Speak Production Checklist

Speak Production Checklist

Overview

Production readiness checklist for Speak language learning integrations: auth, audio pipeline, monitoring, and compliance.

Prerequisites

• Completed speak-install-auth setup
• Valid API credentials configured
• ffmpeg installed for audio processing

Instructions

Authentication

• API keys stored in secrets manager
• Key rotation schedule established (90 days)
• Separate keys for dev/​staging/​production
• Error handling for expired keys

Audio Pipeline

• Audio preprocessor converts to WAV 16kHz mono
• File size validation (< 25MB)
• Duration validation (0.5s - 60s)
• Background noise detection/​warning
• Fallback for unsupported audio formats

Rate Limiting & Performance

• Rate-limited client wrapper implemented
• Retry logic with exponential backoff on 429
• Request queue for batch assessments
• Response caching where appropriate

Monitoring & Alerting

• API response time tracking
• Error rate monitoring (target < 1%)
• Rate limit hit tracking
• Assessment score distribution monitoring
• Session completion rate tracking

Compliance

• Student data privacy policy documented
• Audio data retention policy implemented
• COPPA compliance verified (if applicable)
• FERPA compliance verified (if educational)
• GDPR data processing agreement (if EU users)

Verification Script

#!/​bin/​bash
set -euo pipefail
echo "Speak Production Readiness"
curl -sf -H "Authorization: Bearer $SPEAK_API_KEY" \
  https://api.speak.com/​v1/​health | jq '.status'
echo "  Auth: PASS"
ffmpeg -version > /​dev/​null 2>&1 && echo "  ffmpeg: PASS" || echo "  ffmpeg: FAIL"
echo "Checks complete."

Output

• Checklist implementation complete
• Speak API integration verified
• Production-ready patterns applied

Error Handling

Resources

• Speak Website
• OpenAI Realtime API
• Speak GPT-4 Blog

Next Steps

See speak-prod-checklist for production readiness.

Examples

Basic: Apply prod checklist with default configuration for a standard Speak integration.

Advanced: Customize for production with error recovery, monitoring, and team-specific requirements.