Transfer files to Polyaxon workspaces over SSH
Use Polyaxon's generated SSH host with native SCP and SFTP to move files into and out of a running service workspace.
ProductCliRemote Development
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Practical guides to building, running, and improving ML and AI in production.
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Train a decision classifier on Polyaxon
Fine-tune an open Qwen model for bounded support-routing decisions with Polyaxon jobs, track the adapter, and serve the reviewed version through vLLM.
LLMOpsFine TuningClassification
Deploy Laya typed decisions on Polyaxon
Serve the open Laya typed-decisions checkpoint through Polyaxon, with a CPU classifier endpoint, explicit model scope, and a review path for uncertain classifications.
LLMOpsInferenceClassification
Serve a Jev-style Qwen classifier on Polyaxon
Deploy an open Qwen model behind a typed classification API on Polyaxon, then check the decision schema and calibration before routing real work.
LLMOpsInferenceClassification
Serve DiffusionGemma on Polyaxon
Adapt Google's Gemma-on-Kubernetes deployment choices to Polyaxon with a DiffusionGemma vLLM service, a batch evaluation job, and an explicit compatibility checklist.
LLMOpsInferenceKubernetes
Run background commands in Polyaxon sandboxes
Start a background process, save its execution ID, reconnect to status and logs, and distinguish command limits from the lifetime of a Polyaxon sandbox.
PolyaxonSandboxesPython
Schedule mapped runs in the order you specify
Use an ordered Polyaxon mapping for a curated list of experiments, control concurrency, and distinguish scheduling order from dependencies and completion order.
PolyaxonOrchestrationExperimentation
Separate evaluator changes from application improvements
Compare old and new application outputs under both evaluator versions, inspect changed decisions, and retain the four comparisons in Polyaxon.
LLMOpsEvaluationExperimentation
Make vLLM prefix caching work for repeated prompts
Understand exact prefix reuse in vLLM, structure repeated context, account for replica routing, and compare cold and warm workloads with Polyaxon.
LLMOpsInferencevLLM
Resize CPU and memory without replacing Kubernetes Pods
Use Kubernetes in-place resource resizing for running workloads, inspect whether changes took effect, and understand the limits for Polyaxon services.
KubernetesSchedulingResources
Native gang scheduling reaches beta in Kubernetes 1.37
Explore native gang scheduling in Kubernetes 1.37, its potential for Polyaxon training and sandboxes, and how it compares with KAI, Kueue, and Volcano.
KubernetesSchedulingDistributed Training
Keep failed candidates visible in pipeline reports
Reconcile evaluation results against an expected candidate manifest, preserve failed and missing outcomes, and separate pipeline reporting from release approval.
MLOpsOrchestrationEvaluation
Work inside a team from Python and the CLI
Scope Polyaxon Python clients and CLI commands to a team, review runs across its projects, and keep explicit project targets and saved defaults clear.
PolyaxonTeamsPython
Design a search space before launching the sweep
Use Polyaxon matrices to choose parameter scales, separate meaningful combinations, and control the size of a hyperparameter sweep.
Hyperparameter TuningMLOpsExperimentation
Version the dataset behind every evaluation
Use Polyaxon data references, artifact logging, and registered versions to retain the dataset and split behind each evaluation.
DataOpsMLOpsLLMOps
Keep distributed training workers close together
Understand native topology-aware workload scheduling, combine rack locality with gang placement, and assess the tradeoff between waiting and communication.
KubernetesSchedulingDistributed Training
Resume interrupted training without losing progress
Build recoverable PyTorch training jobs with complete checkpoints, durable storage, and explicit restoration. Practice recovery locally and with Polyaxon.
MLOpsKubernetesPyTorch
Work interactively with Polyaxon sandboxes
Choose between sandbox shells and exec, understand PTY lifetime and output replay, and manage terminal attachment explicitly through the Python SDK.
ProductCliGuides
Did you find better hyperparameters—or a lucky seed?
Confirm hyperparameter finalists across matched training seeds, compare variation and paired differences, and reserve compute for a defensible final choice.
Hyperparameter TuningMLOpsExperimentation
Connect your local tools to Polyaxon with SSH
Connect native terminals and IDEs to a Polyaxon service, forward application ports, and use tmux explicitly when you want to resume a shell.
ProductCliGuides
Prevent data leakage in ML and LLM evaluation datasets
Choose evaluation boundaries, keep related examples together, audit duplicate overlap, and retain reproducible split manifests for ML and LLM experiments.
DataOpsMLOpsLLMOps
Keep long-running workloads authenticated through token rotation
Use projected ServiceAccount tokens and refresh-aware clients so long-running training, notebooks, and services can keep authenticating without static credentials.
KubernetesSecurityReliability
Reconnect to your Polyaxon shell
Learn how ordinary ops shells differ from tmux sessions, then detach and reconnect to the same Polyaxon shell from the CLI or UI.
ProductCliGuides
Enforce ML workload rules with CEL admission policies
Use Kubernetes ValidatingAdmissionPolicy to check workload ownership and image references, with scoped warning and enforcement stages for ML namespaces.
KubernetesGovernanceSecurity