2 个仓库
Frameworks for wrapping pipeline execution logic within custom web servers.
Distinct from Custom Logic Triggers: Distinct from Custom Logic Triggers: focuses on the API server construction for external triggering rather than just the internal trigger logic.
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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
Wraps pipeline execution logic within a custom web server to implement specialized routing, authentication, or integration requirements.
ZenML is an orchestration platform designed for building, deploying, and monitoring reproducible machine learning pipelines and agentic workflows. It provides a unified framework that manages the entire lifecycle of machine learning assets, from data processing and model training to the deployment of persistent inference services. By decoupling pipeline logic from underlying compute and storage, the platform enables teams to transition workflows seamlessly from local development environments to production-grade cloud infrastructure. The platform distinguishes itself through a service-oriented
Provides bespoke HTTP interfaces to trigger pipeline executions on demand with custom routing and security logic.