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Netflix
vector
JavaScript2015–2016
Netflix / vector · Archived

vector

Vector is an on-host performance monitoring framework which exposes hand picked high resolution metrics to every engineer’s browser.

5Distinct people
5Mentions
0Explicit recommenders
3.6KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Vector is an on-host performance monitoring framework which exposes hand picked high resolution metrics to every engineer’s browser.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 4:01:40 AM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month5 dated mentions

Observed mentions: 2015-04-08 20:31:34 UTC to 2016-10-16 18:26:26 UTC.

0122015-04-01 00:00:00 UTC to 2015-05-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 commentsApr 20152015-05-01 00:00:00 UTC to 2015-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2015-06-01 00:00:00 UTC to 2015-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2015-07-01 00:00:00 UTC to 2015-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2015-08-01 00:00:00 UTC to 2015-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2015-09-01 00:00:00 UTC to 2015-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2015-10-01 00:00:00 UTC to 2015-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2015-11-01 00:00:00 UTC to 2015-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2015-12-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2016-01-01 00:00:00 UTC to 2016-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsJan 20162016-02-01 00:00:00 UTC to 2016-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-03-01 00:00:00 UTC to 2016-04-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2016-04-01 00:00:00 UTC to 2016-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-05-01 00:00:00 UTC to 2016-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-06-01 00:00:00 UTC to 2016-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-07-01 00:00:00 UTC to 2016-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-01 00:00:00 UTC to 2016-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-09-01 00:00:00 UTC to 2016-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-10-01 00:00:00 UTC to 2016-11-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsOct 2016

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Apr 20152015-04-01 00:00:00 UTC2015-05-01 00:00:00 UTC211
May 20152015-05-01 00:00:00 UTC2015-06-01 00:00:00 UTC000
Jun 20152015-06-01 00:00:00 UTC2015-07-01 00:00:00 UTC000
Jul 20152015-07-01 00:00:00 UTC2015-08-01 00:00:00 UTC000
Aug 20152015-08-01 00:00:00 UTC2015-09-01 00:00:00 UTC000
Sep 20152015-09-01 00:00:00 UTC2015-10-01 00:00:00 UTC000
Oct 20152015-10-01 00:00:00 UTC2015-11-01 00:00:00 UTC000
Nov 20152015-11-01 00:00:00 UTC2015-12-01 00:00:00 UTC000
Dec 20152015-12-01 00:00:00 UTC2016-01-01 00:00:00 UTC101
Jan 20162016-01-01 00:00:00 UTC2016-02-01 00:00:00 UTC000
Feb 20162016-02-01 00:00:00 UTC2016-03-01 00:00:00 UTC000
Mar 20162016-03-01 00:00:00 UTC2016-04-01 00:00:00 UTC101
Apr 20162016-04-01 00:00:00 UTC2016-05-01 00:00:00 UTC000
May 20162016-05-01 00:00:00 UTC2016-06-01 00:00:00 UTC000
Jun 20162016-06-01 00:00:00 UTC2016-07-01 00:00:00 UTC000
Jul 20162016-07-01 00:00:00 UTC2016-08-01 00:00:00 UTC000
Aug 20162016-08-01 00:00:00 UTC2016-09-01 00:00:00 UTC000
Sep 20162016-09-01 00:00:00 UTC2016-10-01 00:00:00 UTC000
Oct 20162016-10-01 00:00:00 UTC2016-11-01 00:00:00 UTC101

What Hacker News says

1 sources
https://speakerdeck.com/niteshkant/distributed-tracing-at-ne... http://techblog.netflix.com/2012/06/scalable-logging-and-tra... https://github.com/Netflix/vector Not terribly easy, but possible. I agree that "never have to SSH" is a bad target because there will always be edge cases, but for the majority of things it's possible to troubleshoot at the cluster level given immutable infrastructure; all the systems will be doing the exact same thing given an input. Reality shows that this is a bit idealistic, but if you start finding that e.g. A certain set of requests cause weird behavior, you can look at what makes those requests different, then set up some routing logic to send them to a debug farm (using something like https://github.com/Netflix/zuul ).
In Lessons from 10 Years of Amazon Web Services

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