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Tau is a unified development and operations environment designed as a DevOps coordination platform. It functions as a fullstack development workspace that synchronizes coding and infrastructure management tasks for both human users and automated machine processes.
The main features of taubyte/tau are: Cloud Infrastructure Orchestration, Unified Dev Ops Workflows, CLI Environment Managers, Development Environment Management, Development Workflow Automation, Fullstack Workspaces, Workspace Coordination, CLI Workspaces.
Projects with overlapping indexed features include: maiot-io/zenml — ZenML is an extensible machine learning orchestration framework designed to manage the end-to-end lifecycle of data… meshery/meshery — Meshery is a service mesh management plane and cloud native infrastructure orchestrator. It provides a visual… anomalyco/guide — This project is a serverless application framework used to define and deploy cloud infrastructure, serverless APIs,… iterative/cml — CML is a pipeline automation tool for training and evaluating machine learning models, functioning as a CI/CD system… wallix/awless — Awless is a command-line interface and infrastructure orchestrator for managing, deploying, and inspecting AWS cloud… xonsh/xonsh — Xonsh is a cross-platform command-line interface shell and automation tool that integrates a full Python interpreter…
ZenML is an extensible machine learning orchestration framework designed to manage the end-to-end lifecycle of data pipelines and AI agent workflows. It functions as a durable orchestrator that executes machine learning tasks as directed acyclic graphs, ensuring that every step is containerized for consistent performance across local, cloud, and hybrid infrastructure. By decoupling pipeline code from underlying compute and storage backends, the platform allows developers to define infrastructure-agnostic stacks that remain portable across diverse environments. The project distinguishes itself
Meshery is a service mesh management plane and cloud native infrastructure orchestrator. It provides a visual design-as-code environment for modeling microservices and infrastructure components through declarative blueprints, functioning as a centralized platform for designing, deploying, and managing service mesh infrastructure. The platform is distinguished by its ability to translate visual designs into active deployments and its use of gRPC-based adapters to integrate with diverse infrastructure providers. It features a multi-tenant architecture that manages shared workspaces and role-bas
This project is a serverless application framework used to define and deploy cloud infrastructure, serverless APIs, and static frontends through infrastructure as code. It functions as a full stack deployment pipeline and a cloud infrastructure orchestrator for provisioning resources like databases and storage buckets across multiple cloud accounts. The framework includes a local cloud development environment that allows for testing and debugging API endpoints and cloud functions on a local machine before deployment. It also features a containerized build pipeline specifically designed to con
CML is a pipeline automation tool for training and evaluating machine learning models, functioning as a CI/CD system for machine learning. It serves as a cloud compute orchestrator and Git-based workflow manager that automates model training cycles through branch management, automated commits, and integrated reporting. The project distinguishes itself by provisioning ephemeral cloud instances or Kubernetes nodes to provide specialized hardware for compute-heavy tasks. It also manages remote compute runners, allowing the connection of self-hosted GPU clusters or on-premise machines to execute