LABINTERMEDIATE

Deploy Model with KServe

Deploy ML models using KServe serverless inference on Kubernetes.

60 minutes

ai-infrastructure/model-serving

Deploy Model with KServe - Platform Engineering Hands-On Lab Icon

Lab Overview

This hands-on lab teaches you to deploy ML models using KServe on Kubernetes.

You'll learn to:

Install KServe on a Kubernetes cluster
Deploy a scikit-learn model as an InferenceService
Configure autoscaling parameters
Test inference endpoints with the V1 prediction protocol

Prerequisites

kubernetes-fundamentals

ml-resource-quotas

Technologies Covered

kuberneteskservemodel-servinginferenceautoscalingsklearn

Part of a Course

This lab is part of the Model Serving and Kubernetes for ML course

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Content & Learning

Access to all courses and bootcamps
Video lessons with closed captions
Interactive quizzes and assessments
Course completion certificates

Hands-On Labs

Browser-based cloud labs
Pre-configured VMs ready to use
Playgrounds for experiments
Multi-VM realistic scenarios

AWS Integration

Managed AWS Account included
Pre-configured environments
Real-world cloud scenarios

Support & Community

Priority support
Active community forum

No Setup Required

Everything runs in your browser
No software installation needed
Automatic environment provisioning
Works on any device

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