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Advanced Kubernetes Techniques: Monitoring, Logging, Auto-Scaling

Name: Advanced Kubernetes Techniques: Monitoring, Logging, Auto-Scaling
Price: 59 USD
Author: Viktor Farcic

Delve into advanced Kubernetes features like monitoring, alerting, logging, and auto-scaling. Learn to create resilient, self-adaptive clusters and applications with minimal manual intervention.

4.7

76 lessons

12h

Created by Viktor Farcic

Advanced Kubernetes Techniques: Monitoring, Logging, Auto-Scaling

What's included

76 lessons across 9 modules
55 quizzes with instant feedback
AI Tutor on every lesson

Join 3.1 million developers at

What You'll Learn

Create Kubernetes clusters on GKE, EKS, AKS, Minikube, and Docker Desktop using provided scripts
Install and use Metrics Server to retrieve pod and container CPU/memory metrics with kubectl
Configure HorizontalPodAutoscaler for Deployments and StatefulSets using CPU and memory utilization
Set up Cluster Autoscaler to scale nodes up and down and define min/max node thresholds
Implement Prometheus and Alertmanager to query metrics and send alert notifications to Slack
Build Grafana dashboards by importing, customizing, and creating panels for Kubernetes metrics and alerts
Deploy centralized logging with Fluentd and query logs via Papertrail, CloudWatch, Stackdriver, or EFK

Learning Roadmap

76 Lessons55 Quizzes

Before Getting Started

Get familiar with advanced Kubernetes techniques, requirements, and tools for enhanced cluster management.

Introduction

Intended Audience and Course Requirements

Autoscaling Deployments and StatefulSets

Discover the logic behind Kubernetes autoscaling using HorizontalPodAutoscaler for performance management and resource optimization.

Introduction

Create a Cluster

Install Metrics Server

Observe Metrics Server Data

Get Started with Auto-Scaling Pods

Auto-Scale Pods Based on Resource Utilization

Specify Replicas in Deployments or Statefulsets?

Revise and Test the Concepts

Auto-Scaling Nodes Of A Kubernetes Cluster

8 Lessons

Examine auto-scaling nodes for efficient resource use in Kubernetes clusters.

Collecting and Querying Metrics and Sending Alerts

18 Lessons

Grasp the fundamentals of Kubernetes monitoring, metrics collection, querying, and alerting.

Debugging Issues Discovered Through Metrics and Alerts

6 Lessons

Map out the steps for debugging Kubernetes issues using metrics, alerts, and instrumentation.

Extending HorizontalPodAutoscaler With Custom Metrics

10 Lessons

See how HorizontalPodAutoscaler integrates custom metrics, optimizing dynamic scaling and resource management.

Visualizing Metrics And Alerts

10 Lessons

Practice using Grafana and Prometheus for efficient monitoring and alert systems.

Collecting And Querying Logs

13 Lessons

Get familiar with centralized logging solutions and their integration with Kubernetes clusters.

Conclusion

Walk through key advanced Kubernetes techniques for scaling, metrics, and logging.

What did we do?

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

About this course

WHY I WROTE THIS COURSE

The world of DevOps has exploded with the help of technologies like Kubernetes and Docker. In this course, you will learn about more advanced Kubernetes features such as monitoring, alerting, logging, and scaling - crucial concepts for any DevOps professional. You will learn how to monitor clusters, how to send alerts when potential issues arise, and how to query the whole system’s metrics and logs. By the end of this course, you will have the required knowledge to make your clusters and applications truly dynamic and resilient, so that they require minimal manual involvement and are self-adaptive.

ABOUT THE AUTHOR

Viktor Farcic

Playing with tech...

Learn more about Viktor

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