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Getting Started with Kubernetes

You're reading from   Getting Started with Kubernetes Extend your containerization strategy by orchestrating and managing large-scale container deployments

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781788994729
Length 470 pages
Edition 3rd Edition
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Authors (2):
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Jesse White Jesse White
Author Profile Icon Jesse White
Jesse White
Jonathan Baier Jonathan Baier
Author Profile Icon Jonathan Baier
Jonathan Baier
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Toc

Table of Contents (18) Chapters Close

Preface 1. Introduction to Kubernetes FREE CHAPTER 2. Building a Foundation with Core Kubernetes Constructs 3. Working with Networking, Load Balancers, and Ingress 4. Implementing Reliable Container-Native Applications 5. Exploring Kubernetes Storage Concepts 6. Application Updates, Gradual Rollouts, and Autoscaling 7. Designing for Continuous Integration and Delivery 8. Monitoring and Logging 9. Operating Systems, Platforms, and Cloud and Local Providers 10. Designing for High Availability and Scalability 11. Kubernetes SIGs, Incubation Projects, and the CNCF 12. Cluster Federation and Multi-Tenancy 13. Cluster Authentication, Authorization, and Container Security 14. Hardening Kubernetes 15. Kubernetes Infrastructure Management 16. Assessments 17. Other Books You May Enjoy

Built-in monitoring


If you recall from Chapter 1, Introduction to Kubernetes, we noted that our nodes were already running a number of monitoring services. We can see these once again by running the get pods command with the kube-system namespace specified as follows:

$ kubectl get pods --namespace=kube-system

The following screenshot is the result of the preceding command:

System pod listing

Again, we see a variety of services, but how does this all fit together? If you recall, the node (formerly minions) section from Chapter 2, Building a Foundation with Core Kubernetes Constructs, each node is running a kubelet. The kubelet is the main interface for nodes to interact with and update the API server. One such update is the metrics of the node resources. The actual reporting of the resource usage is performed by a program named cAdvisor.

The cAdvisor program is another open source project from Google, which provides various metrics on container resource use. Metrics include CPU, memory, and network...

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