Abstract: Disclosed is a method for managing flow tables at a switch in a network. The method includes establishing a static rule to distribute a first flow to a first server and a second flow to a second server and monitoring a first load on the first server and a second load on a second server. When, based on the monitoring, the first server is running at capacity and the third flow is to be distributed to the first server according to the static rule, the method includes establishing an exception to the static rule to yield an exception rule, distributing the third flow to a third server with capacity according to the exception rule and storing a flow table for the third flow at a switch, wherein the switch does not store a static rule flow table for the static rule.

Abstract: Disclosed is a method for managing flow tables at a switch in a network. The method includes establishing a static rule to distribute a first flow to a first server and a second flow to a second server and monitoring a first load on the first server and a second load on a second server. When, based on the monitoring, the first server is running at capacity and the third flow is to be distributed to the first server according to the static rule, the method includes establishing an exception to the static rule to yield an exception rule, distributing the third flow to a third server with capacity according to the exception rule and storing a flow table for the third flow at a switch, wherein the switch does not store a static rule flow table for the static rule.

Abstract: Techniques are disclosed for determining a preferred hashing algorithm for load balancing physical interface utilization in a network device, such as a switch, configured with a port-channel architecture. While a current hashing algorithm is being applied to network traffic flows, a forwarding engine of the network device retrieves snapshot data of each flow and evaluates the flows against other hashing algorithms. The forwarding engine, for each hashing algorithm result, calculates statistical measures, such as mean, variance, and coefficient of variation. These measures are used to determine the preferred hashing algorithm to subsequently be applied. Once determined, the networking device may notify a user (e.g., a system administrator) of the algorithm.

Abstract: Techniques are disclosed for determining a preferred hashing algorithm for load balancing physical interface utilization in a network device, such as a switch, configured with a port-channel architecture. While a current hashing algorithm is being applied to network traffic flows, a forwarding engine of the network device retrieves snapshot data of each flow and evaluates the flows against other hashing algorithms. The forwarding engine, for each hashing algorithm result, calculates statistical measures, such as mean, variance, and coefficient of variation. These measures are used to determine the preferred hashing algorithm to subsequently be applied. Once determined, the networking device may notify a user (e.g., a system administrator) of the algorithm.