Deployment
This section covers different ways to deploy Kexa in your environment.
Local Deployment
Run Kexa directly on your machine:
- Simple setup
- Good for development
- Easy to debug
- Direct access to logs
See Local Deployment for details.
Docker Deployment
Run Kexa in a container:
- Isolated environment
- Easy to scale
- Consistent runtime
- Simple updates
See Docker Deployment for details.
Kubernetes Deployment
Deploy Kexa in a Kubernetes cluster:
- High availability
- Automatic scaling
- Resource management
- Easy monitoring
See Kubernetes Deployment for details.
GitHub Actions Deployment
Run Kexa as a GitHub Action in your CI/CD pipeline:
- Automated compliance checks
- Pre-production validation
- No infrastructure costs
- Easy integration with GitHub workflows
- Multi-provider support
See GitHub Actions Deployment for details.
Azure Function Deployment
Run Kexa as an Azure Function:
- Serverless architecture
- Pay-per-use
- Automatic scaling
- Easy integration with Azure services
See Azure Function Deployment for details.
Deployment Considerations
When choosing a deployment method, consider:
- Scale requirements
- Resource constraints
- Monitoring needs
- Update frequency
- Security requirements
- Cost implications