seldon-core
Cypress
seldon-core | Cypress | |
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14 | 174 | |
4,220 | 46,167 | |
1.2% | 0.4% | |
7.6 | 9.8 | |
5 days ago | 4 days ago | |
HTML | JavaScript | |
GNU General Public License v3.0 or later | MIT License |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
seldon-core
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seldon-core VS MLDrop - a user suggested alternative
2 projects | 20 Feb 2023
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[D] Feedback on a worked Continuous Deployment Example (CI/CD/CT)
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.
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[D] BentoML's Compatibility with Seldon;
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?
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Building a Responsible AI Solution - Principles into Practice
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.
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Ask HN: Who is hiring? (January 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)
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Has anyone implemented Seldon?
Also note our github repo has a link to our slack where you can ask active users: https://github.com/SeldonIO/seldon-core
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[Discussion] Look for service to upload a model and receive a REST API endpoint, for serving predictions
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
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Looking for open-source model serving framework with dashboard for test data quality
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.
Cypress
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Simulating Internet Outage and Recovery using Cypress
In this blog post, we'll explore a Cypress test that replicates this scenario, utilizing the powerful intercept command to manipulate network requests and responses.
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Testing Defer Blocks in Angular with Cypress
Recently I came across this issue while triaging some issues at Cypress. (Shout out to MattiaMalandrone for creating an issue with clear instructions for how to reproduce). After quickly replicating the issue I sought after a solution which ultimately inspired me to write this article.
- Cypress changed older versions to block third-party plugins (ignoring lockfiles)
- Cypress can't open Tesla.com website
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What is Playwright?
While similar to Puppeteer, Cypress, and Selenium, there are some differences. Let’s find out what they are.
- Episode 23/37: ISR in Angular, Cypress & Playwright
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/Does Cypress Component Testing Work With Libraries
This questions was asked a while ago and pretty much went unanswered: https://github.com/cypress-io/cypress/issues/23677. If it doesn't work with libraries yet I will stop battling with it for now. If it doesn't work, what are you using to test libraries?
- Finally promising Web Testing solution
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Episode 23/27: NgRx 16.1 & Signal Store, Jest, Cypress, Nx
Cypress Release Notes
- Trouble/Weirdness with accessing aliased values in `this` context
What are some alternatives?
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
Playwright - Playwright is a framework for Web Testing and Automation. It allows testing Chromium, Firefox and WebKit with a single API.
MLServer - An inference server for your machine learning models, including support for multiple frameworks, multi-model serving and more
Detox - Gray box end-to-end testing and automation framework for mobile apps
evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
jest - Delightful JavaScript Testing.
great_expectations - Always know what to expect from your data.
kafka-test-helper - Utility library that simplify testing of Node.js components that interacts with Kafka broker.
alibi-detect - Algorithms for outlier, adversarial and drift detection
supertest - 🕷 Super-agent driven library for testing node.js HTTP servers using a fluent API. Maintained for @forwardemail, @ladjs, @spamscanner, @breejs, @cabinjs, and @lassjs.
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Sentry - Developer-first error tracking and performance monitoring