Special Repository of Prasadbobby
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Updated
Jul 3, 2024 - Python
Special Repository of Prasadbobby
Temporal service
An orchestration platform for the development, production, and observation of data assets.
Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.
Flowpipe is a cloud scripting engine. Automation and workflow to connect your clouds to the people, systems and data that matters.
Curated list of useful Github actions with workflows examples 💡
Conductor is an event driven orchestration platform
Your friendliest open source all-in-one automation tool ✨ Workflow automation tool 100+ integration / Enterprise automation tool / Zapier Alternative
Cadence is a distributed, scalable, durable, and highly available orchestration engine to execute asynchronous long-running business logic in a scalable and resilient way.
Python-based workflow engine. Automate and manage custom business processes, with no overhead.
Github action to label pull requests with lerna package names
A Reliable, Customize-able, and Scalable Zapier Alternative for Production-Grade Workflow Automation
Hera is an Argo Python SDK. Hera aims to make construction and submission of various Argo Project resources easy and accessible to everyone! Hera abstracts away low-level setup details while still maintaining a consistent vocabulary with Argo. ⭐️ Remember to star!
OpenFn/Lightning ⚡️ is the newest version of the OpenFn DPG and provides a web UI to visually manage complex workflow automation projects.
Hence, a simple but powerful framework designed to streamline data pipeline, scraping, automation workflow orchestration.
Open-source, low-code, extendable API integration & workflow automation platform. Integrate your organizations or your SaaS product with any third party API
The open-source alert management and AIOps platform
The Daml smart contract language
A collection of portable, reusable and cross-platform automation recipes (CM scripts) with a human-friendly interface and minimal dependencies to make it easier to build, run, benchmark and optimize AI, ML and other applications and systems across diverse and continuously changing models, data sets, software and hardware (cloud/edge)
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