Polyaxon comes with powerful features built directly into the core software which can be customized and configured based on the needs of each individual deployment.
Here's a quick overview of the core features you'll probably be interested in as you're getting started. This isn't an exhaustive list, just some highlights.
Polyaxon provides a powerful and interactive workspace including:
- A command line interface
- SDKs and clients
- An extensive tracking API
- A dashboard with visualizations and advanced insights
- Lineage and provenance tracking
- Possibility to create custom dashboards and visualizations
- Advanced query & search interface
- Uniform logs management and streaming for all operations
- Jupyter Notebook & Jupyter Lab integration
- Matplotlib, Plotly, Bokeh, Altair, and Vega integrations
- Tensorboard integration
- VSCode integration
- Streamlit, Voila, Papermill, Commuter integrations
- Native Kubeflow scheduling
- Celery executor
- Built-in logic for building containers
- Customizable interface
- Unlimited scalability options
- Auto-management of artifacts and lineage tracking
- CI system for automating the training of your experiment based on different types of triggers.
Polyaxon makes your experiments reproducible, portable, and repeatable while being language and framework agnostic.
- Powerful packaging format
Polyaxonfile: A specification for packaging dependencies, inputs, outputs, artifacts, environments, and runtime of an operation to schedule on Kubernetes.
- Extensive tracking API for source code, parameters, data, metrics, tags, and logs.
- You can see the full experiment history at a glance, including when, who, and where.
- Auto-document all experiments with statuses, metrics, hyperparams, source code, data, visualizations, artifacts, and resources used in each experiment.
- Advanced insights and comparison of experiments based on results, hyperparams, versions of training data and source code.
At its core, Polyaxon is a self-consuming, RESTful JSON API with decoupled clients and front-end. We provide lots of tooling to improve data scientists work, but at the end of the day it's Just JSON️, so if you want to use Polyaxon completely headless and write your own frontend or clients... you can!
Equally, Polyaxon is heavily designed for performance and scalability with replication and concurrency.
You can easily scale Polyaxon API and scheduler horizontally, and with Polyaxon agents you can scale your workload over multiple namespaces and clusters.
Polyaxon exposes a flow engine that enables users to author workflows and DAGs with well-thought-out features:
- Concurrency and parallelism
- Native integration with team management, ACL, and RBAC rules
- Native support for ML workload: Kubeflow Operators, Hyperparameter tuning, Spark jobs, Dask Jobs...
Polyaxon exposes an ensemble of hyperparameter tuning algorithms that can effectively optimize any model.
Our optimization engine is based on open-source tools, and can intelligently choose the best parameters for your problem by balancing exploration and exploitation of your parameter search space to obtain high-performing results.
With the robust scheduling provided by the platform, you can fully leverage and maximize your cluster resources and compute infrastructure, to run a high number of parallel jobs and optimize experiments across up to thousands of workers.
Polyaxon components can be developed by anyone, we share some generic components in an open-source public hub, and we welcome users to contribute more components.
And since Polyaxon's core is open-source, built as a JSON API, has webhooks, and gives you full control over your container workload: It essentially integrates with absolutely everything. Some things are easier than others, but almost anything is possible with a little scripting.
You can browse our directory of integrations with instructions, or build any custom integration yourself.
Polyaxon provides an event based abstraction to alter the internal work, and so you can build your own scheduler for example.
Deploy Polyaxon with sensible user roles and permissions from the start.
- Outsiders: Outsider is a person who isn't explicitly a member of your organization, but who has Read, Write, or Admin permissions to one or more projects in your organization.
- Viewers: Viewers can view experiments/jobs/services, as well as view most other data within the organization.
- Members: Members can view and act on experiments/jobs/services, as well as view most other data within the organization.
- Admins: Admin privileges on any teams of which they're a member. They can create new teams and projects, as well as remove teams and projects which they are already admin of.
- Managers: Gains admin access on all teams as well as the ability to add and remove members.
- Owners: Gains full permission across the organization. Can manage members as well as perform catastrophic operations such as removing the organization.
Polyaxon also comes with a concept called
Team that allows you to promote a user role on specific teams,
e.g. an organization wide viewer can have the member or admin role on a specific team.
All projects that authorize that team will give the additional permissions to that user with the global viewer role.
Polyaxon supports several scheduling strategies based on node management and queues routing. Queues in Polyaxon provides an abstraction to manage how your resources can be accessed, every queue has a priority and a concurrency limit.