Sold by: pCloudHosting LLC
Deployed on AWS
AWS Free Tier
This product has charges associated with it for seller support.Polyaxon 2.12.0 is a self-hosted MLOps platform for Kubernetes that enables machine learning experiment tracking, workflow orchestration, model management, and scalable AI workload execution through a web interface and command-line tools.
Overview
Polyaxon 2.12.0 is a self-hosted MLOps and AI orchestration platform designed to run on Kubernetes, enabling organizations to manage the complete machine learning lifecycle from a centralized environment. It provides tools for experiment tracking, workflow automation, model management, resource scheduling, and scalable execution of machine learning workloads across cloud and on-premises infrastructure.
The platform helps data scientists, machine learning engineers, and DevOps teams streamline AI development by offering reproducible experiments, distributed training, automated pipelines, and comprehensive monitoring capabilities. Polyaxon supports containerized workloads and integrates with Kubernetes to efficiently utilize computing resources while maintaining operational consistency.
Features of Polyaxon 2.12.0:
- Centralized management of machine learning experiments, jobs, and workflows.
- Experiment tracking with metrics, logs, artifacts, and reproducibility support.
- Workflow orchestration for training, validation, deployment, and automation pipelines.
- Kubernetes-native architecture for scalable and reliable workload execution.
- Resource scheduling and optimization for CPUs, GPUs, and distributed workloads.
- CLI and web-based interface for administration and operation management.
- Model lifecycle management and artifact storage integration.
- Monitoring, reporting, and operational insights for machine learning projects.
- Multi-user collaboration and access control capabilities.
- Support for cloud, hybrid, and on-premises deployments.
Polyaxon 2.12.0 is widely used by organizations seeking a scalable and production-ready platform for managing machine learning operations, improving experiment reproducibility, and accelerating AI development workflows.
Highlights
- Kubernetes-native MLOps platform for orchestrating, tracking, and scaling machine learning workloads across cloud and on-premises environments.
- Provides experiment tracking, workflow automation, resource scheduling, and model lifecycle management through both web-based and command-line interfaces.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 26.04
Deployed on AWS
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
If you are an AWS Free Tier customer with a free plan, you are eligible to subscribe to this offer. You can use free credits to cover the cost of eligible AWS infrastructure. See AWS Free Tier for more details. If you created an AWS account before July 15th, 2025, and qualify for the Legacy AWS Free Tier, Amazon EC2 charges for Micro instances are free for up to 750 hours per month. See Legacy AWS Free Tier for more details.
Dimension | Cost/hour |
|---|---|
m4.large Recommended | $0.03 |
t3.micro | $0.03 |
t2.micro | $0.01 |
t2.large | $0.03 |
t3.large | $0.03 |
r4.large | $0.03 |
r3.large | $0.03 |
t3.nano | $0.03 |
t2.2xlarge | $0.03 |
t2.medium | $0.03 |
Vendor refund policy
no Refund
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Packaged with latest updates as of June/2026
Additional details
Usage instructions
<section><p>Connect to your instance via SSH using the username <b>ubuntu</b>. For SSH connection instructions, visit: <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/AccessingInstancesLinux.html></p><p>Run the following commands:</p><pre>sudo su
mkdir -p ~/opy
cd ~/opy
python3 -m venv venv
source venv/bin/activate
polyaxon --version</pre><p>To view available Polyaxon CLI commands:</p><pre>polyaxon --help</pre><p>To verify Kubernetes deployment status:</p><pre>kubectl get nodes
kubectl -n polyaxon get pods
kubectl -n polyaxon get svc</pre><p>To verify Helm deployment:</p><pre>helm list -n polyaxon</pre><p>Polyaxon 2.12.0 is a Kubernetes-native MLOps platform that includes both a command-line interface and a web-based management environment for orchestrating machine learning workloads, tracking experiments, and managing AI pipelines.</p></section>
Support
Vendor support
Feel free to reach out anytime. Our support team is available 24x7 for assistance. Email: anant.shahi@pcloudhostings.com Website:
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Similar products
This product has charges associated with it for seller support. Polyaxon is an open source platform for building, training, and managing machine learning and deep learning models at scale, supporting both Kubernetes and Docker based deployments.
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