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Ondřej Surý <ondrej@isc.org>
Internet Systems Consortium
2024-05-21
Measuring DNS Latency
DNS Performance Metrics (quick intro) Measuring DNS Latency
• Performance under normal conditions
‣
• The data is right-skewed
‣ The usual descriptive statistics are useless (average, mean, …)
‣ Most of the queries are answered very quickly
‣ In fact, 95% of the queries are answered under 2 milliseconds
‣ The tails makes it interesting
Ondřej Surý <ondrej@isc.org> 2024-05-21 1 / 8
Logarithmic Percentile Histogram Measuring DNS Latency
Ondřej Surý <ondrej@isc.org> 2024-05-21 2 / 8
Logarithmic Percentile Histogram Measuring DNS Latency
• Both axes are logarithmic
‣ x-axis: slowest percentile
‣ y-axis: average latency
• It makes the tail more visible
• Variant of Complementary Cumulative Distribution Function
• Very robust, can be used for monitoring (1% slowest percentile)
• Introduced by the good folks at PowerDNS
See more: https://blog.powerdns.com/2017/11/02/dns-performance-
metrics-the-logarithmic-percentile-histogram
Ondřej Surý <ondrej@isc.org> 2024-05-21 3 / 8
Compare DNS Latencies
DNS Performance for Developers Compare DNS Latencies
• Comparing two branches of BIND 9
‣ Did we improve the code?
‣ Did we made things worse?
‣ Currently, we compare the graphs by looking at them;
‣ And then running more tests;
‣ And then some wishful thinking…
• Sending thanks to Python’s numpy and scipy developers!
Ondřej Surý <ondrej@isc.org> 2024-05-21 4 / 8
Pick the right statistics Compare DNS Latencies
• The distribution is not normal
• Non-parametrical test then?
‣ Kolmogorov-Smirnov test didn’t really work
• Normalize the data?
‣ Box Cox Transformation didn’t really work
• Maybe look only at the tail then?
Ondřej Surý <ondrej@isc.org> 2024-05-21 5 / 8
Looking at the tail Compare DNS Latencies
• Pick the 95% (99%) percentile complement
‣ Either return the lowest bucket needed for 5% of responses
‣ Or count the answers in (1.9-2.0 second buckets)
• Have at least 3 runs for each group
• Yay! The data are normal and the group variances are equal
‣ Shapiro-Wilk test
– first group (𝑊 = 0.905, 𝑝 = 0.436)
– second group (𝑊 = 0.970, 𝑝 = 0.874)
‣ Brown-Forsyth test (𝐹 = 0.070, 𝑝 = 0.798)
Ondřej Surý <ondrej@isc.org> 2024-05-21 6 / 8
Parametrical test (ANOVA) Compare DNS Latencies
• We can test more than two branches
• One-way ANOVA reports difference between branches
‣ 𝐹 = 9244.090, 𝑝 < .001
• Two-sample T-Test (for confirmation)
‣ 𝑇 = −96.146, 𝑝 < .001
Ondřej Surý <ondrej@isc.org> 2024-05-21 7 / 8
More ideas?
Other tests? More ideas?
• Is this even correct? Or am I crazy? (I’m not a statistician)
• Can we just compare two data sets (1x baseline with 1x branch)?
• Can we use the full (right-skewed) population?
• Are there any other non-parametrical tests I can try/use?
• Are there any other suitable statistical methods?
• Is this useful for other Internet measurements?
Ondřej Surý <ondrej@isc.org> 2024-05-21 8 / 8
Thank you!

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Statistical Analysis of DNS Latencies.pdf

  • 1. Ondřej Surý <ondrej@isc.org> Internet Systems Consortium 2024-05-21
  • 3. DNS Performance Metrics (quick intro) Measuring DNS Latency • Performance under normal conditions ‣ • The data is right-skewed ‣ The usual descriptive statistics are useless (average, mean, …) ‣ Most of the queries are answered very quickly ‣ In fact, 95% of the queries are answered under 2 milliseconds ‣ The tails makes it interesting Ondřej Surý <ondrej@isc.org> 2024-05-21 1 / 8
  • 4. Logarithmic Percentile Histogram Measuring DNS Latency Ondřej Surý <ondrej@isc.org> 2024-05-21 2 / 8
  • 5. Logarithmic Percentile Histogram Measuring DNS Latency • Both axes are logarithmic ‣ x-axis: slowest percentile ‣ y-axis: average latency • It makes the tail more visible • Variant of Complementary Cumulative Distribution Function • Very robust, can be used for monitoring (1% slowest percentile) • Introduced by the good folks at PowerDNS See more: https://blog.powerdns.com/2017/11/02/dns-performance- metrics-the-logarithmic-percentile-histogram Ondřej Surý <ondrej@isc.org> 2024-05-21 3 / 8
  • 7. DNS Performance for Developers Compare DNS Latencies • Comparing two branches of BIND 9 ‣ Did we improve the code? ‣ Did we made things worse? ‣ Currently, we compare the graphs by looking at them; ‣ And then running more tests; ‣ And then some wishful thinking… • Sending thanks to Python’s numpy and scipy developers! Ondřej Surý <ondrej@isc.org> 2024-05-21 4 / 8
  • 8. Pick the right statistics Compare DNS Latencies • The distribution is not normal • Non-parametrical test then? ‣ Kolmogorov-Smirnov test didn’t really work • Normalize the data? ‣ Box Cox Transformation didn’t really work • Maybe look only at the tail then? Ondřej Surý <ondrej@isc.org> 2024-05-21 5 / 8
  • 9. Looking at the tail Compare DNS Latencies • Pick the 95% (99%) percentile complement ‣ Either return the lowest bucket needed for 5% of responses ‣ Or count the answers in (1.9-2.0 second buckets) • Have at least 3 runs for each group • Yay! The data are normal and the group variances are equal ‣ Shapiro-Wilk test – first group (𝑊 = 0.905, 𝑝 = 0.436) – second group (𝑊 = 0.970, 𝑝 = 0.874) ‣ Brown-Forsyth test (𝐹 = 0.070, 𝑝 = 0.798) Ondřej Surý <ondrej@isc.org> 2024-05-21 6 / 8
  • 10. Parametrical test (ANOVA) Compare DNS Latencies • We can test more than two branches • One-way ANOVA reports difference between branches ‣ 𝐹 = 9244.090, 𝑝 < .001 • Two-sample T-Test (for confirmation) ‣ 𝑇 = −96.146, 𝑝 < .001 Ondřej Surý <ondrej@isc.org> 2024-05-21 7 / 8
  • 12. Other tests? More ideas? • Is this even correct? Or am I crazy? (I’m not a statistician) • Can we just compare two data sets (1x baseline with 1x branch)? • Can we use the full (right-skewed) population? • Are there any other non-parametrical tests I can try/use? • Are there any other suitable statistical methods? • Is this useful for other Internet measurements? Ondřej Surý <ondrej@isc.org> 2024-05-21 8 / 8