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Mastering Kubernetes

You're reading from   Mastering Kubernetes Large scale container deployment and management

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Product type Paperback
Published in May 2017
Publisher Packt
ISBN-13 9781786461001
Length 426 pages
Edition 1st Edition
Tools
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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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Table of Contents (16) Chapters Close

Preface 1. Understanding Kubernetes Architecture FREE CHAPTER 2. Creating Kubernetes Clusters 3. Monitoring, Logging, and Troubleshooting 4. High Availability and Reliability 5. Configuring Kubernetes Security, Limits, and Accounts 6. Using Critical Kubernetes Resources 7. Handling Kubernetes Storage 8. Running Stateful Applications with Kubernetes 9. Rolling Updates, Scalability, and Quotas 10. Advanced Kubernetes Networking 11. Running Kubernetes on Multiple Clouds and Cluster Federation 12. Customizing Kubernetes - API and Plugins 13. Handling the Kubernetes Package Manager 14. The Future of Kubernetes Index

Launching jobs


Hue 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 success. If one of the pods managed by the job fails or is deleted, then the job will run a new pod until it succeeds.

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: python:3.5
        command: ["python", 
                  "-c", 
                  "import math; print(math.factorial(5))"]
      restartPolicy: Never      

Note that the restartPolicy must be either Never or OnFailure The default Always value is invalid because a job shouldn't restart after a successful completion.

Let...

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