fast network membership check #2625
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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.
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Related: kubernetes/kubernetes#25533 |
2opremio
approved these changes
Jun 21, 2017
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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.
In my benchmarks this change improves topology rendering performance of Weave Cloud production reports by 3-7%.