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Machine Learning Model Serving Patterns and Best Practices

You're reading from   Machine Learning Model Serving Patterns and Best Practices A definitive guide to deploying, monitoring, and providing accessibility to ML models in production

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Product type Paperback
Published in Dec 2022
Publisher Packt
ISBN-13 9781803249902
Length 336 pages
Edition 1st Edition
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Author (1):
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Md Johirul Islam Md Johirul Islam
Author Profile Icon Md Johirul Islam
Md Johirul Islam
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Table of Contents (22) Chapters Close

Preface 1. Part 1:Introduction to Model Serving
2. Chapter 1: Introducing Model Serving FREE CHAPTER 3. Chapter 2: Introducing Model Serving Patterns 4. Part 2:Patterns and Best Practices of Model Serving
5. Chapter 3: Stateless Model Serving 6. Chapter 4: Continuous Model Evaluation 7. Chapter 5: Keyed Prediction 8. Chapter 6: Batch Model Serving 9. Chapter 7: Online Learning Model Serving 10. Chapter 8: Two-Phase Model Serving 11. Chapter 9: Pipeline Pattern Model Serving 12. Chapter 10: Ensemble Model Serving Pattern 13. Chapter 11: Business Logic Pattern 14. Part 3:Introduction to Tools for Model Serving
15. Chapter 12: Exploring TensorFlow Serving 16. Chapter 13: Using Ray Serve 17. Chapter 14: Using BentoML 18. Part 4:Exploring Cloud Solutions
19. Chapter 15: Serving ML Models using a Fully Managed AWS Sagemaker Cloud Solution 20. Index 21. Other Books You May Enjoy

What is serving?

Serving is an important step for ensuring the business impact of the applications when we develop the life cycle of application development. The application we have developed needs to be available to the user so that they can use it. For example, let’s say we have developed a game. After the development, if the game just stays on the developer’s machine, then it is not going to be of any use to the users. So, the developer needs to bring the game to the users by serving it through a serving platform such as Apple Store, Google Play Store, and web servers.

So, serving can be seen as a mechanism to distribute our applications/services to end users. The end users can be different based on the applications/services we develop. Serving creates a bridge of communication between the two parties: the developer and the users. This bridge is vital for the business success of our application. If we don’t have people using our service, then we are not gaining any business value or impact from the applications we’ve developed. That’s what we have seen in the past when big corporate companies’ servers go down for some time: they incur a huge amount of loss. Facebook (Meta) lost ~65 million US dollars due to its outage for some hours in October 2021, as per Forbes: https://www.forbes.com/sites/abrambrown/2021/10/05/facebook-outage-lost-revenue/?sh=c1d7d03231ad.

The development-to-serving process usually forms the life cycle of the service or application.

For example, let’s consider the life cycle of web application development in Figure 1.1.

Figure 1.1 – Web development life cycle

Figure 1.1 – Web development life cycle

The developer develops the website. Then, the website is served using a web server. Only after that are the users able to use the website. The cycle can continue through collecting feedback from users, improving the website, and serving again on the web server.

Now we know what serving is, let’s look at what we are actually serving.

You have been reading a chapter from
Machine Learning Model Serving Patterns and Best Practices
Published in: Dec 2022
Publisher: Packt
ISBN-13: 9781803249902
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