seldon-core

An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models (by SeldonIO)

Seldon-core Alternatives

Similar projects and alternatives to seldon-core

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better seldon-core alternative or higher similarity.

seldon-core reviews and mentions

Posts with mentions or reviews of seldon-core. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-20.
  • seldon-core VS MLDrop - a user suggested alternative
    2 projects | 20 Feb 2023
  • [D] Feedback on a worked Continuous Deployment Example (CI/CD/CT)
    2 projects | /r/MachineLearning | 12 Apr 2022
    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.
  • [D] BentoML's Compatibility with Seldon;
    1 project | /r/MachineLearning | 7 Mar 2022
    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 â €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?
  • Building a Responsible AI Solution - Principles into Practice
    6 projects | dev.to | 10 Jan 2022
    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.
  • Ask HN: Who is hiring? (January 2022)
    28 projects | news.ycombinator.com | 3 Jan 2022
    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/

  • Ask HN: Who is hiring? (December 2021)
    37 projects | news.ycombinator.com | 1 Dec 2021
  • Has anyone implemented Seldon?
    2 projects | /r/mlops | 19 Oct 2021
    Also note our github repo has a link to our slack where you can ask active users: https://github.com/SeldonIO/seldon-core
  • [Discussion] Look for service to upload a model and receive a REST API endpoint, for serving predictions
    4 projects | /r/MachineLearning | 18 Aug 2021
    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 Core : Open-source platform for rapidly deploying machine learning models on Kubernetes
    1 project | /r/MLOpsIndia | 16 Aug 2021
  • Looking for open-source model serving framework with dashboard for test data quality
    2 projects | /r/datascience | 31 Mar 2021
    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.
  • A note from our sponsor - SaaSHub
    www.saashub.com | 24 Apr 2024
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