seldon-core VS logseq

ZenML is an extensible, open-source MLOps framework to create production-ready machine learning pipelines. Built for data scientists, it has a simple, flexible syntax, is cloud- and tool-agnostic, and has interfaces/abstractions that are catered towards ML workflows. Seldon Core is a production grade open source model serving platform. It packs a wide range of features built around deploying models to REST/GRPC microservices that include monitoring and logging, model explainers, outlier detectors and various continuous deployment strategies such as A/B testing, canary deployments and more.

I am using BentoML to build the docker container for a BERT model, and then deploy that using Seldon on GKE. The model's REST API endpoint works fine. at terms of compatibility with Seldon, the metrics are being scraped by Prometheus and visualized on Grafana. The only Seldon component that doesn't appear to be working is the request logging, which I have working for other applications that were deployed on Seldon. I am using the elastic stack from here. From my understanding, request logging should still be compatible and the ⠀only lost functionality should be Seldon's model metadata. Any insight on how to get the centralized request logging working? No errors were shown; it's just that the logs aren't being captured and sent to ElasticSearch. Anyone have any success using BentoML with Seldon and not losing any of Seldon's features?

While tools in the model experimentation space normally include diagnostic charts on a model's performance, there are also specialised solutions that help ensure that the deployed model continues to perform as they are expected to. This includes the likes of seldon-core, why-labs and fiddler.ai.

Seldon | Multiple positions | London/Cambridge UK | Onsite/Remote | Full time | seldon.io

At Seldon we are building industry leading solutions for deploying, monitoring, and explaining machine learning models. We are an open-core company with several successful open source projects like:

* https://github.com/SeldonIO/seldon-core

* https://github.com/SeldonIO/mlserver

* https://github.com/SeldonIO/alibi

* https://github.com/SeldonIO/alibi-detect

* https://github.com/SeldonIO/tempo

We are hiring for a range of positions, including software engineers(go, k8s), ml engineers (python, go), frontend engineers (js), UX designer, and product managers. All open positions can be found at https://www.seldon.io/careers/

Also note our github repo has a link to our slack where you can ask active users: https://github.com/SeldonIO/seldon-core

If you want to serve your model at scale, with a bunch of production features you should have a look at the open-source framework Seldon Core. It does what you're asking for plus a bunch of other cool stuff like routing, logging and monitoring.

Seldon ticks most of those boxes if you already have some experience with kubernetes. You can set up a/b tests, do payload logging to elastic and then do monitoring on top of that, and it has drift detection and model explainer modules too. Idk about great expectations integration, but you could probably do something with a custom transformer module as part of the inference graph.

Logseq support via our Logseq Plugin

Sorry, but _what exactly_ «it seems to do» from your point of view?

My «second brain» now is almost 300Mb of text, pictures, sound files, PDF and other stuff. As I already mentioned, it contains tables, mathematical formulae, sheet music, cross-references, code samples, UML diagrams and graphs in Graphviz format. It is versioned, indexed by local search engine, analyzed by AI assistant and shared between many computers and mobile devices. And (last but not least) it works: it allows me to solve my tasks way more faster than with the assistant of external, non-personalized tools (like ChatGPT, StackExchange or Google).

I know no tools for all this tasks except org-mode. Well, maybe Evernote in the 2010-s was something similar — but with less features, with more bugs and with worse interface.

Personal note-taking _is_ a complex task per se (well, at least for someone like typical HN visitor). I've seen many note-taking tools, that were ridiculously featureless, stupid and inconvenient because they were _not_ complex enough.

> Sure if one wants to do emacs-gardening it is fine.

1)You can use org-mode outside Emacs. See for example Logseq (https://logseq.com/), organice (https://organice.200ok.ch/) or EasyOrg.

2)Org-mode works in Emacs out of the box, you don't need any «emacs-gardening» to use org-mode.

3)The term «Emacs-gardening» itself sound a bit like hate-speech for me. The complexity of Emacs customization is overrated, mostly due to opinions of people who never used Emacs or used it in the previous millennium.

Obsidian is great.

For those looking for an open source alternative (or don't want to pay the Obsidian fees for professional usage) check out Logseq: https://logseq.com/

For an opensource alternative to Obsidian checkout Logseq (1). I spent a while thinking obsidian was opensource out of my own ignorance and was disappointed when I learned it was not.

1: https://logseq.com/

I use logseq to keep journal of my daily work.

While Emacs and Org mode can certainly be used for this (and, when they can't, you can always inject little python/js scripts in your emacs config to take care of specific things), I'd also recommend you take a look at Logseq.