proposals
Mage
proposals | Mage | |
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60 | 77 | |
63 | 7,050 | |
- | 3.5% | |
4.2 | 9.9 | |
5 days ago | 6 days ago | |
Python | ||
MIT License | 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.
proposals
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Is there an alternative for Airflow for running thousands of dynamic tasks?
Check out temporal.io open source project. It was built at Uber for large scale business-level processes. So any data pipelines are low-rate use cases by definition.
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KuFlow as a Temporal.io-based Workflow Orchestrator
With KuFlow it is also possible to work with serverless workflows apart from Temporal.io, we explain it in this blog entry, but in summary, almost as a no-code tool, the correct use It would be a rather low-code tool; in just a matter of minutes with our drag-and-drop tool, you can have a workflow that interacts with one or more users of the organization.
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How to handle background jobs in Rust?
Otherwise you may want to look into Kafka or Fluvio to ensure that task runs at least once. If you're doing something like batch operations as a background task, Temporal is another great option.
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No-code or Workflow as code? Better both
The runtime is developed using Temporal, which is one of the main tools that we are currently using at KuFlow. Thanks to, all the workflow executions are robust: your application will be durable, reliable, and scalable.
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Temporal Programming, a new name for an old paradigm
Hmmm I got confused by the name. I thought it's related to https://temporal.io/
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Possible innovations in Event Sourcing frameworks.
Have you looked at temporal.io open source platform? It uses event sourcing as an implementation detail. But it greatly simplifies the user experience compared to "raw event sourcing."
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After Airflow. Where next for DE?
Rewrite Airflow on top of temporal.io. This way, you get unlimited scalability and very high reliability out of the box and would be able to innovate on the features that matter for DE.
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Show HN: Retool Workflows â Cronjobs, but better
Hi all, founder @ Retool here. Over the past year, weâve been working on Retool Workflows; a fast way for engineers to automate tasks with code. We started building the product because we ourselves (as developers) were looking for something in-between writing cron jobs (which involves a lot of boilerplate) and Zapier (which oftentimes isnât customizable enough, since it doesnât _really_ support writing code).
Workflows is a code-first automation tool: youâre _expected_ to write code, but we handle all the boilerplate for you. For example: out-of-the-box integration with 80+ resources (you probably donât want to be trying to figure out OAuth 2.0 with Salesforce!), monitoring and observability (so you can see the output of every run in the past, and immediately be notified if something goes wrong), and permissions (e.g. some Okta groups can see the outputs of Workflows, but canât change the code itself).
Right now, the product is cloud-only, but weâre hard at work at an on-prem, self-hosted version (in a Docker image). If youâre interested in that version, feel free to email us at [email protected]. We aim to get it out in the next few weeks. Self-hosted Retool is responsible for a large portion of our usage today, and weâre excited to be supporting Workflows too.
All Retool plans now include 1GB of Workflows throughput, which we think is quite generous (80% of active Workflows users are below 1GB). We donât bill by run at all, so youâre welcome to run as many workflows as you want.
We use a bunch of interesting technology for Workflows; we are, for example, using Temporal (https://temporal.io/) under the hood. Thatâs something weâre going to be writing a blog post about later. (Weâve been hard at work on the launch, hah.)
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How KuFlow supports Temporal as a worfkows engine for our processes?
In such a diverse world, it would be boring to have a single way of doing things. That's why at KuFlow we support different ways to implement the logic of our processes and tasks. And in this post, we will talk about one of them, the orchestration through Temporal, which gives us a powerful way to manage our workflows.
- Library for manage tasks when make a workflow automation.
Mage
- FLaNK AI-April 22, 2024
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A mage on the Heroâs Journey: a fantasy epic on how a startup rose from the ashes
In the coming years, Mage will create a cooperative experience so that developers can build data pipelines with their team and level up together. After that journey, Mage will go on an epic quest to create the 1st open world community experience in the data universe.
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Data sources episode 2: AWS S3 to Postgres Data Sync using Singer
Link to original blog: https://www.mage.ai/blog/data-sources-ep-2-aws-s3-to-postgres-data-sync-using-singer
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What are some open-source ML pipeline managers that are easy to use?
I would recommend the following: - https://www.mage.ai/ - https://dagster.io/ - https://www.prefect.io/ - https://metaflow.org/ - https://zenml.io/home
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Mage Battlegrounds: Craft insights from real-time customer behavior analysis
You're invited to participate in the very first Mage Battlegrounds: Craft insights from real-time customer behavior analysis, a 24-hour virtual hackathon hosted by Shashank Mishra! This data engineering competition will take place on Saturday, April 15, 2023 beginning at 11am (PST). This will be a global event open to all participants who register.
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Looking for an open-source project
Try this feature: https://github.com/mage-ai/mage-ai/issues/1166
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Daskqueue: Dask-based distributed task queue
Seeing if we can use it in https://github.com/mage-ai/mage-ai
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Data Pipeline on a Shoestring
That being said thereâs a solid family of services just breaking ground that make the local pipeline deployment easier (check out https://www.mage.ai, which does have a clear path to cloud deployment of locally developed pipes, it just isnât well documented yet, and also https://www.neuronsphere.io - which doesnât have a public solution YET (theyâre internally testing an alpha) but they built a cloud deployable solution for their paying customers and working to release one for freemium use)
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Trending ML repos of the week đ
7ď¸âŁ mage-ai/mage-ai
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Delta without using Spark
Yes, check out how Mage does it: https://github.com/mage-ai/mage-ai/tree/master/mage_integrations/mage_integrations/destinations/delta_lake_s3
What are some alternatives?
conductor - Conductor is a microservices orchestration engine.
dagster - An orchestration platform for the development, production, and observation of data assets.
temporalite-archived - An experimental distribution of Temporal that runs as a single process
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
zenml - ZenML đ: Build portable, production-ready MLOps pipelines. https://zenml.io.
vscode-dvc - Machine learning experiment tracking and data versioning with DVC extension for VS Code
seldon-core - An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
sqlmesh - Efficient data transformation and modeling framework that is backwards compatible with dbt.
kubemq-community - KubeMQ is a Kubernetes native message queue broker
mito - The mitosheet package, trymito.io, and other public Mito code.
nextjs-cron - Cron jobs with Github Actions for Next.js apps on Vercelâ˛
Data-Science-Roadmap - Data Science Roadmap from A to Z