From dc817056b7e7aabfd8aa27b0a9c57dc8478d2689 Mon Sep 17 00:00:00 2001 From: Jonah Duckles Date: Wed, 15 Jul 2026 12:36:15 +1200 Subject: [PATCH] Update so tcipifo article is not live on kb --- src/content/articles/tcpinfo-snapshot-analysis.md | 1 + 1 file changed, 1 insertion(+) diff --git a/src/content/articles/tcpinfo-snapshot-analysis.md b/src/content/articles/tcpinfo-snapshot-analysis.md index 0c74e6b..46f1292 100644 --- a/src/content/articles/tcpinfo-snapshot-analysis.md +++ b/src/content/articles/tcpinfo-snapshot-analysis.md @@ -3,6 +3,7 @@ title: "Analyzing TCP INFO Snapshots: Data Characteristics and Research Patterns description: A practical guide to M-Lab's TCP INFO snapshot data in BigQuery — how snapshots are collected and thinned, why most rows are noise, how to filter to real tests, and how to use RTT variance data to study latency-sensitive applications like VoIP. tags: [research, data-access] difficulty: intermediate +published: false --- M-Lab's TCP INFO sidecar records a time series of kernel TCP socket statistics for every connection on the platform. The BigQuery table is large, heterogeneous, and counterintuitive until you understand how collection and storage work. This article explains the mechanics, the quirks, and the correct patterns for research use.