*RRP - Reseller Recommend Price. Prices may vary based on local reseller.Prices provided in quotes by local resellers may vary.Show MoreShow Less
Loading...
https://connect.hpe.com/e/f2?nocache
en
Our system could not confirm your address to be valid and cannot find a recommended alternative. It is strongly recommended that you edit the address and try again. You may also continue with the address as you entered it if you are sure it is correct.
Provided User Id doesn't have access to this country, Please try sign in to authorized country partner portal.
Partner doesn’t have any country associated. Please contact System administrator.
Your Email/Password combination is incorrect. Please try again.
We've identified you as an Partner Store customer accessing HPE Storefront. Please 'click here' to log in to the Partner Store.
We've identified you as an HPE storefront customer accessing the Partner Store. Please 'click here' to log in to the HPE storefront.
Login Error
The requested account is an existing enterprise account. Please click here to login to enterprise store.
Sign-in Error
The associated account is connected to an employee profile. Please either register or use an alternative account to log in to the storefront.
Thank you for filling out your profile information. To complete your registration, please check your inbox for an email from Hewlett Packard Enterprise (HPE) and follow the validation steps.
Much like pre-DevOps software development, data science organizations still spend a significant amount of time and effort when moving projects from development to production. Model version control and code sharing is manual, and there is a lack of standardization on tools and frameworks, making it tedious and time-consuming to productize machine learning models.
HPE Ezmeral Machine Learning Ops (HPE Ezmeral ML Ops) extends the capabilities of the HPE Ezmeral Runtime Enterprise and brings DevOps-like agility to enterprise machine learning. With the HPE Ezmeral ML Ops, enterprises can implement DevOps processes to standardize their ML workflows.
HPE Ezmeral ML Ops provides data science teams with a platform for their end-to-end data science needs with the flexibility to run their machine learning or deep learning (DL) workloads on-premises, in multiple public clouds, or a hybrid model and respond to dynamic business requirements in a variety of use cases.
Get Started
Pricing displayed for the products does not include applicable taxes and shipping.
KubeFlow 1.3 (security hardened)? and Model Monitoring
Spark Operator Add-on, Spark History Server, Spark Thrift Server, Apache Livy and Hive Metastore
Delta Lake support
Spark versions supported: Apache Spark 2.4.7 and Apache Spark 3.1.2
HPE Ezmeral Runtime Analytics for Apache Spark
Introducing HPE Ezmeral Runtime Enterprise New UI with ?Enhanced UX: improved UX for data scientists?; Packaged libraries for simplified coding experience and Notebook magics for KubeFlow
Faster Time to Value
Manage and provision infrastructure through an intuitive graphical user interface.
Provision development, test, or production environments in minutes as opposed to days.
Onboard new data scientists rapidly with their choice of tools and languages without creating siloed development environments.
Improved Productivity
Data scientists spend their time building models and analyzing results rather than waiting for training jobs to complete.
HPE Ezmeral Runtime Enterprise helps ensure no loss of accuracy or performance degradation in multi-tenant environments.
Increase collaboration and reproducibility with shared code, project and model repositories.
Reduced Risk
Enterprise-grade security and access controls on compute and data.
Lineage tracking provides model governance and auditability for regulatory compliance.
Integrations with third-party software provides interpretability.
High-availability deployments help ensure critical applications do not fail.
Flexible and Elastic
Deploy on-premises, cloud, or in a hybrid model to suit your business requirements.
Autoscaling of clusters to meet the requirements of dynamic workloads.
Kubernetes ® is a registered trademark of the Linux Foundation in the United States and other countries, and is used pursuant to a license from the Linux Foundation. LINUX FOUNDATION and YOCTO PROJECT are registered trademarks of the Linux Foundation.
Get advice, answers, and solutions when you need them. For general questions, email us at hpestore.quote-request@hpe.com
Find what you are looking for?
Need help locating the right product for your business?
Our product experts would love to chat with you to find products and services that enable opportunities and resolve your business problems.
*All pricing displayed is indicative; the reseller sets the final transactional price and may include other fees such as sales tax/VAT and shipping. The transactional price set by the reseller may vary from other resellers and the indicative price displayed. Indicative pricing may include limited-time promotional offers. HPE reserves the right to make pricing adjustments at any time for reasons including, but not limited to, changing market conditions, product discontinuation, restricted product availability, promotion end of life, and errors in advertisements.
