
Save and reuse an experiment comparison
Save a Polyaxon comparison's query, columns, sorting and charts, reopen it for later runs, and share reusable searches and dashboards with your team.
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Save a Polyaxon comparison's query, columns, sorting and charts, reopen it for later runs, and share reusable searches and dashboards with your team.

Try container images, package versions and environment changes from the Polyaxon CLI, or start a sandbox without writing a Polyaxonfile.

Define jobs and services with top-level container, cmd, env, resources, and service in Polyaxon 2.18, while keeping existing Polyaxonfiles supported.

Compare six experiments at the same epoch, zoom across metric charts together, and configure tooltips with multiple live metric columns and run parameters.

Launch Dask or Ray clusters with Polyaxonfiles, submit repeated work, and control worker capacity, durable outputs, and cluster lifetimes.

Use Polyaxon's generated SSH host with native SCP and SFTP to move files into and out of a running service workspace.

Choose between sandbox shells and exec, understand PTY lifetime and output replay, and manage terminal attachment explicitly through the Python SDK.

Connect native terminals and IDEs to a Polyaxon service, forward application ports, and use tmux explicitly when you want to resume a shell.

Learn how ordinary ops shells differ from tmux sessions, then detach and reconnect to the same Polyaxon shell from the CLI or UI.

Use OR to combine metric thresholds, negated conditions, and independent groups of filters in Polyaxon queries.

Monitor several Polyaxon runs concurrently with async Python clients, retrieve recent logs, and manage concurrency, timeouts, and client cleanup.

Use direct parameter values, let input and output defaults imply optionality, and simplify workload definitions with Polyaxon 2.18.

Upload code, configuration, and small datasets in one Polyaxon CLI command, then save the same path mappings in a declarative mount section.

Start a sandbox-enabled Polyaxon service, upload two files, run a command, download its result, and release the workspace from the CLI.

Archive a Polyaxon sweep or DAG through its parent run, understand what happens to unfinished children, and restore retained records from Python.

Collect reports from several Polyaxon runs with bounded async downloads, fresh staging directories, content checks, and a receipt for every transfer.

Use one Polyaxon connection in a job and its custom sidecar, then decide when a sidecar should not inherit the run's mounts and credentials.

Keep a Polyaxon-managed Ray cluster available for repeated job submissions, with explicit resource settings, job identities, storage, and shutdown ownership.

Select a run cohort, save its UUIDs for review, and apply a ProjectClient bulk action to that explicit inventory without rerunning a changing query.

Use Polyaxon queue and agent statistics with run timelines to distinguish policy limits, workload changes, and Kubernetes placement problems before adding capacity.

Attach a private-registry pull secret to a Kubernetes ServiceAccount, select it for a Polyaxon operation, and verify the new Pod can use the intended image.

At Polyaxon, we're always looking for ways to push the boundaries of what's possible with machine learning infrastructure, this is why we are excited about the upcoming sandbox deployment capabilities.

The run control, i.e. cog icon, is now visible on all tabs to allow users to easily perform actions on a run

Polyaxon UI has new features that allows users to quickly compare and filter their runs