109 lines
4.2 KiB
Plaintext
109 lines
4.2 KiB
Plaintext
---
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title: "In-VPC Deployments"
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description: "Deploy Bifrost within your private cloud infrastructure with VPC isolation, custom networking, and enhanced security controls for enterprise environments."
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icon: "cloud"
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---
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In-VPC (Virtual Private Cloud) deployments allow you to run Bifrost entirely within your private cloud infrastructure, providing maximum security, compliance, and control over your AI gateway deployment.
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## Supported Cloud Providers
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Bifrost supports INVPC deployments across all major cloud providers:
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<div className="grid grid-cols-2 md:grid-cols-3 gap-4 my-6">
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<div className="flex items-center gap-2 p-3 border rounded-lg">
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<span>Google Cloud Platform</span>
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</div>
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<div className="flex items-center gap-2 p-3 border rounded-lg">
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<span>Amazon Web Services</span>
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</div>
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<div className="flex items-center gap-2 p-3 border rounded-lg">
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<span>Microsoft Azure</span>
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</div>
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<div className="flex items-center gap-2 p-3 border rounded-lg">
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<span>Cloudflare</span>
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</div>
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<div className="flex items-center gap-2 p-3 border rounded-lg">
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<span>Vercel</span>
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</div>
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</div>
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## Architecture Benefits
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### Security & Compliance
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- **Network Isolation**: Complete isolation within your VPC with no external network dependencies
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- **Data Sovereignty**: All data processing occurs within your controlled environment
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- **Compliance Ready**: Meets requirements for HIPAA, SOC2, GDPR, and other regulatory frameworks
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- **Zero Trust Architecture**: Implements principle of least privilege with granular access controls
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### Performance & Reliability
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- **Low Latency**: Direct communication between services within your network
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- **High Availability**: Multi-zone deployment with automatic failover capabilities
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- **Guaranteed Uptime**: 99.95% SLA with comprehensive monitoring and alerting
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### Control & Customization
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- **Custom Networking**: Configure subnets, routing, and security groups to your specifications
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- **Resource Management**: Full control over compute, storage, and network resources
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- **Scaling Policies**: Define auto-scaling rules based on your usage patterns
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## Service Level Agreement
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### Availability Commitment
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- **Uptime Guarantee**: 99.95% monthly uptime for all core components
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- **Downtime Calculation**: `(Total Minutes - Downtime Minutes) / Total Minutes × 100`
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- **Partial Downtime**: Reduced functionality counted as 50% downtime
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### Core Components Covered
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The following components are monitored for SLA compliance:
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- Gateway instance
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- Log ingestion pipeline
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### Exclusions
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SLA excludes downtime due to:
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- Scheduled maintenance (14-day advance notice)
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- Downstream provider incidents
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- Client hardware/software/network issues
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- Third-party AI provider outages
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- Client misuse or unauthorized modifications
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## Support & Maintenance
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### Technical Support
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- **24/7 Critical Support**: Available for core component issues
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- **Multiple Channels**: Platform, email (contact@getmaxim.ai), or Slack Connect
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- **Audit Trail**: Detailed logs for any data access during troubleshooting
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### Maintenance Windows
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- **Scheduled Maintenance**: 14-day advance notice for major updates
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- **Security Patches**: Immediate or 14-day delayed application (your choice)
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- **Continuous Updates**: Regular feature improvements with 7-day advance notice
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## Getting Started
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### Prerequisites
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- VPC with appropriate CIDR ranges
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- Kubernetes cluster (GKE, EKS, or AKS)
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- Container registry access
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- DNS configuration for internal routing
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### Deployment Process
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1. **Infrastructure Setup**: Configure VPC, subnets, and security groups
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2. **Cluster Preparation**: Set up Kubernetes cluster with required permissions
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3. **Bifrost Installation**: Deploy using provided Helm charts or manifests
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4. **Configuration**: Apply your specific settings and integrations
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5. **Validation**: Run connectivity and performance tests
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6. **Go Live**: Begin routing production traffic
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## Cost Optimization
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### Resource Sizing
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- **Development**: 2 vCPU, 4GB RAM minimum
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- **Production**: 4+ vCPU, 8GB+ RAM recommended
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- **High Availability**: Multi-zone deployment with load balancing
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### Scaling Strategies
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- **Horizontal Pod Autoscaling**: Based on CPU/memory utilization
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- **Vertical Pod Autoscaling**: Automatic resource adjustment
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- **Cluster Autoscaling**: Node pool expansion/contraction
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