aptakube VS hnrss

Are you specifically looking for a free Kubernetes GUI?

If you’re open to commercial options, have a look at what Aptakube (https://aptakube.com) can do.

One feature that sets it apart from other UIs is connecting to multiple clusters simultaneously and seeing all resources in a single table.

Disclaimer: I’m the author

During my previous job, when we were migrating to Kubernetes I couldn’t really find a GUI app that I liked, and most importantly, that could connect to multiple clusters simultaneously. We had 6 clusters and having to switch context constantly was annoying

I ended up building one [1] to use myself, shared with a few people and they loved it. I asked if they’d pay for it and to my surprise, a lot of people said yes. I’ve put up a website and a “pre-order” button with a regressive monthly discount. Sales were going up month after month, and a few months later I decided to quit my job to go all in on it.

Today, I’m averaging on ~€5k/mo from this app, but I’m still doing some part time freelancing, as well as building other products that are not as successful, but are making >€1000/mo

The latest one is open source, privacy friendly analytics for apps [2] that I’m still very actively working on. This is my current “side project” as the previous side project became my main job :)

There’s also an open source upvote site [3] that I haven’t had much time to work on lately, but still generating $$ monthly.

[1] https://aptakube.com

In case you're into Kubernetes, check out Aptakube, a Kubernetes Desktop Client built with Tauri 😊

Aptakube is GUI application for Kubernetes that uses the same Kubeconfig files we mentioned above and can connect to multiple clusters at the same time. It essentially presents all your Kubernetes resources as if it was a single clusters. We invite you to try it out free today 😊

I have two projects, combined doing ~€1500/mo

https://fider.io - an open source alternative to UserVoice. I started this one 6 years ago to learn Go and React. I’ve seen thousands of instances out there being self hosted, so I started a cloud hosting to those who don’t want to manage it themselves.

https://aptakube.com - Desktop Client for Kubernetes. This is very recent, launch was 2 weeks ago, so it’s only starting to get some traction now.

I’m leaving my job to go full time indie hacker now, wish me luck!

I'm giving a shot on https://aptakube.com. not OSS, but so far has been a great alternative to lens and k9s. The guy behind it made a thread here a while ago.

Thanks again for sharing your feedback! In case you have more, you can drop them here or add them to https://github.com/aptakube/aptakube

That’s interesting.

I have predictive models that can predict if a headline (w/o the rest of the article and not considering the URL) will (a) get more than 10 votes and (b) if it does get more than 10 votes will the votes/comments ratio be more than 2 (which is roughly average)

The first model gets a ROC-AUC (see https://scikit-learn.org/stable/modules/generated/sklearn.me...) in the low 60’s (not good, the second model gets in the low 70’s (actually pretty good though it is a heat seeking missile for clickbait headlines) and my latest content-based recommender for RSS items gets almost 80. (I saw a paper that one system at TikTok gets about 85)

To do all that you need about 10,000 headlines and don’t get a lot of benefit from having more than 100,000. The ceilings on performance have more to do with the nature of the problem rather than my models: the same article can get submitted twice and get 0 votes one time and 200 the other time so it can never be as accurate as “is this an article about galactic astronomy?”

I had it ingest the HN comments firehose and found the amount of articles was overwhelming, my YOShInOn RSS reader now ingests the “best comments” from

https://hnrss.github.io/

together with 110 other feeds and actually I like the comments it picks out a lot. Now that the system is adding about 3000 items per day it might be able to handle a big feed like the comments firehose since now those comments are diluted with so many quality articles. For a problem like that you might want a two-score system with: (i) is it relevant? (something I like) and (ii) is it popular? (like Google’s PageRank)

I think you could make a model that compares comments in the best comments feed with other comments. I have tried formulating the problems above as regression problems where I try to predict the actual score and it does not work well because of the uncertainty problem but formulated as a classification problem for a score over a threshold it is easy to make a well-calibrated model that tells you “this article has a 20% chance of frontpaging” which is about the best anyone can do.

Subscribe via rss, so you can scratch the curiosity itch and each the FOMO, without coming to the site all the time and looking over the same things 20 times?

https://hnrss.github.io/

https://news.ycombinator.com/item?id=9491978

and this https://hnrss.github.io/

ps i’m ok with some % of false positives, but hopefully a sprinkle of OpenAI could keep that magically low?

thanks

It sounds interesting but I use https://hnrss.github.io/

Unless it had most of the features of hnrss.org I would not be able to use it.

Perhaps you could pivot your approach and submit a PR to hnrss for the feature?

Looks like there's an unmerged PR on the third-party hnrss project that would add this: https://github.com/hnrss/hnrss/pull/84

Check out below link to get a more customized, topic wise rss feeds.

https://hnrss.github.io/