cortex
Airflow
cortex | Airflow | |
---|---|---|
33 | 169 | |
7,990 | 34,570 | |
0.1% | 1.1% | |
2.2 | 10.0 | |
11 months ago | about 4 hours 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.
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cortex
- Ask HN: Are there any reliable benchmarks for Machine Learning Model Serving?
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Local text generation (InferKit alternative)
I found GPT-2 with PyTorch, Cortex, and Transformers.
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Why ML should be written as pipelines from the get-go
Technologies: Flask/FastAPI, Kubernetes, Docker, Cortex, Seldon
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[P] I made tinymodels.io to deploy models quickly, feel free to use for your prototypes and web demos
oh I see - that's neat. I think cortex.dev had some support for that sort of thing. It is? was? a wrapper to manage an EKS cluster for you and it could do things like hot swap what's in ram, autoscale, or use spot instances to save costs.
- Containers as a service on AWS
- Containers as a Service on AWS
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How would you go about deploying transformer based model?
I use cortex.dev for deploying my models. I have successfully deployed finetuned T5s, which seems similar to your usecase.
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Microservice on ECS having burst load issue
Arghs, my bad, yeah, doesn't seem to be available yet. But maybe Cortex might help: https://github.com/cortexlabs/cortex
- Self-hosted AWS Lambda alternative
Airflow
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Building in Public: Leveraging Tublian's AI Copilot for My Open Source Contributions
Contributing to Apache Airflow's open-source project immersed me in collaborative coding. Experienced maintainers rigorously reviewed my contributions, providing constructive feedback. This ongoing dialogue refined the codebase and honed my understanding of best practices.
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Navigating Week Two: Insights and Experiences from My Tublian Internship Journey
In week Two, I contributed to the Apache Airflow repository.
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Airflow VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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Best ETL Tools And Why To Choose
Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows.
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Simplifying Data Transformation in Redshift: An Approach with DBT and Airflow
Airflow is the most widely used and well-known tool for orchestrating data workflows. It allows for efficient pipeline construction, scheduling, and monitoring.
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Share Your favorite python related software!
AIRFLOW This is more of a library in my opinion, but Airflow has become an essential tool for scheduling in my work. All our ML training pipelines are ordered and scheduled with Airflow and it works seamlessly. The dashboard provided is also fantastic!
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Ask HN: What is the correct way to deal with pipelines?
I agree there are many options in this space. Two others to consider:
- https://airflow.apache.org/
- https://github.com/spotify/luigi
There are also many Kubernetes based options out there. For the specific use case you specified, you might even consider a plain old Makefile and incrond if you expect these all to run on a single host and be triggered by a new file showing up in a directory…
- "Você veio protestar para ter acesso ao código fonte da urnas. O que é o código fonte?" "Não sei" 🤡
- Cómo construir tu propia data platform. From zero to hero.
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Is it impossible to contribute to open source as a data engineer?
You can try and contribute some new connectors/operators for workflow managers like Airflow or Airbyte
What are some alternatives?
MLflow - Open source platform for the machine learning lifecycle
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.
golang-design-pattern - 设计模式 Golang实现-《研磨设计模式》读书笔记
dagster - An orchestration platform for the development, production, and observation of data assets.
oauth2 - Go OAuth2
n8n - Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.
prysm - Go implementation of Ethereum proof of stake
luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
terraform-provider-azurerm - Terraform provider for Azure Resource Manager
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
OpenFaaS - OpenFaaS - Serverless Functions Made Simple
Dask - Parallel computing with task scheduling