Overview
AiStreamliner connects every step: from managing your data to training, tracking, and deploying model all in one place. Built on Kubernetes, it scales easily, works with all major cloud providers, and keeps your workflows secure and organized. Kubeflow: Workflow orchestration and training MLflow: Experiment tracking and model registry KServe: Model serving and inference LakeFS: Data version control
Highlights
- Complete open-source LLMOps and MLOps platform. End-to-end workflow integration
- Kubernetes-based for scalable deployment
- Platform agnostic design
Details
Unlock automation with AI agent solutions

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Delivery details
AI Streamliner
- Amazon EKS Anywhere
Container image
Containers are lightweight, portable execution environments that wrap server application software in a filesystem that includes everything it needs to run. Container applications run on supported container runtimes and orchestration services, such as Amazon Elastic Container Service (Amazon ECS) or Amazon Elastic Kubernetes Service (Amazon EKS). Both eliminate the need for you to install and operate your own container orchestration software by managing and scheduling containers on a scalable cluster of virtual machines.
Version release notes
Initial Release
Additional details
Usage instructions
Please ensure you have a kind cluster running locally prior to installation. Instructions can be found here: https://github.com/ArdentMC/ai-streamliner . A cluster can easily be made with the make cluster command.
An installation can then be initiated with the following command after ensuring you are in the proper Kubernetes context. docker run --rm -v $(pwd)/output:/output 709825985650.dkr.ecr.us-east-1.amazonaws.com/ardent-mc/aistreamliner:1.0.3 && cd output && ./deploy-ai-streamliner.sh
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Vendor support
Premium Support: aistreamliner@ardentmc.comÂ
AWS infrastructure support
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