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Mastering Kubernetes

You're reading from   Mastering Kubernetes Level up your container orchestration skills with Kubernetes to build, run, secure, and observe large-scale distributed apps

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Product type Paperback
Published in Jun 2020
Publisher Packt
ISBN-13 9781839211256
Length 642 pages
Edition 3rd Edition
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Author (1):
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Gigi Sayfan Gigi Sayfan
Author Profile Icon Gigi Sayfan
Gigi Sayfan
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Toc

Table of Contents (19) Chapters Close

Preface 1. Understanding Kubernetes Architecture 2. Creating Kubernetes Clusters FREE CHAPTER 3. High Availability and Reliability 4. Securing Kubernetes 5. Using Kubernetes Resources in Practice 6. Managing Storage 7. Running Stateful Applications with Kubernetes 8. Deploying and Updating Applications 9. Packaging Applications 10. Exploring Advanced Networking 11. Running Kubernetes on Multiple Clouds and Cluster Federation 12. Serverless Computing on Kubernetes 13. Monitoring Kubernetes Clusters 14. Utilizing Service Meshes 15. Extending Kubernetes 16. The Future of Kubernetes 17. Other Books You May Enjoy
18. Index

Launching jobs

Hue has evolved and has a lot of long-running processes deployed as microservices, but it also has a lot of tasks that run, accomplish some goal, and exit. Kubernetes supports this functionality via the Job resource. A Kubernetes job manages one or more pods and ensures that they run until they are successful. If one of the pods managed by the job fails or is deleted, then the job will run a new pod until it succeeds.

There are also many serverless or function-as-a-service solutions for Kubernetes, but they are built on top of native Kubernetes. We will dedicate a whole chapter to serverless computing.

Here is a job that runs a Python process to compute the factorial of 5 (hint: it's 120):

apiVersion: batch/v1
kind: Job
metadata:
  name: factorial5
spec:
  template:
    metadata:
      name: factorial5
    spec:
      containers:
      - name: factorial5
        image: g1g1/py-kube:0.2
        command: ["python",
                  "-c...
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