flyte
kestra
Our great sponsors
flyte | kestra | |
---|---|---|
31 | 32 | |
4,761 | 6,340 | |
4.0% | 14.7% | |
9.8 | 9.9 | |
1 day ago | 2 days ago | |
Go | Java | |
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
-
First 15 Open Source Advent projects
9. Flyte by Union AI | Github | tutorial
-
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 π (4.1k stars on GitHub)
GitHub: https://github.com/flyteorg/flyte
-
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
-
Orchestration: Thoughts on Dagster, Airflow and Prefect?
Anyone tried Flyte?
-
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 π (3.4k stars on GitHub)
Website: https://flyte.org/
-
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 π (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
-
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 itβll be interesting to get your perspectives on itβs capabilities.
-
Github alternative for ML?
Have you looked at flyte.org. It aims to bring "versioning", "compute" and "reproducibility" together in one package.
kestra
-
A High-Performance, Java-Based Orchestration Platform
Kestra's communication is asynchronous and based on a queuing mechanism. It leverages the Micronaut framework and offers two runners: one that uses a database (JDBC) for both the message queue and resource storage, and another that uses Kafka as the message queue and Elasticsearch as the resource storage. The platform is fully extensible and plugin-based, providing a rich set of plugins for various workflow tasks, triggers, and data storage options. For those interested, the GitHub repository is available here: https://github.com/kestra-io/kestra
- Kestra is an open-source data orchestration platform for complex workflows
- YAML-based data orchestrator
- Kestra
-
Introduction to Kestra, the open source data orchestration and scheduling platform
For everyone wondering https://github.com/kestra-io/kestra/discussions/468
-
Snowflake data pipeline with Kestra
If you need any guidance with your Snowflake deployment, our experts at Kestra would love to hear from you. Let us know if you would like us to add more plugins to the list. Or start building your custom Kestra plugin today and send it our way. We always welcome contributions!
-
Airflow's Problem
But I totally agree that a large static dag is not appropriate in the actual data world with data mesh and domain responsibility.
[0] https://github.com/kestra-io/kestra
-
Ask HN: Open-source with Kafka as dependencies, is this a instant turn off?
- We have plans to add another option that will replace both dependencies with jdbc (https://github.com/kestra-io/kestra/pull/368), is theses dependencies more comfortable for you?
-
ELT vs ETL: Why not both?
With Kestra's innate flexibility, and many integrations, you are not locked into the choice of one ingestion method or the other. Complex workflows can be developed, whether in parallel or sequentially, to deliver both ELT and ETL processes. Simple descriptive yaml is used to connect plugins, and to create flows. Because workflows created in Kestra are represented visually, and issues can be seen in relation to individual tasks, there is no need to fear complexity. Trouble can be traced to its source in an instant, allowing you to try new things and come up with a new solution without fear. Give it a try, and let us know what you come up with!
-
Debezium Change Data Capture without Kafka Connect
Kestra is an orchestration and scheduling platform that is designed to simplify the building, running, scheduling, and monitoring of complex data pipelines. Data pipelines can be built in real-time, no matter how complex the workflow, and can connect to multiple resources as needed (including Debezium).
What are some alternatives?
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
conductor - Conductor is a microservices orchestration engine.
argo - Workflow Engine for Kubernetes
zeebe - Distributed Workflow Engine for Microservices Orchestration
temporal - Temporal service
kogito-runtimes - This repository is a fork of apache/incubator-kie-kogito-runtimes. Please use upstream repository for development.
kubeflow - Machine Learning Toolkit for Kubernetes
debezium - Change data capture for a variety of databases. Please log issues at https://issues.redhat.com/browse/DBZ.
Celery-Kubernetes-Operator - An operator to manage celery clusters on Kubernetes (Work in Progress)
akhq - Kafka GUI for Apache Kafka to manage topics, topics data, consumers group, schema registry, connect and more...
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.
PowerJob - Enterprise job scheduling middleware with distributed computing ability.