End-to-End AI Development & Deployment with the JRAK Stack

How Drizzle:AI Integrates with the JRAK Stack

Drizzle provides a seamless, production-ready implementation of the JRAK Stack, a powerful combination of open-source tools for the complete AI lifecycle. We expertly integrate Jupyter, Argo, and Ray on a secure Kubernetes foundation (EKS, AKS, or GKE). This creates a single, unified platform for your team to move from interactive experimentation to scalable, production-grade deployment without the friction of fragmented tooling.

Key Features of the Integration

Interactive Development at Scale (Jupyter & Ray): Empower your data scientists with Jupyter Notebooks integrated directly with Ray, allowing them to seamlessly scale from local experimentation to large, distributed compute clusters without leaving their familiar environment.
Robust Workflow Orchestration (Argo Workflows): Automate and manage your entire ML lifecycle, from data processing and model training to evaluation, using Argo Workflows to create robust, repeatable, and observable pipelines.
Scalable Serving & Deployment (Ray Serve & Argo CD): Deploy your models into production with confidence using Ray Serve for scalable online inference and Argo CD for declarative, GitOps-based continuous deployment to your Kubernetes cluster.
A Unified End-to-End Platform: The JRAK stack provides a single, cohesive platform that eliminates tool fragmentation. Drizzle integrates these components to provide your team with a seamless, end-to-end solution for both development and operations.