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akamai
boomerang
JavaScript2019–2021
akamai / boomerang

boomerang

End user oriented web performance testing and beaconing

2Distinct people
4Mentions
0Explicit recommenders
1.9KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

End user oriented web performance testing and beaconing

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 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM 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 month4 dated mentions

Observed mentions: 2019-12-17 16:19:45 UTC to 2021-01-27 18:22:34 UTC.

012019-12-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsDec 20192020-01-01 00:00:00 UTC to 2020-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-02-01 00:00:00 UTC to 2020-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-03-01 00:00:00 UTC to 2020-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-04-01 00:00:00 UTC to 2020-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-05-01 00:00:00 UTC to 2020-06-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2020-06-01 00:00:00 UTC to 2020-07-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsJun 20202020-07-01 00:00:00 UTC to 2020-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-08-01 00:00:00 UTC to 2020-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-09-01 00:00:00 UTC to 2020-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-10-01 00:00:00 UTC to 2020-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-11-01 00:00:00 UTC to 2020-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-12-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-01-01 00:00:00 UTC to 2021-02-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsJan 2021

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
Dec 20192019-12-01 00:00:00 UTC2020-01-01 00:00:00 UTC101
Jan 20202020-01-01 00:00:00 UTC2020-02-01 00:00:00 UTC000
Feb 20202020-02-01 00:00:00 UTC2020-03-01 00:00:00 UTC000
Mar 20202020-03-01 00:00:00 UTC2020-04-01 00:00:00 UTC000
Apr 20202020-04-01 00:00:00 UTC2020-05-01 00:00:00 UTC000
May 20202020-05-01 00:00:00 UTC2020-06-01 00:00:00 UTC101
Jun 20202020-06-01 00:00:00 UTC2020-07-01 00:00:00 UTC101
Jul 20202020-07-01 00:00:00 UTC2020-08-01 00:00:00 UTC000
Aug 20202020-08-01 00:00:00 UTC2020-09-01 00:00:00 UTC000
Sep 20202020-09-01 00:00:00 UTC2020-10-01 00:00:00 UTC000
Oct 20202020-10-01 00:00:00 UTC2020-11-01 00:00:00 UTC000
Nov 20202020-11-01 00:00:00 UTC2020-12-01 00:00:00 UTC000
Dec 20202020-12-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
Jan 20212021-01-01 00:00:00 UTC2021-02-01 00:00:00 UTC101

What Hacker News says

4 sources
The simplest way to measure impact on users would be to just use boomerang which gets you all of this out of the box: https://github.com/akamai/boomerang To do it yourself, you need a combination of PainTiming and measuring LongTasks or study the periodicity of setInterval/requestAnimationFrame The above works for synthetic as well as real users. If you're able to measure real users directly, then you'd also want to look at Input Delays, Rage Clicks, Dead Clicks, Missed Clicks, Scroll Jank.
In We rendered a million web pages to find out what makes the web slow
I've recently been pondering whether to create a log receiver that will produce Prometheus metrics as well as logs for Loki. Why? Because there are several open source projects that if joined up in a relatively simple way would provide a full RUM / Analytics solution. For collecting the analytics: Akamai Boomerang, which is a descendant of Yahoo tooling https://github.com/akamai/boomerang and BSD licensed Then insert a collector that will produce Prometheus metrics and write log lines. The metrics will provide the timing information and in many ways will be richer than Google Analytics, and the log lines will provide the potentially high cardinality of string based data like user agents, URIs, etc and Grafana supports PromQL queries against logs such that you can gain metrics from the log lines too. Then add in a free Grafana Cloud https:
Read the rest
//grafana.com/products/cloud/ and configure Prometheus to scrape from the collector, and Loki to consume the logs. This is an end-to-end cloud hosted RUM / Analytics solution that for a single user would be free and one can even add alerting. The missing link is that collector, to consume the Boomerang output and produce Prometheus metrics and log lines for Loki. All of this is open source and can be self hosted, the only piece you would have to host today would be that custom collector to receive the Boomerang requests.
In Lightweight Alternatives to Google Analytics
Recently I've been thinking there must be a better way. I want rich insights from a session angle, but I mostly want to know performance timings and what my end users experience. How can I improve my web apps to increase engagement, and where are the issues on my website as it's seen from a user's perspective. My current thought (not yet implemented) is to take several existing things and to glue them together. 1. Boomerang https://github.com/akamai/boomerang is a Real User Monitoring JS include that is open source and comes from the Yahoo and Akamai performance teams 2. Grafana Cloud https://grafana.com/products/cloud/ has Loki and Prometheus for log consumption and metrics respectively and now has a self serve plan of $50 per month (but I think this is reasonable as the data storage is managed for you and you could run many instances of
Read the rest
RUM monitoring via this to spread the cost reasonably) 3. Write a simple server to receive the Boomerang requests, log each request received in full detail and structured. At the same time increment Prometheus metrics. Let Loki and Prometheus then put that into Grafana Cloud. Then it's just a case of using Grafana to configure a dashboard to offer whatever views, alerts, analysis that you want. The thing I like about this is that no matter what the website the inputs are the same (whatever Boomerang provides), and so the dashboards are inherently shareable so that others can use them.
In My Messy Analytics Breakup

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