Polyaxon vs ZenML

Polyaxon is an AI engineering control plane for machine-learning training, inference and agent workloads on Kubernetes. It records run parameters, metrics, logs, code versions, artifacts, lineage and runtime state. Orchestration covers jobs, services, DAGs, schedules, sweeps, distributed workloads and reusable components. Isolated execution environments can be launched with controlled filesystems, network access, tools, SSH and runtime policies. Evaluation and monitoring include offline and online evaluations, logs, traces, metrics, health checks, alerts and dashboards. Listed integrations include PyTorch, TensorFlow, Hugging Face, LangChain, Ray, Dask, Spark, AWS, GCP, Azure, GitHub, GitLab, Slack and Datadog. Deployment is available through managed cloud or self-hosted Community and Enterprise editions. The core is Apache 2.0 licensed. A free Community Edition covers one cluster and namespace; paid access starts at $555/mo.

ZenML orchestrates AI and machine-learning pipelines and agents written in Python. Pipelines can run on Kubernetes, Vertex AI, SageMaker, AzureML, or a laptop without rewriting code. ZenML versions step outputs such as models and evaluation datasets, supports re-execution from any step, and reuses cached results when code and inputs have not changed. Deployment choices include local, SaaS, and self-hosted setups, with Docker and Kubernetes Helm methods. ZenML says it stores metadata while data, artifacts, and compute remain in the customer's infrastructure or VPC. Its integrations directory lists 66 tools, including LangGraph, OpenAI Agents SDK, PyTorch, MLflow, AWS, and Google Cloud Vertex AI Pipelines. The self-hosted Open Source plan is free and includes unlimited executions and projects. Scale costs $999 a month and includes 2,000 executions, three projects, and five snapshots. Enterprise has custom pricing and adds SSO, custom-role RBAC, audit logs, and air-gapped deployment. ZenML says it is SOC 2 Type II and ISO 27001 certified.