feedback VS QuestDB

no-one-left-behind[1] was not even a year ago, and yet the link on npm[2] explaining why it was removed is already broken. Classic JS ecosystem.

1: https://github.com/npm/feedback/discussions/858

2: https://www.npmjs.com/package/no-one-left-behind

I created a new discussion in the npm/feedback repo to share my idea. I also mentioned my idea in relevant discussions: npm scores, Weird search behavior with stats, and Improve search functionality on npmjs.com.

We encourage you to open a discussion if you have suggestions for how we can improve npm. You don't need to have a solution to the problem you are facing to kick off a discussion. We are hoping to foster productive and collaborative conversations, so please check out how to give good feedback if you want some guidance on how to kick off a successful discussion.

There is an ongoing discussion about 2FA and possible bandaids for this sort of problem in the npm community forum: https://github.com/npm/feedback/discussions/588

See - https://github.com/npm/feedback/discussions/191

Now there have been some discussions around to mitigate these things which might have gone side ways like https://npm.community/t/blacklist-entire-packages/9659/4 and https://github.com/npm/feedback/discussions/272. Of course there might be tools which you can use, such as running a commercial npm registry in proxy mode with blacklisting support. But what are the basic features you have as a developer that can be use to mitigate these things ?

This is likely the issue as npm 7 auto installs peer dependencies, which will fail on conflicting dependents.

If your data lacks uniform time intervals between consecutive entries, QuestDB offers a solution by allowing you to sample your data. After that, MindsDB facilitates creating, training, and deploying your time-series models.

If you're interested in that functionality or have any other feedback, please drop by our open source repository or community Slack and let us know.

QuestDB is a high-performance time series database with SQL analytics that can power through market data ingestion and analysis. It's open source and integrates well with the tools and languages you use. Check us out!

Looks like full keys are always compared if hash codes test equal, which is what I'd expect. For example: https://github.com/questdb/questdb/blob/master/core/src/main...

But of course, I want to run a QuestDB instance on my node, which uses two additional TCP ports for Influx Line Protocol (ILP) and Pgwire communication with the database. So how can I expose these extra ports on my node and route traffic to the QuestDB container running inside of k3s?

In this post, I will detail a way in which I recently used annotations while writing an operator for my company's product, QuestDB. Hopefully this will give you an idea of how you can incorporate annotations into your own operators to harness their full potential.

QuestDB is an open source, high performance time series database. With its massive ingestion throughput speeds and cost effective operation, QuestDB reduces infrastructure costs and helps you overcome tricky ingestion bottlenecks. Thanks for reading!