Deploy From Zero

This guide starts from a clean development machine and brings up a private Monkeys stack with the current multi-repository layout.

1. Prepare The Machine

Install:

Git
Docker Engine or Docker Desktop
Docker Compose v2
Node.js 18 or later
Yarn 1.x for the main Node.js services

Docker needs enough memory for PostgreSQL, Redis, Elasticsearch, Conductor, MinIO, Prometheus, Grafana, and product services. For Docker Desktop, allocate at least 12 GB memory when possible.

2. Create A Workspace

Keep Monkeys repositories as siblings. The compose files in monkeys use this layout when building service images.

mkdir -p INFMONKEYS
cd INFMONKEYS

git clone https://github.com/infmonkeys/monkeys.git
git clone https://github.com/infmonkeys/monkeys-server.git
git clone https://github.com/infmonkeys/monkeys-studio.git
git clone https://github.com/infmonkeys/monkeys-kernel.git
git clone https://github.com/infmonkeys/monkeys-compute.git

Clone optional capability services only when you need them:

git clone https://github.com/infmonkeys/monkeys-agent-server.git
git clone https://github.com/infmonkeys/monkeys-billing-server.git
git clone https://github.com/infmonkeys/monkeys-data-server.git
git clone https://github.com/infmonkeys/monkeys-webhook-server.git
git clone https://github.com/infmonkeys/monkeys-mcp-server.git
git clone https://github.com/infmonkeys/monkeys-conductor-worker.git
git clone https://github.com/infmonkeys/monkeys-training-worker.git
git clone https://github.com/infmonkeys/monkeys-comfyui-worker.git
git clone https://github.com/infmonkeys/monkey-tools-third-party-api.git
git clone https://github.com/infmonkeys/monkey-tools-third-party-api-python.git
git clone https://github.com/infmonkeys/monkey-tools-sandbox.git
git clone https://github.com/infmonkeys/monkey-tools-agentkits.git

3. Start Infrastructure

The infrastructure compose file lives in the hub repository.

cd monkeys/docker/infrastructure
docker compose up -d

Expected local endpoints:

Service	Endpoint
PostgreSQL	`localhost:5432`
Redis	`localhost:6379`
Elasticsearch	`http://localhost:9200`
Conductor API	`http://localhost:8080/api`
Conductor UI	`http://localhost:5008`
MinIO API	`http://localhost:9000`
MinIO console	`http://localhost:9001`
Prometheus	`http://localhost:9090`
Grafana	`http://localhost:3003`

Check the core dependencies before starting product services:

docker compose ps
curl http://localhost:8080/health
curl http://localhost:9200/_cluster/health

4. Start Core Product Services

From the services compose directory:

cd ../services
docker compose up -d --build

The default profile builds and starts:

monkeys-server
monkeys-studio
monkeys-kernel
monkeys-compute

Core service ports:

Service	Endpoint
Studio	`http://localhost:3000`
Main backend	`http://localhost:33002`
Kernel frontend	`http://localhost:3001`
Compute frontend	`http://localhost:3002`

5. Add Capability Profiles

Start optional profiles only after their sibling repositories are cloned.

docker compose --profile agent up -d --build
docker compose --profile billing up -d --build
docker compose --profile data up -d --build
docker compose --profile webhook up -d --build
docker compose --profile mcp up -d --build
docker compose --profile worker up -d --build
docker compose --profile tools up -d --build

Profiles can be combined:

docker compose --profile agent --profile tools up -d --build

6. Verify The Stack

Use these checks after startup:

docker compose ps
curl http://localhost:33002

Then open Studio at http://localhost:3000, create or select a team, configure model credentials, and create a small workflow with one model node and one explicit output.

7. Stop Or Reset

Stop product services:

cd monkeys/docker/services
docker compose down

Stop infrastructure:

cd ../infrastructure
docker compose down

Delete local infrastructure data only when you intentionally want a clean database and object store:

docker compose down -v