Search Results for "dag"

...Define workflows where each step in the workflow is a container. Model multi-step workflows as a sequence of tasks or capture the dependencies between tasks using a directed acyclic graph (DAG). Easily run compute intensive jobs for machine learning or data processing in a fraction of the time using Argo Workflows on Kubernetes. Run CI/CD pipelines natively on Kubernetes without configuring complex software development products. Argo Workflows is the most popular workflow execution engine for Kubernetes. It can run 1000s of workflows a day, each with 1000s of concurrent tasks. ...

...It can run anywhere Kubernetes is deployed: public cloud, on-prem or hybrid cloud. Cyclone is architectured with a low-level workflow engine that is application agnostic, offering capabilities like workflow DAG scheduling, resource lifecycle management and most importantly, a pluggable and extensible framework for extending the core APIs. Above which, Cyclone provides built-in support for high-level functionalities, with CI/CD pipelines and AI DevOps being two notable examples, and it is possible to expand to more use cases as well. With Cyclone, users end up with the flexibility of workflow orchestration and the usability of complete CI/CD and AI DevOps solutions. ...

...Powered by go-git. There are two command-line tools: hercules and labours. The first is a program written in Go that takes a Git repository and executes a Directed Acyclic Graph (DAG) of analysis tasks over the full commit history. The second is a Python script that shows some predefined plots over the collected data. These two tools are normally used together through a pipe. It is possible to write custom analyses using the plugin system. It is also possible to merge several analysis results together - relevant for organizations. ...