Information Technology Reference
In-Depth Information
This table shows what the control scenario was and the improvement that was made. The
percentage increase in performance is shown for each prefix count tested. A number of
combinations were performed to show the relationship between the various optimizations.
The control time is the amount of time the test took to run with the optimization set defined
in the Control column. The improvement time is the amount of time the test took to run with
the optimization set defined in the Improvement column. The improvement percentages
were derived by dividing the delta between the control time and improvement time by the
control time. This reflects the improvement based on the control time.
Summary
This chapter covered two major aspects of BGP performance tuning: BGP convergence
tuning and BGP network performance turning. The first section covered the major features
that dramatically improve BGP convergence. The case study provided empirical evidence
to complement the conceptual explanation.
The section on BGP network tuning focused on reducing the scope of network-affecting
events and reducing the amount of BGP information advertised.
The challenge of BGP performance tuning is ongoing as networks increase in both node
count and prefix count. The sheer amount of information involved in large BGP networks
provides many areas for optimization that, if not capitalized on, can result in network-wide
meltdowns. Deploying BGP convergence optimizations should be considered a common
best practice for all BGP networks.
