Deployment
Learn how to deploy, version, and manage AI Builder applications across environments
Deploying AI Builder use cases requires a structured approach to move your solutions from development to production. This guide outlines strategies for versioning, deploying, and managing applications across different environments to ensure reliability and performance.
Deployment Strategies
Best for: Basic applications with minimal complexity, such as simple prompting agents
In this approach, you use a single workspace for both development and production:
- Development: Create and test your application directly in the workspace
- Production: Once tested, the same workspace serves as the production environment
- Version Control: Use versioning to save stable points for potential rollback
Advantages:
- Simplest deployment approach
- No need to migrate between workspaces
- Quick iteration and updates
Considerations:
- Limited separation between development and production
- Higher risk of disruptive changes affecting live users
- Best suited for applications with low complexity and minimal regulatory constraints
Best for: Basic applications with minimal complexity, such as simple prompting agents
In this approach, you use a single workspace for both development and production:
- Development: Create and test your application directly in the workspace
- Production: Once tested, the same workspace serves as the production environment
- Version Control: Use versioning to save stable points for potential rollback
Advantages:
- Simplest deployment approach
- No need to migrate between workspaces
- Quick iteration and updates
Considerations:
- Limited separation between development and production
- Higher risk of disruptive changes affecting live users
- Best suited for applications with low complexity and minimal regulatory constraints
Best for: Moderately complex applications with some regulatory needs
In this approach, you use multiple workspaces on the same Prisme.ai instance:
- Development Workspace: For building and testing
- Production Workspace: For live user access
- Optional Pre-Production Workspace: For final testing before deployment
Advantages:
- Clear separation between development and production
- Same instance simplifies resource management
- Different access controls for each environment
Considerations:
- Requires process for migrating between workspaces
- All environments share the same Prisme.ai instance resources
- Good balance of separation and simplicity
Best for: Complex enterprise applications with strict regulatory requirements
In this approach, you use separate Prisme.ai instances for each environment:
- Development Instance: For building and initial testing
- Staging/Pre-production Instance: For integration testing and validation
- Production Instance: For live user access
Advantages:
- Complete isolation between environments
- Independent scaling and resource allocation
- Highest level of security and stability
Considerations:
- Most complex to manage
- Requires robust deployment processes
- Necessary for applications with strict compliance requirements
Versioning Your Application
Configure Git Repository
Set up version control for your workspace:
- Access workspace raw configuration by clicking “Edit source code” in the workspace action menu
- Add repository configuration to the end of the file:
You can use secrets for sensitive information:
For SSH authentication, use:
Remember to use git@github.com:YourUser/your-repository.git
format for SSH URLs.
Push to Repository
Save your workspace state:
- From the workspace action menu, select “Versions”
- Choose the repository you configured
- Click “Push to repository”
- Enter a commit message describing your changes
- Submit to save the current state
This creates a snapshot of your workspace in the remote repository.
Pull from Repository
Retrieve saved workspace state:
- From the workspace action menu, select “Versions”
- Choose the repository you want to pull from
- Click “Pull from repository”
- Confirm the operation
This updates your workspace with the state stored in the repository.
Exclude Files from Import
Protect specific configurations during pulls:
This prevents overwriting custom configurations when pulling changes.
Deployment Methods
Understanding What’s Versioned
Included in Versioning
Workspace components that are saved and deployed:
- Pages and their configurations
- Blocks and custom components
- Automations and workflows
- Security roles and permissions
- App configurations
- Workspace settings
Not Included in Versioning
Data that remains specific to each environment:
- Events and their history
- Collection data
- Crawled documents
- Uploaded files
- User-specific settings
- Runtime state
The versioned content is identical to what’s included in the workspace export archive.
Environment-Specific Configuration
Manage differences between environments:
Use Workspace Secrets
Store environment-specific values as secrets:
Access these values in your application using:
Conditional Logic
Implement environment-aware behavior in automations:
This allows your applications to adapt to different environments.
Handling Pull Results
After each import or repository pull, Prisme.ai emits a workspaces.imported
event with details:
You can create automations that listen for this event to:
- Log deployment activities
- Notify team members of successful deployments
- Track errors and conflicts
- Trigger post-deployment tasks
Deployment Best Practices
Version Everything
Maintain complete history of your application:
- Commit changes frequently with clear messages
- Use branches for feature development
- Tag important releases (e.g., v1.0.0)
- Document significant version changes
- Never work directly in production
Test Before Deployment
Validate thoroughly before moving to production:
- Test in development environment first
- Verify integrations with external systems
- Test with realistic data sets
- Include user acceptance testing
- Conduct security testing
Controlled Deployment
Implement safeguards around deployment:
- Use approval workflows for production changes
- Deploy during low-traffic periods
- Implement monitoring during deployment
- Prepare rollback procedures
- Document deployment steps
Environment Isolation
Maintain clear boundaries between environments:
- Use separate API keys for each environment
- Configure different external service endpoints
- Apply appropriate security controls by environment
- Use visual indicators to distinguish environments
- Limit production access to necessary personnel
Troubleshooting Deployments
Next Steps
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