_port |
30080 |
NodePort for the NGINX Ingress controller (all external traffic enters here) |
Access URLs (local cluster):
| Path | Destination |
|---|---|
http://localhost:30080/ |
Jaseci application |
http://localhost:30080/grafana |
Grafana dashboard (if monitoring enabled) |
http://localhost:30080/cache-dashboard/ |
Redis Insight (if redis_dashboard = true) |
http://localhost:30080/db-dashboard |
Mongo Express (if mongodb_dashboard = true) |
To change in jac.toml:
Rate Limiting (DDoS Protection)#
jac-scale applies NGINX rate limiting annotations to the Ingress to protect against abuse and DDoS traffic. Limits are enforced per client IP.
How it works (leaky bucket algorithm):
ingress_limit_rps- sustained requests per second allowed per IP.ingress_limit_burst_multiplier- burst =limit_rps x burst_multiplier. Requests within the burst are queued; requests beyond it are dropped with429.ingress_limit_connections- maximum number of concurrent open connections per IP. Excess connections are rejected immediately.
Defaults:
| TOML Key | Default | Description |
|---|---|---|
ingress_limit_rps |
20 |
Sustained requests per second per client IP |
ingress_limit_burst_multiplier |
5 |
Burst headroom multiplier (burst = rps × multiplier) |
ingress_limit_connections |
20 |
Max concurrent connections per client IP |
Requests that exceed the limits receive 429 Too Many Requests.
To customize in jac.toml:
[plugins.scale.kubernetes]
ingress_limit_rps = 50 # allow more sustained traffic
ingress_limit_burst_multiplier = 3 # tighter burst control
ingress_limit_connections = 30 # more concurrent connections
Sticky Sessions (Cookie-Based Affinity)#
When your pods hold per-user state (e.g. running user processes), you need requests from the same user to always reach the same pod. jac-scale supports opt-in cookie-based session affinity via NGINX.
Enabled by default. Disable it in jac.toml if not needed:
How it works:
On the first response, NGINX sets a route cookie in the browser. Every subsequent request includes that cookie and NGINX uses it to route back to the same pod, regardless of IP changes (mobile networks, NAT, VPN, proxies). The cookie never expires in the browser.
| Behaviour | Detail |
|---|---|
| Cookie name | route |
| Cookie lifetime | Never expires (max-age ~68 years) |
| On pod failure | NGINX re-routes to a healthy pod and rewrites the cookie automatically |
| IP changes (mobile/NAT) | Handled correctly - routing is cookie-based, not IP-based |
When to use:
- Your pods run stateful per-user processes (e.g. sandbox environments, background workers per user)
- You need a user to consistently land on the pod that owns their session
Limitations:
Sticky sessions ensure routing while a pod is alive. If a pod is deleted (e.g. during a rolling deployment), in-flight user processes on that pod are lost. The user is automatically re-routed to a new pod, but any in-memory state is gone. For true resilience, externalize per-user state to Redis or a database so any pod can serve any user.
Domain & TLS (HTTPS)#
jac-scale supports custom domain names and automatic HTTPS via cert-manager + Let's Encrypt. TLS is a two-step process to avoid the chicken-and-egg problem (NLB hostname is unknown until after the first deploy).
Step 1 - Deploy (HTTP)#
Set your domain in jac.toml and deploy normally:
After deploy, the NLB hostname is printed:
Deployment complete! Service available at: http://k8s-default-...elb.amazonaws.com
Point your domain CNAME to: k8s-default-...elb.amazonaws.com
Step 2 - Add CNAME record#
In your DNS registrar (Namecheap, Route 53, Cloudflare, etc.) add:
| Type | Host | Value |
|---|---|---|
| CNAME | app (or @) |
k8s-default-...elb.amazonaws.com |
Wait for DNS propagation (usually 1–15 minutes). Verify with dig app.example.com.
Step 3 - Enable TLS#
This installs cert-manager, creates a Let's Encrypt Issuer, patches the live Ingress with TLS annotations, and updates all service URLs to HTTPS. No redeployment of your application occurs.
Output:
TLS enabled. App is now live at:
App URL: https://app.example.com
Grafana: https://app.example.com/grafana
Mongo Express: https://app.example.com/db-dashboard
RedisInsight: https://app.example.com/cache-dashboard
Note:
--enable-tlsrequiresdomainto be set injac.toml. It will error if no domain is configured.
Configuration options:
| TOML Key | Default | Description |
|---|---|---|
domain |
"" |
Custom domain name (e.g. app.example.com). Leave empty for NLB-only access. |
cert_manager_email |
"" |
Email for Let's Encrypt certificate registration and expiry notices. |
Certificate renewal is automatic - cert-manager renews ~30 days before expiry.
Resource Limits#
Controls CPU and memory requests/limits for the application container. Kubernetes uses requests for scheduling and limits for enforcement (OOM-kill).
Defaults:
| TOML Key | Default | Description |
|---|---|---|
cpu_request |
None | CPU units reserved for scheduling (e.g. "250m") |
cpu_limit |
None | Maximum CPU the container may use (e.g. "1000m") |
memory_request |
None | Memory reserved for scheduling (e.g. "256Mi") |
memory_limit |
None | Memory ceiling - container is OOM-killed if exceeded |
Accepted suffixes: Ki, Mi, Gi (binary) or K, M, G (decimal).
To change in jac.toml:
[plugins.scale.kubernetes]
cpu_request = "250m"
cpu_limit = "1000m"
memory_request = "256Mi"
memory_limit = "2Gi"
Health Probes#
Kubernetes uses readiness and liveness probes to decide when a pod is ready to serve traffic and when to restart it. Both probes hit GET <health_check_path> on the container.
Defaults:
| TOML Key | Default | Description |
|---|---|---|
health_check_path |
Endpoint probed by both readiness and liveness checks | |
readiness_initial_delay |
10 |
Seconds to wait before first readiness check |
readiness_period |
20 |
Seconds between readiness checks |
liveness_initial_delay |
10 |
Seconds to wait before first liveness check |
liveness_period |
20 |
Seconds between liveness checks |
liveness_failure_threshold |
80 |
Consecutive failures before the pod is restarted |
To change in jac.toml:
[plugins.scale.kubernetes]
health_check_path = "/health"
readiness_initial_delay = 15
readiness_period = 10
liveness_initial_delay = 30
liveness_period = 30
liveness_failure_threshold = 5
Tip: Set
health_check_path = "/health"to use the built-in liveness and readiness endpoints - see Health Checks.
Horizontal Pod Autoscaling (HPA)#
jac-scale creates a Kubernetes HPA that scales the application pod count up or down based on average CPU utilization across all pods.
Defaults:
| TOML Key | Default | Description |
|---|---|---|
min_replicas |
1 |
Minimum number of pods (HPA lower bound) |
max_replicas |
3 |
Maximum number of pods (HPA upper bound) |
cpu_utilization_target |
50 |
Average CPU % across pods that triggers scale-out |
To change in jac.toml:
[plugins.scale.kubernetes]
min_replicas = 2
max_replicas = 10
cpu_utilization_target = 70 # Scale out when average CPU exceeds 70%
HPA requires
cpu_requestto be set. Without a CPU request, Kubernetes cannot compute a utilization percentage.
Persistent Storage#
Controls the PersistentVolumeClaim (PVC) size for MongoDB and Redis StatefulSets. The same size applies to both.
Default:
| TOML Key | Default | Description |
|---|---|---|
pvc_size |
5Gi |
Storage size for each database PVC |
To change in jac.toml:
Note: PVC size cannot be reduced after creation. Increasing it requires deleting and recreating the StatefulSet (data loss). Plan accordingly.
Container Images#
Controls the base images used for the application pod and init containers. Override these when you need a specific Python version or when operating in air-gapped environments.
Defaults:
| TOML Key | Default | Description |
|---|---|---|
python_image |
python:3.12-slim |
Base image for the application pod |
busybox_image |
busybox:1.36 |
Init container image used for dependency health checks |
To change in jac.toml:
Additional Packages#
Install extra pip packages into the pod at startup, alongside the standard Jaseci stack.
Default: [] (none)
To add in jac.toml:
Packages are installed at pod startup before the application starts. For frequently-updated packages, prefer building a custom Docker image with --build instead to keep startup times short.
Jaseci Source Pinning (Experimental)#
When using --experimental mode, Jaseci packages are installed from the GitHub repository instead of PyPI. Pin a specific branch or commit for reproducible builds.
Defaults:
| TOML Key | Default | Description |
|---|---|---|
jaseci_repo_url |
https://github.com/jaseci-labs/jaseci.git |
GitHub repository to install Jaseci packages from |
jaseci_branch |
main |
Repository branch to install from |
jaseci_commit |
None | Specific commit SHA - leave empty for latest of the branch |
To change in jac.toml:
Package Version Pinning#
Pin specific PyPI versions for Jaseci packages installed inside the pod. Use "none" to skip a package entirely.
Defaults: all packages default to "latest" from PyPI.
To configure in jac.toml:
[plugins.scale.kubernetes.plugin_versions]
jaclang = "0.1.5" # Pin to a specific version
jac_scale = "latest" # Latest from PyPI (default)
jac_client = "0.1.0" # Specific version
jac_byllm = "none" # Skip installation entirely
| Package | Description |
|---|---|
jaclang |
Core Jac language runtime |
jac_scale |
This scaling plugin |
jac_client |
Frontend/client support |
jac_byllm |
LLM integration (set to "none" to exclude) |
Monitoring Stack#
jac-scale can deploy a full observability stack (Prometheus + Grafana + kube-state-metrics + node-exporter) into the same namespace as your application.
| Component | Purpose |
|---|---|
| Prometheus | Collects and stores metrics (ClusterIP - internal only, scraped by Grafana) |
| Grafana | Dashboard UI - served via NGINX Ingress at /grafana (NodePort locally, NLB on AWS) |
| kube-state-metrics | K8s object state: pod counts, replica health, restart counts |
| node-exporter | Host-level metrics: CPU, memory, disk, network per node |
Defaults:
| TOML Key | Default | Description |
|---|---|---|
enabled |
false |
Deploy the monitoring stack and expose the app's /metrics endpoint |
k8s_metrics_enabled |
true |
Include kube-state-metrics and node-exporter exporters |
prometheus_admin_password |
Adminpassword123 |
Grafana admin login password |
To enable in jac.toml:
[plugins.scale.monitoring]
enabled = true
k8s_metrics_enabled = true
prometheus_admin_password = "StrongPassword123!"
After deployment, access:
- Grafana:
http://localhost:<ingress_node_port>/grafana- log in withadmin/<prometheus_admin_password>
On AWS clusters, the NGINX Ingress controller is exposed via a Network Load Balancer (NLB). Grafana is accessible at <nlb-url>/grafana.
Prometheus scrape targets:
- Jaseci application
/metricsendpoint - kube-state-metrics (pod, deployment, replica, restart state)
- node-exporter (CPU, memory, disk, network per node)
To collect application metrics, also enable
[plugins.scale.metrics] enabled = true- see Prometheus Metrics.
Deployment Status#
Check the live health of all deployed components:
Displays a table with:
- Component health - Jaseci App, Redis, MongoDB, Prometheus, Grafana
- Pod readiness -
ready/totalreplica count per component - Service URLs - application endpoint and Grafana URL
Status values:
| Value | Meaning |
|---|---|
Running |
All pods ready |
Degraded |
Some pods ready, others not |
Pending |
Pods are starting up |
Restarting |
One or more pods are crash-looping |
Failed |
No pods are running |
Not Deployed |
Component was never provisioned |
Resource Tagging#
All Kubernetes resources created by jac-scale are labeled managed: jac-scale for easy auditing:
# List all jac-scale managed resources across all namespaces
kubectl get all -l managed=jac-scale -A
Tagged resource types: Deployments, StatefulSets, Services, ConfigMaps, Secrets, PersistentVolumeClaims, HorizontalPodAutoscalers.
Remove Deployment#
Warning
You will be prompted to confirm with y before deletion proceeds. The command deletes the entire namespace and all its resources - including persistent volumes and database data.
Removes:
- Application Deployment and pods
- Redis and MongoDB StatefulSets
- PersistentVolumeClaims (data is lost)
- Services, ConfigMaps, Secrets, and HPA
Health Checks#
Built-in endpoints are available for Kubernetes probes:
/health-- Liveness probe/ready-- Readiness probe
You can also create custom health walkers:
Health Endpoint#
Create a health walker:
Access at: POST /walker/health
Readiness Check#
walker ready {
can check with Root entry {
db_ok = check_database();
cache_ok = check_cache();
if db_ok and cache_ok {
report {"status": "ready"};
} else {
report {
"status": "not_ready",
"db": db_ok,
"cache": cache_ok
};
}
}
}
Builtins#
Root Access#
Memory Commit#
CLI Commands#
| Command | Description |
|---|---|
jac start app.jac |
Start local API server |
jac start app.jac --scale |
Deploy to Kubernetes |
jac start app.jac --scale --build |
Build image and deploy |
jac start app.jac --scale --target kubernetes |
Explicit deployment target (default) |
jac start app.jac --scale --enable-tls |
Enable HTTPS on a live deployment (no redeploy) |
jac status app.jac |
Show live deployment status |
jac status app.jac --target kubernetes |
Status for a specific target |
jac destroy app.jac |
Remove Kubernetes deployment (prompts for confirmation) |
jac destroy app.jac --target kubernetes |
Destroy a specific target |
API Documentation#
When server is running:
- Swagger UI:
http://localhost:8000/docs - ReDoc:
http://localhost:8000/redoc - OpenAPI JSON:
http://localhost:8000/openapi.json
Graph Visualization#
Navigate to http://localhost:8000/graph to view an interactive visualization of your application's graph directly in the browser.
- Without authentication - displays the public graph (super root), useful for applications with public endpoints
- With authentication - click the Login button in the header to sign in and view your user-specific graph
The visualizer uses a force-directed layout with color-coded node types, edge labels, tooltips on hover, and controls for refresh, fit-to-view, and physics toggle. If a user has previously logged in (via a jac-client app or the login modal), the existing jac_token in localStorage is picked up automatically.
| Endpoint | Description |
|---|---|
GET /graph |
Serves the graph visualization UI |
GET /graph/data |
Returns graph nodes and edges as JSON (optional Authorization header) |
Prometheus Metrics#
jac-scale provides built-in Prometheus metrics collection for monitoring HTTP requests and walker execution. When enabled, a /metrics endpoint is automatically registered for Prometheus to scrape.
Configuration#
Configure metrics in jac.toml:
[plugins.scale.metrics]
enabled = true # Enable metrics collection and /metrics endpoint
endpoint = "/metrics" # Prometheus scrape endpoint path
namespace = "myapp" # Metrics namespace prefix
walker_metrics = true # Enable per-walker execution timing
histogram_buckets = [0.005, 0.01, 0.025, 0.05, 0.075, 0.1, 0.25, 0.5, 0.75, 1.0, 2.5, 5.0, 10.0]
| Option | Type | Default | Description |
|---|---|---|---|
enabled |
bool | false |
Enable Prometheus metrics collection and /metrics endpoint |
endpoint |
string | "/metrics" |
Path for the Prometheus scrape endpoint |
namespace |
string | "jac_scale" |
Metrics namespace prefix |
walker_metrics |
bool | false |
Enable walker execution timing metrics |
histogram_buckets |
list | [0.005, ..., 10.0] |
Histogram bucket boundaries in seconds |
Note: If
namespaceis not set, it is derived from the Kubernetes namespace config (sanitized) or defaults to"jac_scale".
Exposed Metrics#
| Metric | Type | Labels | Description |
|---|---|---|---|
{namespace}_http_requests_total |
Counter | method, path, status_code |
Total HTTP requests processed |
{namespace}_http_request_duration_seconds |
Histogram | method, path |
HTTP request latency in seconds |
{namespace}_http_requests_in_progress |
Gauge | -- | Concurrent HTTP requests |
{namespace}_walker_duration_seconds |
Histogram | walker_name, success |
Walker execution duration (only when walker_metrics=true) |
Authentication#
The /metrics endpoint requires admin authentication. Include the admin token in the Authorization header:
# Scrape metrics (admin token required)
curl -H "Authorization: Bearer <admin_token>" http://localhost:8000/metrics
Unauthenticated requests receive a 403 Forbidden response. This protects sensitive server performance data from unauthorized access.
Admin Metrics Dashboard#
The admin portal includes a monitoring page that displays metrics in a visual dashboard. Access it at /admin and navigate to the Monitoring section.
Additionally, the /admin/metrics endpoint returns parsed metrics as structured JSON:
Response format:
{
"status": "success",
"data": {
"metrics": [
{
"name": "jac_scale_http_requests_total",
"type": "counter",
"help": "Total HTTP requests processed",
"values": [
{"labels": {"method": "GET", "path": "/", "status_code": "200"}, "value": 42}
]
}
],
"summary": {
"total_requests": 156,
"avg_latency_ms": 45.2,
"error_rate_percent": 0.5,
"active_requests": 2
}
}
}
The admin dashboard monitoring page displays:
- HTTP traffic breakdown by method and status code
- Request latency statistics
- Active requests gauge
- System metrics (GC collections, memory usage, CPU time, file descriptors)
Requests to the metrics endpoint itself are excluded from tracking.
Kubernetes Secrets#
Manage sensitive environment variables securely in Kubernetes deployments using the [plugins.scale.secrets] section.
Configuration#
[plugins.scale.secrets]
OPENAI_API_KEY = "${OPENAI_API_KEY}"
DATABASE_PASSWORD = "${DB_PASS}"
STATIC_VALUE = "hardcoded-value"
Values using ${ENV_VAR} syntax are resolved from the local environment at deploy time. The resolved key-value pairs are created as a proper Kubernetes Secret ({app_name}-secrets) and injected into pods via envFrom.secretRef.
How It Works#
- At
jac start app.jac --scale, environment variable references (${...}) are resolved - A Kubernetes
OpaqueSecret named{app_name}-secretsis created (or updated if it already exists) - The Secret is attached to the deployment pod spec via
envFrom.secretRef - All keys become environment variables inside the container
- On
jac destroy, the Secret is automatically cleaned up
Example#
# jac.toml
[plugins.scale.secrets]
OPENAI_API_KEY = "${OPENAI_API_KEY}"
MONGO_PASSWORD = "${MONGO_PASSWORD}"
JWT_SECRET = "${JWT_SECRET}"
# Set local env vars, then deploy
export OPENAI_API_KEY="sk-..."
export MONGO_PASSWORD="secret123"
export JWT_SECRET="my-jwt-key"
jac start app.jac --scale --build
This eliminates the need for manual kubectl create secret commands after deployment.
Setting Up Kubernetes#
Docker Desktop (Easiest)#
- Install Docker Desktop
- Open Settings > Kubernetes
- Check "Enable Kubernetes"
- Click "Apply & Restart"
Minikube#
# Install
brew install minikube # macOS
# or see https://minikube.sigs.k8s.io/docs/start/
# Start cluster
minikube start
# Access your app via minikube service
minikube service jaseci -n default
MicroK8s (Linux)#
Troubleshooting#
Application Not Accessible#
# Check pod status
kubectl get pods
# Check service
kubectl get svc
# For minikube, use tunnel
minikube service jaseci
Database Connection Issues#
# Check StatefulSets
kubectl get statefulsets
# Check persistent volumes
kubectl get pvc
# View database logs
kubectl logs -l app=mongodb
kubectl logs -l app=redis
Build Failures (--build mode)#
- Ensure Docker daemon is running
- Verify
.envhas correctDOCKER_USERNAMEandDOCKER_PASSWORD - Check disk space for image building
General Debugging#
# Describe a pod for events
kubectl describe pod <pod-name>
# Get all resources
kubectl get all
# Check events
kubectl get events --sort-by='.lastTimestamp'
Library Mode#
For teams preferring pure Python syntax or integrating Jac into existing Python codebases, Library Mode provides an alternative deployment approach. Instead of .jac files, you use Python files with Jac's runtime as a library.
Complete Guide: See Library Mode for the full API reference, code examples, and migration guide.
Key Features:
- All Jac features accessible through
jaclang.libimports - Pure Python syntax with decorators (
@on_entry,@on_exit) - Full IDE/tooling support (autocomplete, type checking, debugging)
- Zero migration friction for existing Python projects
Quick Example:
from jaclang.lib import Node, Walker, spawn, root, on_entry
class Task(Node):
title: str
done: bool = False
class TaskFinder(Walker):
@on_entry
def find(self, here: Task) -> None:
print(f"Found: {here.title}")
spawn(TaskFinder(), root())
Sandbox Environments#
jac-scale includes a sandbox system for creating isolated, ephemeral preview environments. Each sandbox runs a user's Jac application in its own container or pod with resource limits, network isolation, and automatic cleanup -- ideal for live preview, collaborative editing, or CI/CD preview deployments.
Overview#
The sandbox system follows jac-scale's factory pattern: an abstract SandboxEnvironment interface with three provider implementations. You choose the provider via configuration, and the factory handles instantiation.
| Provider | Isolation | Use Case |
|---|---|---|
local |
Subprocess | Local development, no container runtime needed |
docker |
Container | Staging, basic isolation with Docker |
kubernetes |
Pod | Production, full isolation with resource limits and RBAC |
Configuration#
Enable and configure sandboxes in jac.toml:
[plugins.scale.sandbox]
enabled = true
type = "kubernetes" # "kubernetes", "docker", or "local"
namespace = "jac-sandboxes" # K8s namespace for sandbox pods
max_per_user = 3 # Maximum concurrent sandboxes per user
ttl_seconds = 3600 # Auto-cleanup after this many seconds (1 hour)
cpu_limit = "500m" # CPU limit per sandbox
memory_limit = "512Mi" # Memory limit per sandbox
base_image = "python:3.12-slim" # Base Docker/K8s image
storage_limit = "256Mi" # Scratch storage (/tmp) limit
domain_template = "{sandbox_id}.preview.example.com" # URL template
security_context = true # Run as non-root, no privilege escalation
network_isolation = true # Isolate sandboxes from each other
ingress_class = "nginx" # K8s Ingress class (nginx, alb, traefik)
tls_enabled = false # Enable TLS via cert-manager
tls_issuer = "letsencrypt-prod" # cert-manager ClusterIssuer name
proxy_mode = false # Use shared proxy instead of per-sandbox Ingress
warm_pool_size = 0 # Pre-initialized pods for instant startup (K8s only)
| Option | Type | Default | Description |
|---|---|---|---|
enabled |
bool | false |
Enable the sandbox system |
type |
string | "local" |
Provider: "kubernetes", "docker", or "local" |
namespace |
string | "jac-sandboxes" |
Kubernetes namespace for sandbox resources |
max_per_user |
int | 3 |
Maximum concurrent sandboxes per user |
ttl_seconds |
int | 3600 |
Time-to-live before automatic cleanup (seconds) |
cpu_limit |
string | "500m" |
CPU limit per sandbox (K8s format) |
memory_limit |
string | "512Mi" |
Memory limit per sandbox (K8s format) |
base_image |
string | "python:3.12-slim" |
Base container image for sandboxes |
storage_limit |
string | "256Mi" |
Ephemeral storage limit for /tmp |
domain_template |
string | "{sandbox_id}.preview.example.com" |
URL template ({sandbox_id} is replaced) |
security_context |
bool | true |
Enable security context (non-root, no privilege escalation) |
network_isolation |
bool | true |
Isolate sandboxes from each other |
ingress_class |
string | "nginx" |
Kubernetes Ingress class name |
tls_enabled |
bool | false |
Enable TLS via cert-manager |
tls_issuer |
string | "letsencrypt-prod" |
cert-manager ClusterIssuer name |
proxy_mode |
bool | false |
Use shared routing proxy (see Proxy Mode) |
warm_pool_size |
int | 0 |
Number of pre-initialized warm pods (see Warm Pool) |
Environment Variables (override jac.toml):
| Variable | Description |
|---|---|
JAC_SANDBOX_TYPE |
Provider type ("kubernetes", "docker", "local") |
JAC_SANDBOX_NAMESPACE |
Kubernetes namespace |
JAC_SANDBOX_DOMAIN |
Domain template |
Configuration priority: jac.toml > environment variables > defaults.
Programmatic Usage#
Use SandboxFactory to create and manage sandboxes in your Jac code:
import from jac_scale.factories.sandbox_factory { SandboxFactory }
# Create sandbox using jac.toml config
glob sandbox = SandboxFactory.get_default();
# Or create with explicit type and config
glob sandbox = SandboxFactory.create("kubernetes", {
"namespace": "jac-sandboxes",
"base_image": "python:3.12-slim",
"memory_limit": "1Gi",
"ttl_seconds": 1800,
"domain_template": "{sandbox_id}.preview.example.com"
});
Creating a Sandbox#
with entry {
result = sandbox.create(
user_id="user-123",
project_id="my-project",
code_path="/path/to/project/files"
);
if result.success {
print(f"Sandbox ready at: {result.url}");
print(f"Sandbox ID: {result.sandbox_id}");
}
}
Sandbox Lifecycle#
with entry {
# Check status
status = sandbox.status("jac-sbx-abc123");
print(f"State: {status.state}"); # pending, starting, running, stopped, error
# List user's sandboxes
sandboxes = sandbox.list_sandboxes("user-123");
for s in sandboxes {
print(f"{s.sandbox_id}: {s.state} - {s.url}");
}
# Stop a sandbox
sandbox.stop("jac-sbx-abc123");
# Destroy and clean up all resources
sandbox.destroy("jac-sbx-abc123");
# Clean up expired sandboxes (beyond TTL)
cleaned = sandbox.cleanup_expired();
print(f"Cleaned {cleaned} expired sandboxes");
}
File Operations#
Read, write, and manage files inside a running sandbox:
with entry {
# Write a file
sandbox.write_file("jac-sbx-abc123", "main.jac", "with entry { print('hello'); }");
# Read a file
result = sandbox.read_file("jac-sbx-abc123", "main.jac");
print(result["content"]);
# Read binary files (images) -- returned as base64
result = sandbox.read_file("jac-sbx-abc123", "assets/logo.png");
# result = {"success": True, "content": "<base64>", "is_binary": True, "mime_type": "image/png"}
# Delete a file
sandbox.delete_file("jac-sbx-abc123", "old_file.jac");
# List files
result = sandbox.list_files("jac-sbx-abc123");
for f in result["files"] {
print(f);
}
}
Path Security: All file paths are validated against directory traversal, absolute paths, and shell metacharacters. Paths like ../, /etc/passwd, or strings containing ;, |, &, ` are rejected.
Excluded Directories: File listing automatically skips .jac/, node_modules/, __pycache__/, dist/, and .git/.
Command Execution#
with entry {
result = sandbox.exec_command("jac-sbx-abc123", "ls -la /app", timeout=30);
print(result["stdout"]);
}
Log Retrieval#
with entry {
result = sandbox.logs("jac-sbx-abc123", offset=0);
print(result["content"]);
# result["offset"] contains the byte offset for the next read (streaming)
}
Sandbox States#
| State | Description |
|---|---|
pending |
Pod/container created, waiting to start |
starting |
Container starting, installing dependencies |
running |
Application fully ready and serving traffic |
stopping |
Shutdown in progress |
stopped |
Container stopped |
error |
Error or crash state |
Local Sandbox Provider#
The local provider runs each sandbox as a subprocess on the host machine. No container runtime required.
How it works:
- Allocates a port pair from a pool (base ports 5180-5200, stride of 2)
- Runs
jac start main.jac --dev -p {port}as a child process - Checks for readiness by scanning process output for
"Server ready" - Returns
http://localhost:{port}as the preview URL
Environment sourcing:
- Global:
~/.jac-ide/global.env(if it exists) - Project:
.envin the project directory (if it exists)
Limitations:
- No isolation between sandboxes
- No resource limits
- Port pool limits concurrent sandboxes (10 by default)
- Development and testing only
Docker Sandbox Provider#
The docker provider runs each sandbox in an isolated Docker container with resource limits.
[plugins.scale.sandbox]
enabled = true
type = "docker"
base_image = "python:3.12-slim"
memory_limit = "512Mi"
cpu_limit = "500m"
network_isolation = true
How it works:
- Creates a Docker container from
base_image - Copies project files into
/appvia tarball injection - Runs
jac install && jac start main.jac --dev -p 8000 - Applies resource limits (memory, CPU, storage)
- Optionally creates an isolated Docker bridge network per sandbox
- Polls container health via HTTP until ready (120s timeout)
Container labels:
| Label | Value |
|---|---|
jac-sandbox |
true |
jac-sandbox-id |
{sandbox_id} |
jac-sandbox-user |
{user_id} |
jac-sandbox-project |
{project_id} |
Requirements: Docker daemon must be running on the host.
Kubernetes Sandbox Provider#
The kubernetes provider creates isolated pods in a dedicated namespace with RBAC, resource limits, and automatic cleanup. This is the recommended provider for production.
[plugins.scale.sandbox]
enabled = true
type = "kubernetes"
namespace = "jac-sandboxes"
base_image = "python:3.12-slim"
memory_limit = "2Gi"
cpu_limit = "500m"
ttl_seconds = 3600
max_per_user = 3
security_context = true
How it works:
- Ensures namespace exists with label
jac-sandbox: namespace - Provisions RBAC (ServiceAccount, Role, RoleBinding) for pod management
- Packages project files into a ConfigMap (text files in
data, binary files inbinaryDataas base64) - Creates a pod with an init container that unpacks the ConfigMap into
/app - Main container runs
jac install && jac start main.jac --dev -p 8000 - Creates a Service and Ingress (unless
proxy_mode = true) - Polls pod readiness (container ready + "Server ready" in logs, 120s timeout)
- Returns the preview URL
Pod naming: jac-sbx-{user}-{project}-{uuid} (lowercase, max 63 chars per K8s requirements)
Pod labels:
| Label | Value |
|---|---|
jac-sandbox |
true |
jac-sandbox-id |
{sandbox_id} |
jac-sandbox-user |
{user_id} |
jac-sandbox-project |
{project_id} |
Environment variables injected into sandbox pods:
| Variable | Value | Purpose |
|---|---|---|
JAC_SANDBOX_ID |
{sandbox_id} |
Sandbox identifier |
JAC_SANDBOX_USER |
{user_id} |
Owner user ID |
JAC_SANDBOX_PROJECT |
{project_id} |
Project ID |
CHOKIDAR_USEPOLLING |
1 |
Force file watcher to use polling (for HMR) |
WATCHPACK_POLLING |
true |
Webpack polling fallback (for HMR) |
Resource configuration:
- Limits:
cpu_limit,memory_limitfrom config - Requests: 100m CPU, 64Mi memory (fixed)
- Scratch storage:
storage_limitas tmpfs on/tmp - Active deadline:
ttl_seconds(K8s kills the pod after this) - Graceful shutdown: 10 seconds
Security context (when enabled):
runAsNonRoot: truerunAsUser: 1000allowPrivilegeEscalation: false
ConfigMap limits: Project files are packed into a single ConfigMap with a 1MB size limit. Binary files (images, fonts, etc.) are stored in the binaryData field using base64 encoding. Files in .jac/, node_modules/, __pycache__/, dist/, and .git/ directories are excluded.
RBAC auto-provisioning: On first use, the provider creates a Role (jac-sandbox-manager) and RoleBinding in the sandbox namespace with permissions for pods, services, configmaps, and ingresses. If running inside a K8s cluster, it binds the role to the pod's ServiceAccount (via POD_SERVICE_ACCOUNT and POD_NAMESPACE environment variables).
Automatic cleanup: A background thread runs every 60 seconds and:
- Lists all sandbox pods in the namespace
- Deletes pods older than
ttl_seconds - Deletes pods in terminal states (Failed, Succeeded)
- Purges stale registry entries for pods that no longer exist
Ingress Routing#
When using type = "kubernetes", sandboxes need to be accessible from the browser. There are two routing modes:
Per-Sandbox Ingress (default)#
Each sandbox gets its own Kubernetes Ingress resource:
[plugins.scale.sandbox]
proxy_mode = false # default
ingress_class = "nginx" # or "alb", "traefik"
domain_template = "{sandbox_id}.preview.example.com"
tls_enabled = true
tls_issuer = "letsencrypt-prod"
Traffic flow:
Each sandbox creates:
- A
ClusterIPService:{sandbox_id}-svc - An Ingress resource:
{sandbox_id}-ingresswith the configured hostname
Custom Ingress annotations:
[plugins.scale.sandbox.ingress_annotations]
"nginx.ingress.kubernetes.io/proxy-read-timeout" = "3600"
"nginx.ingress.kubernetes.io/proxy-send-timeout" = "3600"
TLS: When tls_enabled = true, cert-manager is used to automatically provision TLS certificates. Requires a ClusterIssuer named tls_issuer to be deployed in the cluster.
Drawback: Creating per-sandbox Ingress resources is slow on some cloud providers (e.g., AWS ALB target group registration takes 30-60 seconds).
Proxy Mode#
A single shared proxy service routes traffic to all sandboxes by pod IP. No per-sandbox Ingress or Service is created.
Traffic flow:
How it works:
- A single proxy deployment runs in the sandbox namespace (2 replicas recommended)
- The proxy watches all pods labeled
jac-sandbox=truevia the Kubernetes Watch API - It maintains an in-memory routing table:
sandbox_id → {ip, phase, ready} - Incoming requests have their
Hostheader parsed to extract thesandbox_id(e.g.,jac-sbx-abc.preview.example.com → jac-sbx-abc) - HTTP requests are forwarded to
http://{pod_ip}:8000{path} - WebSocket connections are bidirectionally relayed (supports Vite HMR with
vite-hmrsub-protocol)
Loading page: When a sandbox pod isn't ready yet, the proxy returns an auto-refreshing HTML page with a loading spinner. The page refreshes every 2 seconds until the pod is ready, then serves the actual application. This only applies to browser navigation requests (Accept: text/html); API calls receive proper 502/503 status codes.
Advantages over per-sandbox Ingress:
- Instant routing (no Ingress provisioning delay)
- No per-sandbox K8s resources (Service, Ingress)
- Scales to hundreds of concurrent sandboxes
- Native WebSocket support for HMR
Proxy environment variables:
| Variable | Default | Description |
|---|---|---|
SANDBOX_NAMESPACE |
jac-sandboxes |
Namespace to watch for sandbox pods |
SANDBOX_LABEL |
jac-sandbox=true |
Label selector for sandbox pods |
INTERNAL_PORT |
8000 |
Port on sandbox pods |
PROXY_PORT |
8080 |
Port the proxy listens on |
Deploying the proxy: K8s manifest templates are included in jac-scale/targets/kubernetes/templates/sandbox-proxy/:
rbac.yaml-- ServiceAccount + Role (get/list/watch pods) + RoleBindingdeployment.yaml-- 2-replica Deployment (replaceREPLACE_WITH_IMAGEwith your built proxy image)service.yaml-- ClusterIP Service on port 8080ingress.yaml-- Wildcard Ingress (replace*.example.comwith your domain)
The proxy itself is a Jac application at jac-scale/providers/proxy/sandbox_proxy.jac. Build it with the provided Dockerfile at jac-scale/targets/kubernetes/templates/sandbox-proxy.Dockerfile:
FROM python:3.12-slim
RUN pip install --no-cache-dir aiohttp kubernetes_asyncio jaclang jac-scale
COPY sandbox_proxy.jac /app/sandbox_proxy.jac
WORKDIR /app
EXPOSE 8080
CMD ["jac", "run", "sandbox_proxy.jac"]
Health check endpoint: GET /_proxy/health returns ok (N routes) where N is the number of tracked sandbox pods.
Warm Pool#
The warm pool pre-creates idle pods that are ready to accept code instantly, eliminating pod scheduling and image pull delays.
How it works:
- On startup, the provider creates
warm_pool_sizepods usingbase_image - Warm pods run a wait loop:
while [ ! -f /app/.jac-start ]; do sleep 0.5; done - When a sandbox is requested, a warm pod is claimed and relabeled with the user's sandbox ID
- Project code is injected via
kubectl exec(tar stream piped into the pod) - A signal file (
/app/.jac-start) is touched, triggeringjac install && jac start - The pool automatically replenishes in the background
Warm pod labels:
| Label | Value |
|---|---|
jac-sandbox |
true |
jac-sandbox-pool |
warm (idle) or active (claimed) |
Benefits:
- Eliminates ~10 seconds of pod scheduling + image pull time
- No ConfigMap creation needed (code is injected directly)
- Pool replenishes automatically after each claim
Fallback: If no warm pod is available (pool exhausted), the provider falls back to the standard cold-start path (ConfigMap + new pod creation).
HMR (Hot Module Replacement) Support#
When using proxy_mode = true, Vite HMR works through the proxy:
The proxy:
- Detects WebSocket upgrade requests via the
Upgrade: websocketheader - Forwards the
Sec-WebSocket-Protocolheader (e.g.,vite-hmr) to the backend - Uses a separate session with no timeout for long-lived WebSocket connections
- Bidirectionally relays
TEXTandBINARYmessages - Properly propagates close events between both sides
File watcher polling: Sandbox pods have CHOKIDAR_USEPOLLING=1 and WATCHPACK_POLLING=true environment variables set. This forces Vite's file watcher to use polling instead of inotify, which is necessary because files written via kubectl exec don't trigger filesystem notification events.
Troubleshooting#
Sandbox pod stuck in Pending#
Check events for scheduling failures, insufficient resources, or image pull errors.
Preview shows loading page indefinitely#
# Check if pod is running
kubectl get pods -n jac-sandboxes -l jac-sandbox-id=<sandbox-id>
# Check pod logs
kubectl logs <pod-name> -n jac-sandboxes -c sandbox
Common causes: jac install failing (missing dependencies), port conflict, application crash.
ConfigMap too large#
If your project exceeds the 1MB ConfigMap limit, consider:
- Using
warm_pool_size > 0(warm pools inject code via tar, no size limit) - Adding large files to the base image instead
- Excluding unnecessary files from the project directory
HMR not updating the preview#
Verify the proxy is forwarding WebSocket traffic:
# Check proxy logs
kubectl logs -l app=sandbox-proxy -n jac-sandboxes
# Verify proxy health
curl http://<proxy-service>:8080/_proxy/health
Cleaning up stuck sandboxes#
# List all sandbox pods
kubectl get pods -n jac-sandboxes -l jac-sandbox=true
# Delete a specific sandbox
kubectl delete pod <pod-name> -n jac-sandboxes
# Delete all sandboxes
kubectl delete pods -n jac-sandboxes -l jac-sandbox=true