Shadow-Deployments

Shadow deployments are a strategy used in machine learning and software development to test new model versions or application updates without impacting the user experience. In this approach, a new model, referred to as the shadow variant, runs alongside the existing production model, capturing a portion of the incoming requests. This allows developers to evaluate the performance of the new model in real-time while the production model continues to serve users. By analyzing the results from the shadow variant, teams can ensure that any potential issues are identified before fully transitioning to the new model, thereby minimizing risks and downtime.

Shadow Deployment of ML Models With Amazon SageMaker

 Towards AI

Validate the performance of new ML models by comparing them to production models with Amazon SageMaker shadow testing AWS has announced the shadow model deployment strategy support in Amazon SageMaker...

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Deployment Strategies

 Level Up Coding

When it comes to deployment, one major question you may have is what deployment pattern (strategy or type) I should pick. Some of the strategies are quick to implement but have a lot of downsides, whi...

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Zero-downtime deployments

 Software Architecture with C plus plus

There are two common ways to minimize the risk of downtime during deployments: blue-green deployments and canary releases . You can use the Envoy sidecar when introducing any of those two.

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Deployments Concepts

 FastAPI Documentation

Deployments Concepts When deploying a FastAPI application, or actually, any type of web API, there are several concepts that you probably care about, and using them you can find the most appropriate ...

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Deployment

 Full Stack Python

Web application deployment involves packaging and running your app on a server. Learn more about deployments on Full Stack Python.

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Deployment and operational views

 Software Architecture with C plus plus

If you have a non-standard or complex deployment environment, such as specific needs with regard to hardware, third-party software or networking requirements, consider documenting it in a separate dep...

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Six Deployment Strategies

 Javarevisited

Over this article, we are discussing different deployment strategies. Different organizations using different deployment strategies based on different factors such as cost savings, downtime management...

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📝 Guest post: The Rise of Shadow AI*

 TheSequence

In TheSequence Guest Post our partners explain in detail what ML and AI challenges they help deal with. In this article, Fara Hain from Run:ai discusses the problem of ‘shadow AI’ – when siloed teams ...

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Shadowfier

 Level Up Coding

Generating authentic product shadows using image-processing photo by @kadircelep on unsplash.com Recently, I have been working on a problem statement to generate studio-style product catalogue images...

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Deploy

 CherryPy Documentation and Tutorials

Deploy CherryPy stands on its own, but as an application server, it is often located in shared or complex environments. For this reason, it is not uncommon to run CherryPy behind a reverse proxy or us...

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Deployment - Intro

 FastAPI Documentation

Deployment - Intro Deploying a FastAPI application is relatively easy. What Does Deployment Mean To deploy an application means to perform the necessary steps to make it available to the users . For ...

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Deployment Options

 Flask User's Guide

Deployment Options While lightweight and easy to use, Flask’s built-in server is not suitable for production as it doesn’t scale well. Some of the options available for properly running Flask in produ...

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