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HubSpot
Singularity
Java2015–2021
HubSpot / Singularity

Singularity

Scheduler (HTTP API and webapp) for running Mesos tasks—long running processes, one-off tasks, and scheduled jobs. #hubspot-open-source

4Distinct people
5Mentions
0Explicit recommenders
828GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Scheduler (HTTP API and webapp) for running Mesos tasks—long running processes, one-off tasks, and scheduled jobs. #hubspot-open-source

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, 5:58:02 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 year5 dated mentions

Observed mentions: 2015-08-18 22:15:23 UTC to 2021-04-06 17:50:17 UTC.

0122015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments20152016-01-01 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): 1 mentions; 0 submissions, 1 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20182019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 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 2022-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2021

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
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC202
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 UTC101
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC000
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC101

What Hacker News says

1 sources
[Copying my reply from reddit] I can give you some background on the way we structure things in case it's helpful. We use GitHub for our open-source projects, GitHub:Enterprise for our internal code, and our engineering team has about 300 engineers. Each project or feature usually lives in its own repository, and is split into a number of Maven modules. Using the maven-snapshot-accelerator ( https://github.com/HubSpot/maven-snapshot-accelerator ) as an example, it's roughly 1,000 lines of code split into 6 Maven modules (representing a small percentage of what my team owns). There's the root pom which just aggregates the other modules, a core module that contains the POJOs, a REST API module that uses the POJOs, a client module which uses the POJOs to hit the REST API, a module for the maven plugin, and a module for the maven extension. I
Read the rest
f this was an internal project, it might also have supporting Hadoop jobs, Kafka workers, Spark jobs, etc. depending on how the system was designed. Each of these would usually live in a separate Maven module. I'm not sure how much thought we gave to splitting into Maven modules along these lines, it just kind of seemed natural to us. It also has a few benefits compared to larger modules: - The dependency trees are smaller, because you're pulling in a more focused set of libraries rather than the kitchen sink - Our build infrastructure only builds what has changed when you push a commit, but it can only do this at Maven module granularity. So by splitting things up this way, pushing a change to your kafka workers won't rebuild your Spark or Hadoop jobs. Using one of our larger open-source projects as an example, Singularity ( https://github.com/HubSpot/Singularity ) is split into 15 Maven modules (and represents maybe a third to a half of what that team is responsible for). Snapshots vs. versions is a whole different topic and probably deserving of its own blog post. More generally, whether we should bend our workflow to the tools or bend the tools to our workflow is a constant tension and something we're always thinking about, so feedback is always appreciated.
In Need for Speed: Accelerating Maven Snapshots

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