seldon-core
Hasura
seldon-core | Hasura | |
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14 | 228 | |
4,220 | 30,832 | |
1.2% | 0.3% | |
7.6 | 9.8 | |
5 days ago | 4 days ago | |
HTML | TypeScript | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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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.
Hasura
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Serious flaws in SQL – Edgar F. Codd (1990)
> 2. ORMs do not hide SQL nastiness.
This is certainly true!
I mean: ORMs are now well known to "make the easy queries slightly more easy, while making intermediate queries really hard and complex queries impossible".
I think the are of ORMs is over. It simply did not deliver.
If a book on SQL is --say-- 100 pages, a book on Hibernate is 400 pages. So much to learn just to make the easy queries slightly easier to type? Just not worth it.
I prefer jooq any day over ORMs. And dont get me started over what tools like Hasuna have to offer.
There are also some languages (forgot the names) that are SQL-done-right. Select in the back, more type safe, more logic, more in the same steps as the query gets executed. These need to be adopted by PG and MySQL and we're good to go. (IMHO)
https://www.jooq.org/
https://hasura.io/
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Ask HN: How Can I Make My Front End React to Database Changes in Real-Time?
[4] https://github.com/hasura/graphql-engine/blob/master/architecture/live-queries.md
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The Many Ways Not to Build an API
Another strategy is to model access control declaratively and enforce it in the application layer. ZenStack (built above Prisma ORM) and Hasura are good examples of this approach. The following code shows how access policies are defined with ZenStack and how a secured CRUD API can be derived automatically.
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The 2024 Web Hosting Report
Today, this ecosystem is going strong with new providers like Hasura, AppWrite and Supabase powering millions of projects. There are a few reasons people choose this style of hosting, especially if they are more comfortable with frontend development. BaaS lets them set up a database in a secure way, expose some business logic on top of the data, and connect via a dev-friendly SDK from their app or website code to save data easily. These modern tools build a blend of managed database with curated plugins such as authentication, great admin dashboards, and function as a service type capability - all in one package, and often offered as a integrated hosted service.
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Ask HN: Is There a Zapier for APIs?
Hi! If you’ve ever thought about something like using GraphQL for something like this.. You might like Hasura. (Obligatory I work for Hasura)
We’ve got an OpenAPI import and you can setup cron-jobs or one-off jobs and do things like load in headers from the environment variables to pass through. There isn’t currently an easy journey for chaining multiple calls together without writing any code at all, but you can wrap pretty much any API endpoint via OpenAPI import or a custom action, and you can even make minor edits to things like the API contract format to change aliases/naming.
Our goal is to join all the things, databases and API’s. Most people know us for instant GraphQL API’s that give you CRUD on your database, but we also wrap APIs.
Not sure if something like this would fit your use-case and do check out some of the other things mentioned, but depending what you are trying to do I think Hasura might potentially work.
You can find out more here: https://hasura.io
- Ask HN: What is the easiest way to create a CRUD web app in 2024?
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2024 Web Development Wish List
Nested Mutation - 113 thumbs up, and still open since 2019... another case of not listening to the users?
- Hasura V3 Engine is in alpha
- Hasura: Instant GraphQL on your Postgres data
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Hasura and Keycloak integration with NestJS server
Hasura is an open-source real-time GraphQL API server with a strong authorization layer on your database. You can subscribe to database events via webhooks. It can combine multiple API servers into one unified graphQL API. Hasura is a great tool to build any CRUD GraphQL API. Hasura does not have any authentication mechanisms; e.g., you need an auth server to handle sign-up and sign-in.
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!
supabase - The open source Firebase alternative.
MLServer - An inference server for your machine learning models, including support for multiple frameworks, multi-model serving and more
postgrest - REST API for any Postgres database
evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
Kong - 🦍 The Cloud-Native API Gateway and AI Gateway.
great_expectations - Always know what to expect from your data.
crystal - 🔮 Graphile's Crystal Monorepo; home to Grafast, PostGraphile, pg-introspection, pg-sql2 and much more!
alibi-detect - Algorithms for outlier, adversarial and drift detection
KrakenD - Ultra performant API Gateway with middlewares. A project hosted at The Linux Foundation
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Neo4j - Graphs for Everyone