flyte
Celery-Kubernetes-Operator
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| flyte | Celery-Kubernetes-Operator | |
|---|---|---|
| 31 | 1 | |
| 4,727 | 79 | |
| 3.3% | - | |
| 9.8 | 3.6 | |
| 7 days ago | 5 months ago | |
| Go | Python | |
| Apache License 2.0 | Apache License 2.0 |
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 🚀 (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 🚀 (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 🚀 (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 it’ll be interesting to get your perspectives on it’s 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.
Celery-Kubernetes-Operator
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Help: from Docker-Compose to Production (EC2, ECS, EKR)
The take-out from that course is: don't deploy anything stateful on Kubernetes in production, period. Even disregarding that, don't deploy anything stateful that doesn't come in a form of an operator. For celery, https://github.com/celery/Celery-Kubernetes-Operator is a WIP, so obviously not suitable for anything.
What are some alternatives?
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
flower - Real-time monitor and web admin for Celery distributed task queue
argo - Workflow Engine for Kubernetes
rq - Simple job queues for Python
temporal - Temporal service
huey - a little task queue for python
kubeflow - Machine Learning Toolkit for Kubernetes
kopf - A Python framework to write Kubernetes operators in just a few lines of code
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.
deploy-ecs - This project aims to build, deploy and configure your services into containers of AWS ECS
hera - Hera is an Argo Python SDK. Hera aims to make construction and submission of various Argo Project resources easy and accessible to everyone! Hera abstracts away low-level setup details while still maintaining a consistent vocabulary with Argo. ⭐️ Remember to star!
sieve - Automatic Reliability Testing for Kubernetes Controllers and Operators