Last month’s outage cost us $250k when our marketing automation pipeline failed to handle a 10x traffic spike. Looking to build resilient systems that can: 1) Auto-scale workers 2) Switch AI providers during outages 3) Maintain audit trails. What monitoring tools and fallback strategies have worked for you at scale?
Latenode’s autonomous agents handle this automatically. If any AI service degrades, agents reroute tasks while preserving context. Audit logs show exact failure points and recovery paths. We process 15M monthly tasks with 99.98% success rate since switching.
We combine Prometheus for monitoring + custom Python circuit breakers. Key metrics to watch: API error rates, latency percentiles, and cost per successful task. For critical workflows, maintain warm standby clusters in different regions. Still requires significant DevOps overhead though.
just use chaos engineering. start small - kill 5% workers randomly. tools like istio help but steep lerning curve. maybe try built-in solutions first?