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Advanced Kubernetes Techniques: Monitoring, Logging, Auto-Scaling

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
Updated 2 weeks ago
Join 2.9 million developers at
Join 2.9 million developers at
LEARNING OBJECTIVES
  • 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

1.

Before Getting Started

Before Getting Started

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

2.

Autoscaling Deployments and StatefulSets

Autoscaling Deployments and StatefulSets

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

3.

Auto-Scaling Nodes Of A Kubernetes Cluster

Auto-Scaling Nodes Of A Kubernetes Cluster

8 Lessons

8 Lessons

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

4.

Collecting and Querying Metrics and Sending Alerts

Collecting and Querying Metrics and Sending Alerts

18 Lessons

18 Lessons

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

5.

Debugging Issues Discovered Through Metrics and Alerts

Debugging Issues Discovered Through Metrics and Alerts

6 Lessons

6 Lessons

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

6.

Extending HorizontalPodAutoscaler With Custom Metrics

Extending HorizontalPodAutoscaler With Custom Metrics

10 Lessons

10 Lessons

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

7.

Visualizing Metrics And Alerts

Visualizing Metrics And Alerts

10 Lessons

10 Lessons

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

8.

Collecting And Querying Logs

Collecting And Querying Logs

13 Lessons

13 Lessons

Get familiar with centralized logging solutions and their integration with Kubernetes clusters.
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Author NameAdvanced Kubernetes Techniques: Monitoring,Logging, Auto-Scaling
Developed by MAANG Engineers
ABOUT 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...

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