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goreplay
Go2013–2023
probelabs / goreplay

goreplay

GoReplay is an open-source tool for capturing and replaying live HTTP traffic into a test environment in order to continuously test your system with real data. It can be used to increase confidence in code deployments, configuration changes and infrastructure changes.

13Distinct people
17Mentions
1Explicit recommenders
19.3KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

GoReplay is an open-source tool for capturing and replaying live HTTP traffic into a test environment in order to continuously test your system with real data. It can be used to increase confidence in code deployments, configuration changes and infrastructure changes.

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

I love to see more activity in this area! I'm maintainer of GoReplay https://github.com/buger/goreplay and work in this area for the last 10 years. It is quite hard problem to…

LeonidBugaev used a recommendation phrase. One indexed comment matches. This is a phrase match, not a verdict.

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, 4:00:59 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 year17 dated mentions

Observed mentions: 2013-06-04 18:11:26 UTC to 2023-03-18 15:21:09 UTC.

012342013-01-01 00:00:00 UTC to 2014-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments20132014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20182019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 3 mentions; 3 submissions, 0 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2023

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
20132013-01-01 00:00:00 UTC2014-01-01 00:00:00 UTC110
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC101
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC312
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC101
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC000
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC101
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC330
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC404
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC101
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC110
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC101

What Hacker News says

1 sources
InfluxDB isn't as easy as it's sound to operate. Anything built on top of Postgres probably has year of knowledge to tune the db. but not much on InfluxDB. You are on your own. You cannot even easily upgrade InfluxDB, especially when you want to use some new feature such as enabling the TSI. When something is wrong, again, you're on the own. The question to InfluxDB HA isn't available as well. Yes, with all of that pain point, I'm still using InfluxDB. I even have to add in https://github.com/buger/goreplay to support replaying traffic to other instance during upgrade. I have to write a tool to re-read old data and import into new instance instead of using their own import/restore. Many gotcha with InfluxDB, hard to explain to dev not using high cardinality for tag, or not using too many tag. For example, people get used to `tag` concept
Read the rest
of `fluentd` and put stuff like user id, device id into tag... I want to log slow query time, now, I cannot use whole query as tag because of very high cardinality. However, I kept using InfluxDB. I want to support it so we have something better than Postgres. I'm sick of SQL query(personaly) and I would like for Flux to be successful. Similar to MongoDB, it's bad years ago but very good nowadays. I guess same thing will happen with InfluxDB. And indeed, they do improve over the year. Similar to how we use Ruby vs C. It's about productivity. And despite of above pain points, I always find a way to solve them eventually. And the tooling around InfluxDB is nice, especially Grafana.
In TimescaleDB vs. InfluxDB: built differently for time-series data

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