collie-cli VS seldon-core

meshcloud GmbH | Various Engineering Positions | Frankfurt, Germany | Remote work within Germany, after the Onboarding World Office | Fulltime and Permanent

Our multi-cloud platform provides control and visibility to enable an efficient and secure cloud strategy for our customers such as Volkswagen or Commerzbank. To get a tiny insight about our work: We recently launched a new open-source CLI tool that provides an easy overview of cloud landscapes: https://github.com/meshcloud/collie-cli

We are looking for:

I'm a contributor to Collie CLI which is an open-source multi-cloud management CLI for extracting various information from Google Cloud, Azure & AWS.

The best we did so far is create a neutral model for Azure Subscriptions, Role Assignments and more, which you can find in our wiki.

Disclaimer: I'm currently building an open-source CLI to make it easier to govern clouds, and I'm thinking of including hierarchy structuring as a part of it.

This looks really cool! I know how painful it can be to manage costs in the cloud so it's great that this is available as a free to use resource.

We also recently launched an open-source multi-cloud CLI for doing high-level governance in AWS, GCP & Azure.

Reading the part about tags in the handbook, it might be useful for some to use our CLI for improving your tagging strategy. Check it out here: https://github.com/meshcloud/collie-cli/wiki#identifying-inc...

I wanted to share Collie CLI with you, an open-source multi-cloud CLI that we built to make it easier to get a high-level overview of your cloud environments across the three hyperscalers. View your cloud accounts (tenants), tags, costs, and IAM directly in your terminal.

u/DeboX85 great news, Windows support has arrived with v0.5.0.

If you're looking for full transparency on your growing cloud landscape, Collie is just right for you. Collie is open-source and available on GitHub. You only need to have the native cloud CLIs installed on your machine and are ready to go.

You can find it on GitHub: Collie CLI

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.