Today there are several public cloud providers in the industry that we can choose from and where we can upload our mission-critical business applications, but there are certain features that not all public cloud providers can deliver, and that is why we want to present the cloud hybrid of the manufacturer HPE (Hewlett Packard Enterprise), in what follows a brief summary.

HPE EZmeral is a hybrid cloud purpose-built platform for data science and analytics workloads.

It builds and accelerates modern data analytics initiatives at scale with a full, orchestrated Kubernetes container platform, along with a built-in persistent storage layer, and also operationalizes machine learning (ML Ops) for data science workloads.

The ability to apply artificial intelligence (AI) and machine learning (ML) to unlock Knowledge from data represents a key competitive advantage for companies of nowadays. Today’s modern businesses understand the benefits that learning automatic can offer and want to expand its use. However, as they try operationalize their machine learning models, they face last-minute problems hours related to the implementation and management of the model.

HPE Ezmeral ML Ops offers a DevOps-like speed and agility to the machine learning lifecycle and empowers to large companies to overcome the barriers of implementation and operationalization of artificial intelligence and machine learning across the organization.

Challenges

Similar to pre-DevOps software development, most data science organizations today lack streamlined processes for their machine learning workflows, causing many data science projects to fail. This, in turn, prevents the implementation of the model in current applications and business processes.

HPE Ezmeral ML Ops helps enterprises overcome these challenges, with an open source platform that offers a cloud-like experience combined with pre-packaged tools to operationalize machine learning, from pilot to production.

Coverage

The HPE Ezmeral ML Ops solution supports all stages of the machine learning lifecycle: from data preparation to model creation, model training, model deployment, collaboration, and monitoring.

HPE Ezmeral ML Ops is a global data science solution that has the flexibility to run workloads on-premises, across multiple public clouds, or in a hybrid model, as well as respond to dynamic business needs across a wide range of use cases.

Architecture

Hybrid architecture contemplates extreme (edge), on-premise and the cloud.

HPE Ezmeral ML Ops Platform Architecture

HPE Ezmeral ML Ops platform architecture

Characteristic

One of the key features of HPE EZmeral ML Ops is that it addresses the entire machine learning (ML) cycle, from data preparation to model creation, training, deployment, and monitoring

Advantage

Some main benefits are: Faster profit time, improved productivity, risk reduction, flexibility and elasticity.

Contact

Mario Avilés

[email protected]

Movil: +569 9999 2650