prefect-deployment-patterns
Airflow
prefect-deployment-patterns | Airflow | |
---|---|---|
1 | 169 | |
93 | 34,570 | |
- | 1.4% | |
0.0 | 10.0 | |
over 1 year ago | 3 days ago | |
Python | 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.
prefect-deployment-patterns
-
[D] Should I go with Prefect, Argo or Flyte for Model Training and ML workflow orchestration?
Have you used infrastructure blocks in Prefect? You could easily build a block for Sagemaker deploying infrastructure for the flow running with GPUs, then run other flow in a local process, yet another one as Kubernetes job, Docker container, ECS task, AWS batch, etc. Super easy to set up, even from the UI or from CI/CD. There are a bunch of templates and examples here: https://github.com/anna-geller/prefect-deployment-patterns
Airflow
-
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.
-
Navigating Week Two: Insights and Experiences from My Tublian Internship Journey
In week Two, I contributed to the Apache Airflow repository.
-
Airflow VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
-
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.
-
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.
-
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!
-
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.
-
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?
Taipy - Turns Data and AI algorithms into production-ready web applications in no time.
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.
Udacity-Data-Engineering-Projects - Few projects related to Data Engineering including Data Modeling, Infrastructure setup on cloud, Data Warehousing and Data Lake development.
dagster - An orchestration platform for the development, production, and observation of data assets.
buildflow - BuildFlow, is an open source framework for building large scale systems using Python. All you need to do is describe where your input is coming from and where your output should be written, and BuildFlow handles the rest. No configuration outside of the code is required.
n8n - Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.
weather_data_pipeline - This is a PySpark-based data pipeline that fetches weather data for a few cities, performs some basic processing and transformation on the data, and then writes the processed data to a Google Cloud Storage bucket and a BigQuery table.The data is then viewed in a looker dashboard
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.
canarypy - CanaryPy - A light and powerful canary release for Data Pipelines
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
f1-data-pipeline - F1 Data Pipeline
Dask - Parallel computing with task scheduling