Datarobot, a leader in AI, needed a unified infrastructure for its applications. The project included consolidation of services, migration of infrastructure, and implementation of advanced DevOps solutions so that all products offered by this company use the same infrastructure.
It specialises in developing AI platforms and applications that help organisations maximise the impact and minimise the risks associated with implementing artificial intelligence. Datarobot serves a variety of industries, including energy, financial services, healthcare, manufacturing and the public sector, offering solutions tailored to the specific needs of each sector.
The three main solutions offered by Datarobot are:
AI Platform - a comprehensive tool for creating, deploying and managing AI models, supporting both generative and predictive AI. AI Application - ready-to-use AI applications that integrate with key business processes, enabling teams to effectively use AI in day-to-day operationsAutomated machine learning - A platform that automates the complex steps of the machine learning process, enabling the rapid building and deployment of predictive models. Stability and performance under increasing load without additional costs.
Kubernetes cluters in three major regions -Single-client clustering processesUnification of the platformEffective resources managementDeployment and management of 6 production clusters in the US, EU and Japan, ensuring high availability and performance for users worldwide.
Create processes to enable single clusters for customers on Azure and GCP platforms, increasing the flexibility of the offering.
Consolidation of all DataRobot services on a common infrastructure, which has simplified management and reduced operating costs.
Implementation of advanced auto-scaling mechanisms using Karpenter, ensuring optimal use of resources and cost control
Deployment and management of 6 production clusters in the US, EU and Japan, ensuring high availability and performance for users worldwide.
Significant reduction in operational expenditure through consolidation of services and efficient management of resources through automatic scaling.
Management of 6 production clusters in 3 regions of the world has ensured high availability and reliability of DataRobot services
Strategic deployment of clusters in the US, EU and Japan has minimised delays for end users, providing faster access to services
Expanding the platform to include Azure and GCP has enabled the offering to be tailored to a wider range of customers and their specific infrastructure requirements
Consolidation of services on a common infrastructure has significantly simplified operational processes and reduced the complexity of managing the platform
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