Imported from jeremylongshore/tons-of-skills-marketplace (plugins/saas-packs/mistral-pack/skills/mistral-prod-checklist/SKILL.md). Install upstream with npx skills add jeremylongshore/tons-of-skills-marketplace --skill mistral-prod-checklist. Copyright stays with the author (MIT).

Mistral AI Production Checklist

Overview

Complete checklist for deploying Mistral AI integrations to production. Covers credential management, code quality gates, health endpoints, circuit breaker resilience, gradual rollout, and rollback procedures.

Prerequisites

• Staging environment tested and verified
• Production API keys from La Plateforme
• Deployment pipeline (CI/CD) configured
• Monitoring and alerting ready (see mistral-observability)

Instructions

Step 1: Pre-Deployment Verification

Credentials

• Production API key stored in secret manager (never in env files or code)
• Key tested with curl -H "Authorization: Bearer $KEY" https://api.mistral.ai/v1/models
• Key has appropriate model access scope
• Fallback key available for rotation

Code Quality

• npm run typecheck passes
• npm test passes (unit + integration)
• No hardcoded keys: grep -r "MISTRAL_API_KEY\|sk-" src/ --include="*.ts"
• Error handling covers 401, 429, 500+ status codes
• Rate limiting/backoff implemented
• Logging excludes message content and API keys

Model Configuration

• Using versioned model IDs or -latest aliases intentionally
• maxTokens set to prevent runaway costs
• temperature set appropriately (0 for deterministic, 0.7 for creative)
• Token budget alerts configured

Step 2: Health Check Endpoint

import { Mistral } from '@mistralai/mistralai';

interface HealthStatus {
  status: 'healthy' | 'degraded' | 'unhealthy';
  provider: 'mistral';
  latencyMs: number;
  model?: string;
  error?: string;
}

export async function checkHealth(): Promise<HealthStatus> {
  const start = performance.now();
  try {
    const client = new Mistral({ apiKey: process.env.MISTRAL_API_KEY! });
    const models = await client.models.list();
    const latencyMs = Math.round(performance.now() - start);

    return {
      status: latencyMs > 5000 ? 'degraded' : 'healthy',
      provider: 'mistral',
      latencyMs,
      model: models.data?.[0]?.id,
    };
  } catch (error: any) {
    return {
      status: 'unhealthy',
      provider: 'mistral',
      latencyMs: Math.round(performance.now() - start),
      error: error.message,
    };
  }
}

// Express route
app.get('/health', async (req, res) => {
  const health = await checkHealth();
  res.status(health.status === 'unhealthy' ? 503 : 200).json(health);
});

Step 3: Circuit Breaker

class MistralCircuitBreaker {
  private failures = 0;
  private lastFailure = 0;
  private state: 'closed' | 'open' | 'half-open' = 'closed';
  private readonly threshold = 5;
  private readonly resetMs = 60_000;

  async execute<T>(fn: () => Promise<T>, fallback?: () => T): Promise<T> {
    if (this.state === 'open') {
      if (Date.now() - this.lastFailure > this.resetMs) {
        this.state = 'half-open';
      } else if (fallback) {
        return fallback();
      } else {
        throw new Error('Circuit breaker open — Mistral unavailable');
      }
    }

    try {
      const result = await fn();
      if (this.state === 'half-open') {
        this.state = 'closed';
        this.failures = 0;
      }
      return result;
    } catch (error: any) {
      if (error.status >= 500 || error.status === 429) {
        this.failures++;
        this.lastFailure = Date.now();
        if (this.failures >= this.threshold) {
          this.state = 'open';
        }
      }
      throw error;
    }
  }
}

Step 4: Gradual Rollout

set -euo pipefail
# Deploy to canary (10% traffic)
kubectl set image deployment/mistral-app app=mistral-app:v2
kubectl rollout pause deployment/mistral-app

# Monitor for 10 minutes
echo "Monitoring canary..."
for i in $(seq 1 10); do
  curl -sf https://yourapp.com/health | jq '.services.mistral'
  sleep 60
done

# If healthy, resume rollout
kubectl rollout resume deployment/mistral-app
kubectl rollout status deployment/mistral-app

Step 5: Post-Deployment Verification

set -euo pipefail
# 1. Health check
curl -sf https://yourapp.com/health | jq '.'

# 2. Smoke test
curl -X POST https://yourapp.com/api/chat \
  -H "Content-Type: application/json" \
  -d '{"messages":[{"role":"user","content":"ping"}]}' | jq '.choices[0].message.content'

# 3. Check error rate in monitoring
echo "Check Grafana/Datadog for mistral_errors_total"

Step 6: Emergency Rollback

set -euo pipefail
# Immediate rollback
kubectl rollout undo deployment/mistral-app
kubectl rollout status deployment/mistral-app

# Verify
curl -sf https://yourapp.com/health | jq '.'

Alert Configuration

Documentation Requirements

• Incident runbook created (see mistral-incident-runbook)
• Key rotation procedure documented
• Rollback procedure tested
• On-call escalation path defined
• API usage limits documented

Output

• Production deployment with verified credentials
• Health check endpoint with latency monitoring
• Circuit breaker for graceful degradation
• Gradual rollout procedure
• Emergency rollback tested

Error Handling

Examples

Gate a canary before resuming rollout

Pause the deployment, run the health and chat smoke tests against the canary revision, and inspect the error-rate and auth-failure panels for the defined observation period. Resume only when the checks hold; otherwise execute kubectl rollout undo and keep the incident record linked to the failed revision.

Resources

• Mistral AI Status
• Mistral AI Console
• Rate Limits