Deploying a Crew on CrewAI Enterprise
After creating a crew locally or through Crew Studio, the next step is deploying it to the CrewAI Enterprise platform. This guide covers multiple deployment methods to help you choose the best approach for your workflow.
You should have a working crew either built locally or created through Crew Studio
Your crew code should be in a GitHub repository (for GitHub integration method)
The CLI provides the fastest way to deploy locally developed crews to the Enterprise platform.
Install CrewAI CLI
If you haven’t already, install the CrewAI CLI:
The CLI comes with the main CrewAI package, but the [tools]
extra ensures you have all deployment dependencies.
Authenticate with the Enterprise Platform
First, you need to authenticate your CLI with the CrewAI Enterprise platform:
When you run either command, the CLI will:
Upon successful authentication, you’ll see a confirmation message in your terminal!
Create a Deployment
From your project directory, run:
This command will:
.env
fileOn successful creation, you’ll see a message like:
Monitor Deployment Progress
Track the deployment status with:
For detailed logs of the build process:
The first deployment typically takes 10-15 minutes as it builds the container images. Subsequent deployments are much faster.
The CrewAI CLI offers several commands to manage your deployments:
You can also deploy your crews directly through the CrewAI Enterprise web interface by connecting your GitHub account. This approach doesn’t require using the CLI on your local machine.
Pushing to GitHub
You need to push your crew to a GitHub repository. If you haven’t created a crew yet, you can follow this tutorial.
Connecting GitHub to CrewAI Enterprise
Select the Repository
After connecting your GitHub account, you’ll be able to select which repository to deploy:
Set Environment Variables
Before deploying, you’ll need to set up your environment variables to connect to your LLM provider or other services:
KEY=VALUE
format (one per line)Deploy Your Crew
Once deployment is complete, you’ll see:
Important: CrewAI Enterprise has security restrictions on environment variable names that can cause deployment failures if not followed.
For security reasons, the following environment variable naming patterns are automatically filtered and will cause deployment issues:
Blocked Patterns:
_TOKEN
(e.g., MY_API_TOKEN
)_PASSWORD
(e.g., DB_PASSWORD
)_SECRET
(e.g., API_SECRET
)_KEY
in certain contextsSpecific Blocked Variables:
GITHUB_USER
, GITHUB_TOKEN
AWS_REGION
, AWS_DEFAULT_REGION
Some variables are explicitly allowed despite matching blocked patterns:
AZURE_AD_TOKEN
AZURE_OPENAI_AD_TOKEN
ENTERPRISE_ACTION_TOKEN
CREWAI_ENTEPRISE_TOOLS_TOKEN
If your deployment fails due to environment variable restrictions:
PROVIDER_API_KEY
instead of PROVIDER_TOKEN
If you encounter deployment failures with cryptic environment variable errors, check your variable names against these patterns first.
Once deployment is complete, you can access your crew through:
REST API: The platform generates a unique HTTPS endpoint with these key routes:
/inputs
: Lists the required input parameters/kickoff
: Initiates an execution with provided inputs/status/{kickoff_id}
: Checks the execution statusWeb Interface: Visit app.crewai.com to access:
From the Enterprise dashboard, you can:
The Enterprise platform provides comprehensive observability features:
The Enterprise platform also offers:
Contact our support team for assistance with deployment issues or questions about the Enterprise platform.