Docs // Latency_Budgets
Bending
Time.
How Sudarshan Ai simulates real-world latency budgets to optimize your global infrastructure footprint.
M/M/1 Queue Simulation
Our engine doesn't just look at distance; it applies formal queuing theory to calculate P99 latencies under various load conditions. We simulate resource saturation, context-switching overhead, and network hop latency.
// Simulation Parameters:
λ (Arrival Rate) = 1.2k req/sec
μ (Service Rate) = 2.0k req/sec
ρ (Utilization) = 0.6
E[W] (Expected Wait) = 0.75ms
λ (Arrival Rate) = 1.2k req/sec
μ (Service Rate) = 2.0k req/sec
ρ (Utilization) = 0.6
E[W] (Expected Wait) = 0.75ms
Regional Latency
Predicted P50/P99 between all global cloud regions.
Request Path
Visualizing every hop from Edge to Core Database.
Budget Alerts
Automated warnings when synthesis hits theoretical limits.