Persistent Storage Solutions

Kubernetes clusters require persistent storage. Containers have never been designed to be persistent, but enterprises need the persistence to change loads, keep state use more hardware for different loads, etc. DevOps engineers, storage engineers nor application developers are not DBAs or data managers, making the use of Kubernetes very complicated.

Hammerspace provides the Active-Active geo-spanning Namespace to support persistent storage solutions in a hybrid/multi-cloud mobility model.

Business Value

Global access to billions of files across the hybrid cloud demands a unique approach to data orchestration – a continuous market economy simulation between real data and available infrastructure resources run by machine learning. The model treats storage services as landlords with resources to lease, and data files as tenants who spend limited currency to meet specific needs.

Hammerspace continuously collects performance telemetry from workloads for each file accessed, in the form of metadata. This monitoring provides a rich understanding of how the infrastructure is performing, so Hammerspace can automatically correct for issues before they happen. Real-time decisions for data placement are fully automated by machine learning, balancing performance and cost across the hybrid cloud.

How It Works

Active-Active Geo-spanning Namespace provides the technical foundation enabling persistent storage solutions to be effective in a hybrid model.

As a Metadata-as-a-Service solution, Hammerspace alone matches Kubernetes hyper-scaling ability, ignoring storage and location silos, enabling all the benefits of using Kubernetes

Security and Compliance
The dynamic and stateless nature of Kubernetes workloads poses difficulties when determining user access privileges to applications running in Kubernetes. The main security issue with storage for Kubernetes is maintaining access control and authorization privileges to ensure that only the relevant containers and services have access to sensitive data.
Hammerspace, through policy and automation, can maintain awareness of all workloads, no matter how large or small, ephemeral or static.

Data-as-a-Service

Hammerspace virtualizes and abstracts data from the infrastructure using machine learning, creating the agility required to provide File Data-as-a-Service to any application or data service.

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