specification

Vector Database Deployment Architecture Analysis

Executive Summary

Recommendation: The dedicated per-customer deployment model offers the most favorable balance of operational simplicity, security, and reliability.

While shared services appear to offer resource efficiency, this analysis shows that dedicated deployments significantly reduce operational complexity, security risks, and maintenance overhead. The modest increase in resource consumption is substantially outweighed by reduced operational burden, simpler troubleshooting, stronger security isolation, and elimination of cross-customer impacts.

Key benefits of dedicated deployment:

• Simplified security model primarily using network isolation with optional token verification via reverse proxy
• Elimination of complex token management systems for multi-tenant deployments
• Complete isolation preventing cross-customer impacts during outages
• Reduced attack surface and simplified security posture
• Straightforward scaling, backup, and recovery processes

Overview

This analysis evaluates deployment options for our vector database system used in the AI Copilot feature. The document covers:

• Architectural comparison of shared vs. dedicated deployment models
• Cost analysis (infrastructure and operational labor)
• Security and performance implications
• Implementation requirements for each approach
• Risk assessment and operational complexity considerations

This document shows three primary deployment architectures:

1. Fully Shared Services: Single embedding service and vector database serving all customers
2. Hybrid Approach: Shared embedding service with dedicated vector databases per customer
3. Fully Dedicated Services: Separate embedding and vector database instances per customer

Security Layer Implementation

The system architecture includes a layered security approach:

Factor	Network Isolation Only	Network Isolation + Reverse Proxy Token Verification
Primary Security Mechanism	VPC and subnet isolation	VPC and subnet isolation
Secondary Security	None	Token verification through reverse proxy
Configuration	Simple network rules	Network rules + reverse proxy configuration + tokens
Purpose	Prevent unauthorized access	Added protection against misconfiguration
Operational Impact	Minimal	Moderate (reverse proxy configuration and token management)

Both Ollama embedding service and Qdrant vector database can have token verification implemented through a reverse proxy:

• Implementation: Authentication handled entirely by the reverse proxy, not by the services themselves
• Token Handling: VectorStoreConfig supplies tokens that will be sent with requests to both services
• Library Support: The library will include these tokens in the appropriate headers when making requests

The token verification layer provides an additional security measure beyond network isolation, which can protect services if cloud configuration mistakes occur.

Overall Architecture Comparison

Factor	Fully Shared	Hybrid Approach	Fully Dedicated
Initial Setup Complexity	High	Medium	Low
Ongoing Maintenance	High	Medium-High	Low
Security Posture	Weakest	Medium	Strongest
Performance Isolation	Poor	Medium	Excellent
Resource Efficiency	Highest	Medium	Lowest
Failure Isolation	Poor	Medium	Excellent
Implementation Time	Weeks-Months	Weeks	Days
Operational Risk	High	Medium	Low
Debugging Complexity	High	Medium	Low
Configuration Errors Risk	High	Medium	Low

Cost Analysis

Infrastructure Costs

Cost Category	Shared Services	Dedicated Services
Computing Resources	Lower overall resource utilization	Higher due to idle capacity (~2-4GB RAM per customer for model)
Storage Requirements	Slightly lower	Slightly higher due to duplication
Network Usage	Similar	Similar
Licensing Impact	Similar	Similar

Labor Costs

Shared services require substantial additional implementation effort for authentication systems, token management infrastructure, and security controls. Ongoing maintenance involves regular token rotation and security verification activities.

Cost Category	Shared Services	Dedicated Services
Initial Implementation	Extra dedicated project needed: - Authentication system development - Token management infrastructure - Security validation - Cross-tenant isolation	Existing deployment solution: - Standard container templates - Basic network configuration - Optional reverse proxy setup
Ongoing Administration	Regular activities required: - Token rotation procedures - Token database maintenance - Access control updates - Customer token management	Minimal activities required: - Standard container updates - Basic health monitoring - Optional token rotation
Security Management	Regular activities required: - Token security audits - Cross-tenant isolation verification - Permission boundary reviews	Standard container security practices - Optional token rotation
Incident Response	Complex procedures required: - Cross-customer impact assessment - Tenant isolation verification - Coordinated recovery	Straightforward procedures: - Single customer impact - Independent recovery
Customer Onboarding	Multiple steps required: - Token generation - Token distribution - Documentation - Permission configuration	Simple deployment automation - Optional token configuration

Risk-Related Costs

Risk Category	Shared Services	Dedicated Services
Security Breach Impact	Potentially all customers	Limited to single customer
Downtime Impact	All affected customers	Single affected customer
Misconfiguration Risk	High (complex authentication)	Low (simple network rules + optional token verification)
Recovery Time	Longer, more complex	Faster, straightforward

Detailed Deployment Architecture Comparison

Embedding Service Deployment Options

Factor	Shared Embedding Service	Dedicated Embedding Service
Authentication Requirements	Complex token-based authentication system API gateway for authentication Token issuance & rotation infrastructure Token-to-customer mapping database	Network-level isolation as primary security Optional token verification via reverse proxy No token mapping/management system required
Performance Management	Per-customer rate limiting Fair usage policies Queue management Noisy neighbor mitigation	Predictable performance No cross-customer impacts
Resource Utilization	More efficient memory usage Higher utilization of compute resources	~2-4GB memory overhead per instance Idle capacity during low usage
Operational Complexity	Token generation workflows Token rotation procedures Emergency revocation process Token security measures	Simple network configuration Standard container deployment Optional token management
Monitoring & Alerting	Customer-specific request tracking Per-customer quota monitoring Cross-customer usage patterns	Simple instance health checks Basic resource monitoring
Security Risks	Token leakage/theft Cross-tenant data access Privilege escalation vectors	Lower attack surface Strong tenant isolation Simple security model

Vector Database Deployment Options

Factor	Shared Vector Database	Dedicated Vector Database
Security Implementation	Namespace-to-token mapping system Authorization middleware Collection access control Cross-namespace protection	Network isolation as primary security Optional token verification via reverse proxy No cross-customer access possible
Data Isolation	Logical separation only listNamespaces() information disclosure Shared lock infrastructure	Complete physical isolation No data leakage possibilities
Performance Characteristics	Unpredictable load patterns Resource contention risks Complex scaling requirements Noisy neighbor effects	Predictable performance Independent scaling Resource guarantees
Operational Complexity	Namespace permission management Cross-namespace security auditing Complex backup/restore procedures	Simple instance management Straightforward backup/restore
Failure Impact Radius	All customers affected by outages Cascading failure risks Complex recovery procedures	Failures isolated to single customer Independent recovery No cascading failures
Scalability Approach	Complex horizontal scaling Data replication challenges Consistency management	Simple vertical scaling Predictable growth patterns

Implementation Requirements

1. Required for Shared Embedding Service

To implement a secure, multi-tenant embedding service:

1. Authentication System:
   • Token generation infrastructure
   • Secure token storage system
   • Token distribution mechanism to customers
   • Token validation middleware
2. Token Lifecycle Management:
   • Scheduled rotation process (typically 30-90 days)
   • Emergency revocation procedures
   • Expired token cleanup
   • Token version tracking
3. Access Control:
   • Request validation middleware
   • Rate limiting per customer
   • Usage quotas and enforcement
   • Abuse detection systems
4. Monitoring and Auditing:
   • Per-customer usage tracking
   • Token usage patterns analysis
   • Suspicious activity detection
   • Usage reporting system

2. Required for Shared Vector Database

To implement a secure, multi-tenant vector database:

1. Namespace Security:
   • Namespace-to-customer mapping system
   • Namespace access validation layer
   • Prevention of cross-namespace operations
   • Modifications to listNamespaces() to prevent information disclosure
2. Performance Isolation:
   • Per-namespace resource quotas
   • Operation rate limiting
   • Priority-based scheduling
   • Noisy neighbor detection and mitigation
3. Data Isolation Enhancements:
   • Security auditing for namespace operations
   • Access control for collection operations
   • Namespace-based locks to prevent information leakage
4. Operational Support:
   • Per-namespace backup/restore capabilities
   • Selective recovery procedures
   • Customer-specific maintenance windows

3. Required for Dedicated Per-Customer Solution

To implement a dedicated per-customer solution:

1. Deployment Automation:
   • Customer provisioning templates
   • Container orchestration configurations
   • Resource allocation specifications
2. Network Isolation:
   • Customer-specific network segments
   • Simple IP/hostname whitelisting
   • Basic firewall rules
3. Optional Token Verification (implemented through reverse proxy):
   • Reverse proxy configuration for token validation
   • Token generation and management processes
   • Library configuration to supply tokens
4. Resource Management:
   • Right-sized container specifications
   • Vertical scaling guidelines
   • Resource monitoring baseline

Conclusion

The analysis demonstrates significant differences in operational complexity, security posture, and long-term maintenance requirements between shared and dedicated architectural approaches.

While shared services offer some resource efficiency benefits, these advantages are outweighed by substantial increases in:

1. Authentication and security infrastructure requirements
2. Operational complexity for token management
3. Cross-tenant isolation challenges
4. Increased risk surface area
5. More complex troubleshooting and debugging

The dedicated service approach, while consuming slightly more resources due to idle capacity, dramatically simplifies the security model, operational procedures, and failure isolation. The reduction in configuration complexity alone significantly decreases the risk of security or operational incidents.

The design allows for optional token verification via a reverse proxy as a defense-in-depth measure without significantly complicating the deployment model. This provides an additional safeguard against potential cloud configuration mistakes while maintaining network isolation as the primary security mechanism.

For organizations with limited operational resources to dedicate to security infrastructure and token management, the slight increase in infrastructure costs for dedicated deployments is substantially offset by reduced operational overhead and risk exposure.

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