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Joined November 2014

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DevopsCube
@devopscube
Aug 13
The MLOPS for DevOps repo is close to 500 stars 🚀 We started this series with a simple goal. To help DevOps engineers understand the key concepts and workflows required for MLOps. Because knowing just Terraform, cloud, and Kubernetes is not enough for MLOps. You need
DevopsCube
@devopscube
10h
Practical Guides and resources this week at DevOpsCube ☕ Read these 👇 1. Canary Vs Shadow Deployment vs. A/B Testing - linkedin.com/feed/update/ur… 2. MLflow to KServer: Deploying AI models on K8s - newsletter.devopscube.com/p/kserve 3. Model signature in MLFlow - linkedin.com/feed/update/ur…
DevopsCube
@devopscube
Aug 14
Kubernetes Tip 💡 When a pod starts, Kubernetes automatically adds environment variables based on the services in the same namespace. Because the enableServiceLinks is set to true by default in the cluster. These SVC variables follow a specific format:
DevopsCube
@devopscube
Aug 14
One of the interesting concepts in MLflow is model signature Every model expects inputs in a certain schema and format. If you pass inputs that don't match what the model expects, it may give the wrong predictions So how do you know what inputs the model expects? That's
DevopsCube
@devopscube
Aug 12
How does a trained AI model become a production API on Kubernetes? KServe is a CNCF incubating project for serving AI models on Kubernetes. Simply put, KServe takes a trained model and turns it into a scalable inference service on Kubernetes. It handles deployment,
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