prefect-deployment-patterns
canarypy
| prefect-deployment-patterns | canarypy | |
|---|---|---|
| 1 | 2 | |
| 93 | 3 | |
| - | - | |
| 0.0 | 7.3 | |
| over 1 year ago | 10 months ago | |
| Python | 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.
prefect-deployment-patterns
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[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
canarypy
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Ask HN: Open-Source Canary Release Tool – Seeking Your Feedback
I'm excited to introduce CanaryPy, a new open-source tool to make your data pipelines more robust by introducing new releases of your data pipelines minimising the impact of unanticipated issues. It has a plugin for Apache Airflow for now but more to come.
We'd love for you to check it out on GitHub: https://github.com/thcidale0808/canarypy
Your feedback and suggestions for improvement are precious to us. What features would you like to see? How's the usability? Would you have any thoughts on integration with your current tools?
Thank you in advance for your insights!
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Introducing Canary Release Tool to integrate with Apache Airflow - Seeking Your Feedback!
We'd love for you to check it out on GitHub: https://github.com/thcidale0808/canarypy
What are some alternatives?
Taipy - Turns Data and AI algorithms into production-ready web applications in no time.
dagster-example-pipeline - Template Dagster repo using poetry and a single Docker container; works well with CICD
Udacity-Data-Engineering-Projects - Few projects related to Data Engineering including Data Modeling, Infrastructure setup on cloud, Data Warehousing and Data Lake development.
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.
pyStudio - The easier way to do machine learning in Python without coding!
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
dagster - An orchestration platform for the development, production, and observation of data assets.
f1-data-pipeline - F1 Data Pipeline
Prefect - The easiest way to build, run, and monitor data pipelines at scale.
dataall - A modern data marketplace that makes collaboration among diverse users (like business, analysts and engineers) easier, increasing efficiency and agility in data projects on AWS.
youtube_data_analysis - Created an optimised pipeline to provide accurate data for analysis, then used snowsight (provided by Snowflake) to create a dashboard.