Going to Production
A comprehensive checklist for deploying your Avatarium integration to production.
⚠️
Don't skip the checklist! Production issues are 10x harder to fix than pre-launch issues.
Pre-Launch Checklist
Configuration
- API Key: Using live key (
av_live_*), not test key - Environment Variables: All secrets in secure environment vars
- BYOK Keys: Production provider keys configured
- Domain Allowlist: Production domain added in dashboard
Security
- API Key Protection: Key not exposed in client-side code
- CORS: Configured for production domain only
- Rate Limiting: Client-side throttling implemented
- Input Validation: User inputs sanitized
Performance
- CDN: Avatar assets served from CDN
- Lazy Loading: Avatar loads on demand, not on page load
- Error Boundaries: Graceful degradation on failures
- Streaming: Enabled for faster perceived response
Content
- System Prompt: Finalized and tested
- Knowledge Base: Uploaded and verified
- Fallback Responses: Defined for unknown questions
- Escalation Path: Human handoff configured
Monitoring
- Analytics: Dashboard tracking enabled
- Alerts: Budget alerts configured
- Error Tracking: Logging in place
- Uptime Monitoring: Health checks configured
Step-by-Step Launch Guide
Finalize Configuration
Ensure your production settings are locked in:
// production.config.ts
export const avatarConfig = {
apiKey: process.env.AVATARIUM_API_KEY,
avatarId: 'your-avatar-id',
environment: 'production',
// BYOK for cost control
byokAI: {
provider: 'groq',
apiKey: process.env.GROQ_API_KEY,
model: 'llama-3.1-70b-versatile',
},
// Production TTS
byokTTS: {
provider: 'google',
apiKey: process.env.GOOGLE_TTS_KEY,
},
// Analytics enabled
analytics: {
enabled: true,
trackConversations: true,
},
};Set Up Error Handling
Implement comprehensive error handling:
import { Avatar } from '@avatarium/react';
function ProductionAvatar() {
const [error, setError] = useState<Error | null>(null);
if (error) {
return <FallbackChat error={error} />;
}
return (
<ErrorBoundary
fallback={<FallbackChat />}
onError={(error) => {
reportError(error); // Send to logging service
setError(error);
}}
>
<Avatar
{...avatarConfig}
onError={(error) => {
if (error.code === 'RATE_LIMIT') {
showMessage('Please wait a moment before sending more messages.');
} else if (error.code === 'BUDGET_EXCEEDED') {
showContactSupport();
} else {
setError(error);
}
}}
/>
</ErrorBoundary>
);
}Configure Monitoring
Set up production monitoring:
// monitoring.ts
import { initAvatariumAnalytics } from '@avatarium/analytics';
initAvatariumAnalytics({
// Send events to your analytics service
onEvent: (event) => {
analytics.track(event.name, event.properties);
},
// Monitor performance
onPerformance: (metrics) => {
if (metrics.responseTime > 5000) {
alertOps('Slow avatar response', metrics);
}
},
// Track errors
onError: (error) => {
errorTracking.capture(error);
},
});Test in Staging
Before going live, test in a staging environment:
# Deploy to staging
npm run deploy:staging
# Run automated tests
npm run test:e2e
# Smoke test manually
# - Load avatar
# - Send test messages
# - Verify responses
# - Check analyticsStaged Rollout
Roll out gradually to catch issues early:
// feature-flags.ts
const ROLLOUT_PERCENTAGE = 10; // Start with 10%
function shouldShowAvatar(userId: string): boolean {
const hash = hashUserId(userId);
return (hash % 100) < ROLLOUT_PERCENTAGE;
}
// In your component
function App() {
const { userId } = useUser();
if (!shouldShowAvatar(userId)) {
return <LegacyChat />;
}
return <Avatar {...config} />;
}Monitor Launch
Watch key metrics during the first 24-48 hours:
| Metric | Target | Alert If |
|---|---|---|
| Error rate | <1% | >5% |
| Response time | <3s | >10s |
| User satisfaction | >4.0 | <3.0 |
| Session completion | >80% | <50% |
Scaling Considerations
Traffic Planning
| Expected Sessions | Tier | Recommendation |
|---|---|---|
| <1,000/month | Free or Infrastructure | Start here |
| 1,000-10,000/month | Professional | Good balance |
| 10,000-50,000/month | Business | Volume discounts |
| 50,000+/month | Enterprise | Contact sales |
Performance at Scale
// Implement connection pooling for high traffic
const avatarPool = createAvatarPool({
maxConnections: 100,
idleTimeout: 60000,
});
// Use session affinity for better caching
const session = await avatarPool.getSession(userId);Global Deployment
For international users, consider:
| Region | Recommendation |
|---|---|
| North America | Primary Avatarium region |
| Europe | Deploy on edge nodes closest to your users |
| Asia-Pacific | Consider edge caching |
Production Support
Support Escalation
| Issue Type | Response Time | Contact |
|---|---|---|
| P1 - Service Down | <1 hour | Emergency support |
| P2 - Degraded | <4 hours | Priority support |
| P3 - Bug | <24 hours | Standard support |
| P4 - Question | <48 hours | Standard support |
Getting Help
Community & Email Support
- Discord community for peer support
- Email: support@avatarium.ai
- Response within 48 hours
Included in: Free, Infrastructure
Backup & Recovery
What to Back Up
| Item | Frequency | Storage |
|---|---|---|
| System prompts | Every change | Version control |
| Knowledge base | Weekly | Cloud storage |
| Configuration | Every change | Version control |
| Analytics export | Monthly | Data warehouse |
Disaster Recovery
// Implement graceful fallback
const FALLBACK_RESPONSES = {
default: "I'm having trouble right now. Please try again or contact support.",
maintenance: "We're doing scheduled maintenance. Back in 30 minutes!",
overload: "High demand right now. Please wait a moment and try again.",
};
function handleAvatarFailure(error: Error): string {
switch (error.code) {
case 'SERVICE_UNAVAILABLE':
return FALLBACK_RESPONSES.maintenance;
case 'RATE_LIMIT':
return FALLBACK_RESPONSES.overload;
default:
return FALLBACK_RESPONSES.default;
}
}Post-Launch Operations
Daily Monitoring
- Check error rates
- Review user feedback
- Monitor response times
- Verify budget status
Weekly Tasks
- Review analytics dashboard
- Analyze top unanswered questions
- Update knowledge base if needed
- Check for product updates
Monthly Tasks
- Review and optimize system prompt
- Analyze cost efficiency
- Plan capacity for next month
- Team review of performance
Compliance & Privacy
Data Handling
| Data Type | Retention | Notes |
|---|---|---|
| Conversations | 30 days default | Configurable |
| Analytics | 90 days | Aggregated |
| User PII | As configured | See privacy policy |
Privacy Configuration
<Avatar
privacy={{
// Don't store conversation content
storeConversations: false,
// Anonymize analytics
anonymizeAnalytics: true,
// Require consent before starting
requireConsent: true,
}}
onConsentRequired={(accept) => {
showConsentModal(accept);
}}
/>Required Disclosures
Add to your privacy policy:
- AI-powered chat assistant in use
- Data processing by Avatarium
- User data retention periods
- User rights (access, deletion)
Launch Checklist Summary
Day Before Launch
- All tests passing
- Staging environment verified
- Monitoring configured
- Team briefed on launch plan
- Rollback plan documented
Launch Day
- Deploy to production
- Enable for initial user segment
- Monitor dashboards actively
- Be ready for quick fixes
- Communicate with stakeholders
Post-Launch
- Verify metrics collection
- Review initial user feedback
- Address any immediate issues
- Plan gradual rollout expansion
- Document lessons learned
Next Steps
- Measuring Success - Track your ROI
- Best Practices - Optimization tips
- Analytics Guide - Deep dive into metrics