The traffic hits in waves. Requests surge from thousands of processes, most without a human behind them. Bots, microservices, edge functions. You need a system that can handle it all without hesitation. That’s where a Non-Human Identities Load Balancer comes in.
A Non-Human Identities Load Balancer is built to route and scale requests from machine-to-machine workflows. Unlike traditional load balancers focused on human web sessions, it optimizes for API calls, automated tasks, ephemeral compute, and serverless triggers. It detects, classifies, and directs traffic from these identities with low latency and predictable performance.
Key features include identity awareness. Non-human clients—whether a CI/CD runner, IoT device, or AI agent—often have different authentication flows and throughput patterns. This load balancer assigns rules based on origin type, token scope, or certificate fingerprint. It supports mutual TLS, signed requests, and dynamic token rotation.
Scalability is horizontal and adaptive. Traffic distribution isn’t just round-robin—it’s computed by resource demand, job priority, and execution context. The Non-Human Identities Load Balancer can integrate with service meshes and API gateways, feeding metrics into autoscaling pipelines. It handles sudden spikes without sacrificing SLA.