canarydeployment

Shadow Deployment vs Canary Deployment for ML Models

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When deploying machine learning models to production, choosing the right deployment strategy can make the difference between seamless updates and catastrophic failures. Two of the most powerful approaches for safely rolling out ML models are shadow deployment and canary deployment. While both strategies aim to minimize risk and ensure model reliability, they operate on fundamentally … Read more

Canary Deployments for Machine Learning Models

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In the rapidly evolving landscape of machine learning operations (MLOps), deploying new models safely and efficiently has become a critical challenge that can make or break production systems. Traditional deployment strategies often involve significant risks, potentially exposing entire user bases to untested model behavior that could result in degraded performance, incorrect predictions, or complete system … Read more