D2iQ Introduces Cloud Native Platform to Accelerate the Deployment of Machine Learning on Kubernetes

D2iQ Kaptain speeds time from prototype to production by eliminating the complexities of the underlying infrastructure to power successful machine learning deployments in Day 2 operations

D2iQ, provider of the leading independent Kubernetes platform built to power smarter Day 2 operations, announced the general availability of D2iQ Kaptain, the cloud native end-to-end platform for running machine learning (ML) workloads on Kubernetes. D2iQ Kaptain combines all of the open source components required to accelerate the development, training, tuning and deployment of ML models in the enterprise, cutting the time from prototype to production from months to minutes.

With data volumes growing exponentially, machine learning is no longer an option, but a necessity for digitally-driven organizations. However, many enterprises struggle when moving from a prototype on a single machine to a scalable production deployment. According to industry research, 87 percent of all artificial intelligence (AI) projects never make it into production. D2iQ Kaptain provides data scientists with a familiar, notebook-first approach that has been fully tested and integrated with all the shared resources and data access controls required to build and share models. This enables data scientists to manage the lifecycle of their machine learning models without a need for Kubernetes or production infrastructure knowledge. 

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D2iQ Kaptain is powered by an opinionated subset of Kubeflow, the open source machine learning toolkit for Kubernetes, while also including all of the Day 2 ready features provided by the D2iQ Konvoy Kubernetes distribution and additional production-focused components such as Horovod and Spark. This combination empowers platform operators and data scientists with a robust and enterprise-grade Kubernetes foundation. D2iQ Kaptain dramatically reduces the friction involved in training and deploying ML models in the enterprise, increasing production success rates while speeding time to value.

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“Moving ML workflows from prototype to scalable deployment is increasingly complex and challenging, often requiring significant resources and multiple months to reach production environments,” said Deepak Goel, CTO, D2iQ. “D2iQ Kaptain uniquely supports both data scientists and developer teams with an enterprise-grade, end-to-end ML solution capable of running Kubernetes anywhere, from on-premises to cloud and air-gapped environments. As pioneers in helping organizations navigate cloud native journeys, D2iQ Kaptain leverages our expertise and suite of Kubernetes solutions built for security, scale, flexibility and speed to ensure successful Day 2 operations”

D2iQ Kaptain delivers significant benefits for data scientists and DevOps teams:

• Machine Learning on any Infrastructure: D2iQ Kaptain can be deployed in any environment that ML initiatives take place including on-premise, air-gapped networks, on the public cloud, or in a hybrid or multi-cloud environment.
• Enterprise security and multi-tenancy: D2iQ Kaptain’s end-to-end secure enterprise-grade ML platform is integrated with Konvoy’s multi-tenancy, authentication, and identity services, allowing DevOps teams to run entire ML pipelines securely and efficiently.
• Deliver Models to Production with Speed and Agility: D2iQ Kaptain breaks down operational barriers for data scientists to seamlessly move models from prototype to production, ultimately improving project success rates and speeding time to implementation.
• Expert Support: D2iQ Kaptain offers expert support options with on-demand coverage to ensure that every machine learning initiative has advanced support and rapid response times.

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