flyte
kopf
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flyte | kopf | |
---|---|---|
31 | 6 | |
4,761 | 1,951 | |
3.3% | - | |
9.8 | 7.8 | |
about 6 hours ago | 17 days ago | |
Go | Python | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
flyte
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First 15 Open Source Advent projects
9. Flyte by Union AI | Github | tutorial
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Flyte 1.10: Self-hosted solution to build production-grade data and ML pipelines; now ships with monorepo, new agents and sensors, eager workflows and more π (4.1k stars on GitHub)
GitHub: https://github.com/flyteorg/flyte
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Flyte: Open-source orchestrator for building production-grade ML pipelines
This is actually but a link to Flyte, this is a link to the documentation for the Flyte integration in LangChain, a separate product.
Flyte's homepage is https://flyte.org/
- Flyte: Advanced workflow orchestration alternative to Apache Airflow
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Orchestration: Thoughts on Dagster, Airflow and Prefect?
Anyone tried Flyte?
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Flyte 1.6.0: Self-hosted solution to build production-grade data and ML pipelines; now ships with PyTorch elastic training, image specification without dockerfile, enhanced task execution insights and more π (3.4k stars on GitHub)
Website: https://flyte.org/
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Flyte(v1.5.0) - Self-hosted solution to build production-grade data and ML pipelines; now ships with streaming support, pod templates, partial tasks and more π (3.2k stars on GitHub)
Flyte is an open source orchestration tool for managing the workflow of machine learning and AI projects. It runs on top of Kubernetes.
- Flyte: Open-Source Kubernetes-Native ML Orchestrator Implemented in Go
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What is MLOps and how to get started? | MLOps series | Deploying ML in production
I have a question though, what is your opinion on https://flyte.org. My pipeline uses this and itβll be interesting to get your perspectives on itβs capabilities.
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Github alternative for ML?
Have you looked at flyte.org. It aims to bring "versioning", "compute" and "reproducibility" together in one package.
kopf
- A Kubernetes Operator in Rust
- I wrote a kubernetes operator for βlocustβ, should I open source it
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Automate All the Boring Kubernetes Operations with Python
If you're looking for more examples beyond what was shown and referenced above, I recommend exploring other popular tools that make use Python Kubernetes client, such kopf - the library for creating Kubernetes operators. I also find it very useful to take a look at tests of the library itself, as it showcases its intended usage such this client test suite.
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is it possible to have components of a specific namespace run on specific nodes ?
Depending on how you want to configure your selecting logic, it can be solved by mutating admission webhooks for the pods. For example, in Kopf, the simplest approach would be:
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Kopf 1.31 now supports admission webhooks. Feedback is welcome!
Hello. Kopf (a framework to write Kubernetes operators in Python) 1.31 is released and has finally got admission webhooks β https://github.com/nolar/kopf/releases/tag/1.31.0. I would appreciate some feedback from experienced operator developers on how easy or hard it is to write webhooks now, and what is missing and makes it inconvenient. The docs: https://kopf.readthedocs.io/en/stable/admission/ For a brief preview, it looks like this:
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lightkube 0.6.0 - python kubernetes client
Correct, using generic resources with Client.watch should work. In general to create more complex operators I would recommend to check out kopf.
What are some alternatives?
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
awx-operator - An Ansible AWX operator for Kubernetes built with Operator SDK and Ansible. π€
argo - Workflow Engine for Kubernetes
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
temporal - Temporal service
fastapi-crudrouter - A dynamic FastAPI router that automatically creates CRUD routes for your models
kubeflow - Machine Learning Toolkit for Kubernetes
Celery-Kubernetes-Operator - An operator to manage celery clusters on Kubernetes (Work in Progress)
pykorm - A python π kubernetes βΈοΈ ORM π. Very useful when writing operators for your CRDs with Kopf.
Kedro - Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
Dependency Injector - Dependency injection framework for Python