MLRun vs Polyaxon

MLRun is an open-source framework for orchestrating machine-learning and generative-AI applications across their lifecycles. It automates data preparation, model tuning, customization, validation, and optimization for ML models and large language models over elastic resources. Its feature store can collect, transform, store, catalog, serve, and monitor data features. MLRun supports multi-cloud, hybrid, and on-premises deployments with built-in observability; documented options include Kubernetes, AWS, Azure AKS, and Iguazio’s managed service. The ecosystem includes storage and data systems such as S3, Google Cloud Storage, BigQuery, Snowflake, Kafka, Spark, and Dask, alongside PyTorch, TensorFlow, XGBoost, and ONNX. CI/CD integrations include GitHub Actions, GitLab CI/CD, Jenkins, and Kubeflow Pipelines. MLRun also lists model registry, experiment tracking, pipeline orchestration, model serving, data versioning, and managed compute. The open-source plan costs nothing and includes community support. Managed MLRun includes LDAP integration, user and group management, service authentication and authorization, secured API-gateway authentication, service monitoring, log management, and 24/7 enterprise support.

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.