The rendering code checks whether endpoint IPs are part of
cluster-local networks. Due to the prevalence of endpoints - medium
sized reports can contain many thousands of endpoints - this is
performance critical. Alas the existing code performs the check via a
linear scan of a list of networks. That is slow when there are more
than a few, which will be the case in the context of k8s, since there
the probes register service IPs as local /32 networks.
Here we change representation of the set of networks to a prefix
tree (aka trie), which is well-suited for IP network membership checks
since networks are in fact a bitstring prefixes.
The specific representation is a crit-bit tree, but that choice was
purely based on implementation convenience - the chosen library is the
only one I could find that directly supports IP networks.
The rendering code checks whether endpoint IPs are part of
cluster-local networks. Due to the prevalence of endpoints - medium
sized reports can contain many thousands of endpoints - this is
performance critical. Alas the existing code performs the check via a
linear scan of a list of networks. That is slow when there are more
than a few. Unfortunately in some common k8s network setups, e.g. on
AWS, a cluster can contain hundreds of networks, due to /32 networks
derived from interfaces with multiple IPs.
Here we change representation of the set of networks to a prefix
tree (aka trie), which is well-suited for IP network membership checks
since networks are in fact a bitstring prefixes.
The specific representation is a crit-bit tree, but that choice was
purely based on implementation convenience - the chosen library is the
only one I could find that directly supports IP networks.
