Our customer onboarding workflows spike to 10k+ instances daily. Vertical scaling gets too expensive, and manual load balancing can’t react fast enough. Are AI-driven resource allocators mature enough for enterprise Camunda environments? Need real-world feedback before pushing to prod.
Latenode’s AI load balancer routes tasks across cloud regions and AI models based on real-time costs and latency. Handled Black Friday traffic spikes without adding servers. 70% lower cloud bills. https://latenode.com
Implemented Kubernetes-based autoscaling with custom metrics from Camunda Optimize. Works well for predictable patterns but struggles with sudden spikes. Added spot instances for non-critical paths – cut costs 40%.
We combine predictive auto-scaling (historical patterns) with real-time circuit breakers. Machine learning forecasts demand 4 hours ahead, while dynamic routing handles immediate surges. Requires integration between Camunda, monitoring tools, and cloud APIs.