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Serverless Architectures with Kubernetes

Serverless Architectures with Kubernetes

By : Onur Yılmaz , Sathsara Sarathchandra
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Serverless Architectures with Kubernetes

Serverless Architectures with Kubernetes

By: Onur Yılmaz , Sathsara Sarathchandra

Overview of this book

Kubernetes has established itself as the standard platform for container management, orchestration, and deployment. By learning Kubernetes, you’ll be able to design your own serverless architecture by implementing the function-as-a-service (FaaS) model. After an accelerated, hands-on overview of the serverless architecture and various Kubernetes concepts, you’ll cover a wide range of real-world development challenges faced by real-world developers, and explore various techniques to overcome them. You’ll learn how to create production-ready Kubernetes clusters and run serverless applications on them. You'll see how Kubernetes platforms and serverless frameworks such as Kubeless, Apache OpenWhisk and OpenFaaS provide the tooling to help you develop serverless applications on Kubernetes. You'll also learn ways to select the appropriate framework for your upcoming project. By the end of this book, you’ll have the skills and confidence to design your own serverless applications using the power and flexibility of Kubernetes.
Table of Contents (11 chapters)
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2
2. Introduction to Serverless in the Cloud

Debugging a Kubeless Function

A Kubeless function can fail at different stages of the function life cycle (for example, from deployment time to function execution time) due to a number of reasons. In this section, we are going to debug a function to identify the cause of failure.

In order to demonstrate multiple error scenarios, first, we are going to create a sample function with the following code block in the debug.py file:

def main(event, context)
    name = event['data']['name']
    return "Hello " +  name

Error Scenario 01

Now, let's try to deploy this function using the kubeless function deploy command:

$ kubeless function deploy debug --runtime python \
                           --from-file debug.py \
       ...
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