Clusterone

The Clusterone Deep Learning Platform

A Serverless AI Operating System for Data Scientists

Created by Data Scientists for Data Scientists


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Deep learning scientists are rare and can be difficult to recruit. So when an organisation succeeds in assembling a team of them, the prime goals should be to keep them productive and motivated. Clusterone:

Yet because their teams are small, they often get overlooked when it comes to technical help in setting up the optimal infrastructure for their work.

features graphic takes the pain and lost time out of provisioning resources, deploying clusters, creating orchestrations, and managing projects.
features graphic helps organizations maximize the efficiency of their deep learning scientists, while enhancing the satisfaction of these scientists by off-loading tedious but essential tasks.
features graphic helps organizations to get the maximum value from their hardware resources.

Clusterone’s Elastic GPU Scheduler detects unused processors and makes them available to others on the team when working with on-premises boxes. When working in the cloud, Clusterone’s dynamic scheduling and auto-scaling can spin up and spin down resources. This means scientists always have the resources their work requires without incurring billing for idle hardware instances.

“Devopsbay team likes to do everything perfectly”

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The Devopsbay was Clusterone's tech partner and was responsible for tech delivery. The platform frontend, backend, cloud infrastructure and support was done by our team.The primary challenge of the platform was software orchestration using Kubernetes, cloud deployment, and automation. The platform was hosted on-premise and on AWS. Our team also deployed and supported the software for a number of on-prem customers:

The project was very technically advanced at the time - we had to use a huge stack of technologies. To name the few:

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Programming Languages
Python, Go, Javascript, Typescript
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Frameworks
Flask, FastApi, Celery, NodeJs, Web.go, React.js, Redux
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CI/CD
CircleCi, Our inhouse build system
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Message bus and queues
RabbitMq, Redis
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Databaes
PostgresSQL, Aurora
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Distributed Storage
EFS, EBS, S3, Ceph
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Monitoring
Prometheus, Loki , Grafana, Zabbix (for VM part)
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Technologies
Kubernetes, Docker, Ansible, Terraform, Helm, Chef
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Cloud Providers
AWS, GCP, Azure
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