Sold by: Waltsoft Inc.
Deployed on AWS
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Production-ready Jupyter web interface for Kubeflow ML pipelines. Streamlines machine learning workflow management, experiment tracking, and model deployment for data scientists and ML engineers.
Overview
Overview
Kubeflow ML Pipeline Dashboard provides a comprehensive web-based interface for managing machine learning workflows on Kubernetes. Built on the robust Jupyter ecosystem, it enables data scientists and ML engineers to create, monitor, and deploy ML pipelines at scale.
Features
- Interactive Jupyter notebook environment optimized for ML workflows
- Seamless integration with Kubeflow Pipelines for end-to-end MLOps
- Real-time pipeline monitoring and experiment tracking
- Multi-user support with role-based access control
- Pre-configured ML libraries and frameworks
- Kubernetes-native scaling and resource management
Getting Started
Deploy instantly on port 5000. The dashboard automatically connects to your Kubeflow cluster and provides immediate access to pipeline creation tools, experiment management, and model deployment capabilities. Perfect for teams looking to accelerate their ML development lifecycle.
Disclaimer: This software is open-source and distributed under its own licensing terms. It is not affiliated with, endorsed by, or sponsored by the upstream project maintainers. Provided "as is" without warranty. Users utilize this software at their own risk and are responsible for compliance with applicable regulations.
Disclaimer: This software is open-source and distributed under its own licensing terms. It is not affiliated with, endorsed by, or sponsored by the upstream project maintainers. Provided "as is" without warranty. Users utilize this software at their own risk and are responsible for compliance with applicable regulations.
Highlights
- Interactive Jupyter interface for ML pipeline development
- Real-time experiment tracking and monitoring
- Kubernetes-native scaling and multi-user support
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 24.04
Deployed on AWS
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Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Free trial
Try this product free for 5 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
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. Alternatively, you can pay upfront for a contract, which typically covers your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
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 | Description | Cost/hour |
|---|---|---|
t3.medium Recommended | t3.medium instance | $0.01 |
t3.micro | t3.micro instance | $0.00 |
t3.large | t3.large instance | $0.01 |
m5.large | m5.large instance | $0.01 |
r5.large | r5.large instance | $0.01 |
m5.xlarge | m5.xlarge instance | $0.01 |
Vendor refund policy
No refunds. Cancel anytime. Contact support@waltsoft.net .
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
Kubeflow ML Pipeline Dashboard by Waltsoft.
Additional details
Usage instructions
SSH in, then access Kubeflow at http://<public-ip>:5000
Support
Vendor support
For technical support, email support@waltsoft.net or visit
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.
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