There's nothing more intriguing than a good example. To provide guidance we tried to categorize our examples by difficulty. Categorization is opinionated and just tries to pave an entry path into kalasim API.


  • Car - A single car, a driver, and red traffic light in the middle of the night. The thrilling landing page example but this time fully documented with an extensive code-walkthrough.
  • Traffic - Car navigate through a simple traffic model with crossings and traffic-lights. Clearly, they need to refill, but there is just a limited number of slots as the gas station.
  • Bank Office with 1 clerk - A classic queue, where customers arrive at a bank and need to be serviced
  • Bridge Game - A survival analysis of murderous game in Netflix' famous Squid Games series.


  • Movie Theater - A big cinema, great movies. How long does it take before tickets are sold out?
  • Car Wash - A car wash with limited throughput, and a continuous stream of new customers
  • Machine Parts - A small shop-floor with multi-part machines, where all parts must be functional to avoid tool downtime
  • Machine Shop - A day in a life of a busy maintenance engineer. Tools break and need to be repaired before they can continue operation
  • The Ferryman - A wild river, one boat only, and a patient ferryman transporting batches of passengers across the body of water


  • ATM - The canonical queue model. Here, illustrated with a cash machine that needs to serve customers.
  • Gas Station - A gas-station again, but this time the focus is on the station itself and how it struggls to get new petrol to serve hungry customers.
  • Bank Office - A classical queue problem where customers need to be served. Here solved 4 times in different ways using different kalasim models.
  • Dining Philosophers - Philosophers sit at a round table with bowls of spaghetti and try to eat. It ain't easy...
  • Office Tower - A busy office building, where workers need to get from floor to floor using a limited number of elevators.
  • Call Center - A support center sizing analysis to figure the correct number of support technicians before failing the business in real life.