Multi-Provider Failover
Enterprise-grade high availability with automatic failover across multiple AI providers
Build resilient AI applications with automatic provider failover and redundancy
Overview
Multi-provider failover enables your application to automatically switch between AI providers when one fails, ensuring high availability and reliability. NeurosLink AI provides built-in failover capabilities with configurable priorities, conditions, and retry strategies.
Key Benefits
🔒 99.9%+ Uptime: Automatic failover when providers are down
⚡ Zero Downtime: Seamless switching between providers
💰 Cost Optimization: Route to cheaper providers when available
🌍 Geographic Redundancy: Distribute across regions
🔄 Smart Retries: Exponential backoff with configurable limits
📊 Failover Metrics: Track provider reliability
Use Cases
Production Applications: Ensure critical AI features never go down
Cost Optimization: Use expensive providers only when needed
Geographic Distribution: Serve users from nearest region
A/B Testing: Route traffic between providers for comparison
Compliance: Route EU traffic to GDPR-compliant providers
Quick Start
Basic Failover Configuration
Test Failover
Failover Strategies
1. Priority-Based Failover (Recommended)
Try providers in priority order until one succeeds.
2. Condition-Based Routing
Route to specific providers based on request conditions.
Same priority: Both Mistral and OpenAI have priority 1, but conditions determine which one is used.
GDPR compliance: Route EU users to Mistral AI (European provider) for automatic GDPR compliance.
Regional routing: Non-EU users go to OpenAI. Multiple providers at same priority with mutually exclusive conditions.
Universal fallback: Google AI (priority 2) has no condition, so it's used if both priority 1 providers fail.
Pass routing metadata: Include
userRegionin metadata so conditions can access it for routing decisions.
3. Cost-Based Routing
Try cheaper providers first, fallback to premium providers.
4. Load-Balanced Failover
Combine load balancing with failover.
Retry Configuration
Exponential Backoff
Selective Retry
Retryable errors: Transient failures worth retrying. Network errors (ECONNREFUSED, ETIMEDOUT) and server issues (429, 5xx) often resolve on retry.
Non-retryable errors: Client-side errors that won't be fixed by retrying. Invalid requests (400), authentication failures (401), and authorization issues (403) require code changes.
Custom Retry Logic
Provider Health Checks
Active Health Monitoring
Circuit Breaker Pattern
Production Patterns
Pattern 1: High Availability Setup
Pattern 2: Cost-Optimized Failover
Pattern 3: Geographic Routing
Pattern 4: Model-Specific Failover
Monitoring and Metrics
Track Failover Events
Failover Metrics Dashboard
Best Practices
1. ✅ Always Configure Multiple Providers
2. ✅ Use Health Checks in Production
3. ✅ Implement Circuit Breakers
4. ✅ Monitor Failover Events
5. ✅ Test Failover Regularly
Troubleshooting
Issue 1: Failover Not Triggering
Problem: Requests fail without trying fallback providers.
Solution:
Issue 2: Too Many Retry Attempts
Problem: Requests take too long due to excessive retries.
Solution:
Issue 3: Circuit Breaker Stuck Open
Problem: Provider marked as failed even when healthy.
Solution:
Related Documentation
Feature Guides:
Provider Orchestration - Intelligent provider selection and routing
Regional Streaming - Region-specific failover strategies
Auto Evaluation - Validate failover quality
Enterprise Guides:
Load Balancing Guide - Distribution strategies
Cost Optimization - Reduce AI costs
Provider Setup - Provider configuration
Monitoring Guide - Observability and metrics
Additional Resources
NeurosLink AI GitHub - Source code
GitHub Discussions - Community support
Issues - Report bugs
Need Help? Join our GitHub Discussions or open an issue.
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