seldon-core VS deno

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.

NodeJS is the dominant Javascript server runtime environment for Javascript and Typescript (sort of) projects. But over the years, we have seen several attempts to build alternative runtime environments such as Deno and Bun, today’s subject, among others.

https://github.com/denoland/deno/issues is the ideal place -- we try to triage all incoming issues, the more specific the repro the easier it is to address but we will take a look at everything that comes in.

Install Node.js (or Bun, or Deno, or whatever JS runtime you prefer) if it's not there

QUIC is very exciting, after seeing what it can do for performance in Cloudflare network and Cloudflare workers, I can't wait to finally see it in Deno[0] 1.41.

[0] https://github.com/denoland/deno/pull/21942#issuecomment-192...

So as an end user it's kind of like https://deno.com/ where you buy into a runtime + comes prepacked with DBs (k/v stores), scheduling, and deploy stuff?

> by storing Unison code in a database, keyed by the hash of that code, we gain a perfect incremental compilation cache which is shared among all developers of a project. This is an absolutely WILD feature, but it's fantastic and hard to go back once you've experienced it. I am basically never waiting around for my code to compile - once code has been parsed and typechecked once, by anyone, it's not touched again until it's changed.

Interesting. Whats it like upgrading and managing dependencies in that code? I'd assume it gets more complex when it's not just the Union system but 3rd party plugins (stuff interacting with the OS or other libs).

~90MB+ at this stage and do now allow compression without erroring out. Deploying ala Golang is not feasible at that level but could well be down the line if this dev branch is picked up again!

The exe output grew from from ~50MB to plus ~90MB from 2021 to 2024: https://github.com/denoland/deno/discussions/9811 which mean Deno is worse than Node.js's pkg solution by a decent margin.

Behind the scenes is a simple Sveltekit-powered server function to fetch a Spotify client token then find a user's recommendation playlist and its track information. A Deno edge function to performs this data fetch and renders server-side Svelte.

If your application is written in JavaScript, integrating it with JavaScript extensions is a no-brainer. However, Secutils.dev is entirely written in Rust. How would I even begin? Fortunately, I recently came across an excellent blog post series explaining how to implement your JavaScript runtime in a Rust application with Deno: