On-premises cloud experience accelerates data science
HPE GreenLake for ML Ops makes it easier and faster to get started with ML/AI projects and seamlessly scale them to production deployments. Within your datacentre or colocation facility, deploy AL/ML workloads on HPE's ML-optimised cloud service infrastructure featuring HPE Apollo hardware powered by HPE Ezmeral ML Ops – a solution that is designed to address all aspects of ML lifecycle, from data preparation to model building, training, deployment, monitoring and collaboration. HPE GreenLake offers consumption-based pricing, allowing you to consume these resources on premises with a cloud experience.
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Solve for operational risk and data gravity issues
Avoid the compliance, security and data gravity issues of public cloud, and the operational risk of running the infrastructure yourself. Workloads run right next to your on-premises data lake letting you avoid hidden costs for data egress.
Empower data scientists
Let your data scientists focus on building models and not managing and configuring infrastructure. With HPE GreenLake for ML Ops, you can quickly spin up containerised ML/AI environments with your choice of data science tooling and assign projects to data scientists.
Enjoy elastic pricing and cost monitoring
Reserve the capacity you need and pay-per-use for the resources you consume. With the ability to view your metered usage and associated costs, you can tie usage to specific business objectives.
Secure provisioning and management
Offload monitoring and management of your Data Science environment. With HPE GreenLake for ML Ops, your environment is securely managed from HPE IT Operations Centres, and through HPE GreenLake Central security services.
HPE GreenLake for ML Ops
Run your ML workloads with the security and control that an on-premises infrastructure provides. Pick from 2 configurations – Standard and Performance Optimised – that are built on an enterprise-grade high-performing hardware/software stack optimised for machine learning. Featuring consumption-based billing, this service provides:
- Simple, transparent pricing model delivering on-premises service as operational expense.
- Elasticity to support unpredictable workloads.
- Reserved capacity + usage-based consumption model drives pricing predictability while supporting variable demand typical of data science workloads.
- 4 year contract, paid monthly.
GET THE DETAILS
| | Standard Configuration | Performance Optimised Configuration |
|---|---|---|
| Who is this recommended for | Companies with a data science team who want to use artificial intelligence and machine learning to solve business problems and need to run ML/AI workloads in an agile and secure manner on premises, without having to manage the infrastructure. | Companies with a data science team who are training deep learning models at scale, putting models into production or are running multiple data science projects concurrently on premises. |
| Hardware specifications |
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| Software stack | HPE Ezmeral Container Platform and ML Ops software, including a set of 5 pre-configured data science app images with the option to customise. These images contain a variety of open source data science tools, languages and CI/CD tooling and are designed for data ingestion, data prep, model training, model deployment and notebooks. | HPE Ezmeral Container Platform and ML Ops software, including a set of 5 pre-configured data science app images with the option to customise. These images contain a variety of open source data science tools, languages and CI/CD tooling and are designed for data ingestion, data prep, model training, model deployment and notebooks. |
| Control plane | Secure, self-serve provisioning and management via a common control plane for the HPE Container Platform and HPE GreenLake Central orchestration. | Secure, self-serve provisioning and management via a common control plane for the HPE Container Platform and HPE GreenLake Central orchestration. |
| What is metered | Usage is metered based on the compute (per minute) and storage (per GB) used by the nodes in a cluster. There are 4 meters used to calculate usage over the reserved capacity.
| Usage is metered based on the compute (per minute) and storage (per GB) used by the nodes in a cluster. There are 4 meters used to calculate usage over the reserved capacity.
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| Incuded services |
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SAMPLE STANDARD CONFIGURATION PRICING:
LOW RESERVE
Most flexibility
Includes:
- Reserve utilisation: 50%
- Storage: 114,000 GB
- Usable core CPU hours: 35,064
- V100 GPU hours: 1,461
- T4 GPU hours: 1,461
Base monthly price:
$20,383
Additional Storage: $0.103/GB-mo
Additional CPU: $0.096/CPU-hr
Additional V100 GPU: $2.768/GPU-hr
Additional T4 GPU: $0.858/GPU-hr
BALANCED
Most popular
Includes:
- Reserve utilisation: 70%
- Storage: 159,600 GB
- Usable core CPU hours: 49,090
- V100 GPU hours: 2,045
- T4 GPU hours: 2,045
Base monthly price:
$26,320
Additional Storage: $0.095/GB-mo
Additional CPU: $0.088/CPU-hr
Additional V100 GPU: $2.553/GPU-hr
Additional T4 GPU: $0.791/GPU-hr
HIGH RESERVE
Most cost-efficient
Includes:
- Reserve utilisation: 90%
- Storage: 205,200 GB
- Usable core CPU hours: 63,115
- V100 GPU hours: 2,630
- T4 GPU hours: 2,630
Base monthly price:
$31,215
Additional Storage: $0.088/GB-mo
Additional CPU: $0.081/CPU-hr
Additional V100 GPU: $2.355/GPU-hr
Additional T4 GPU: $0.730/GPU-hr
SAMPLE PERFORMANCE CONFIGURATION PRICING:
LOW RESERVE
Most flexibility
Includes:
- Reserve utilisation: 50%
- Storage: 197,000 GB
- Usable core CPU hours: 43,830
- V100 GPU hours: 2,922
- T4 GPU hours: 1,461
Base monthly price:
$33,810
Additional Storage: $0.103/GB-mo
Additional CPU: $0.096/CPU-hr
Additional V100 GPU: $2.768/GPU-hr
Additional T4 GPU: $0.858/GPU-hr
BALANCED
Most popular
Includes:
- Reserve utilisation: 70%
- Storage: 275,800 GB
- Usable core CPU hours: 61,362
- V100 GPU hours: 4,091
- T4 GPU hours: 2,045
Base monthly price:
$43,660
Additional Storage: $0.095/GB-mo
Additional CPU: $0.088/CPU-hr
Additional V100 GPU: $2.553/GPU-hr
Additional T4 GPU: $0.791/GPU-hr
HIGH RESERVE
Most cost-efficient
Includes:
- Reserve utilisation: 90%
- Storage: 354,600 GB
- Usable core CPU hours: 78,894
- V100 GPU hours: 5,260
- T4 GPU hours: 2,630
Base monthly price:
$51,777
Additional Storage: $0.088/GB-mo
Additional CPU: $0.081/CPU-hr
Additional V100 GPU: $2.355/GPU-hr
Additional T4 GPU: $0.730/GPU-hr
Prices are estimates and are not intended as actual price quotes. Actual prices may vary depending upon the date of purchase, currency of payment and type of agreement you enter with HPE. Contact a HPE sales representative for additional information on pricing.
TECHNICAL RESOURCES
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