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Kubernetes Monitoring, Logging and Auto-Scaling

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Before We Begin

About this Module

Before Getting Started

Introduction Intended Audience and Course Requirements

Autoscaling Deployments and StatefulSets

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

Introduction Create a Cluster Set up Cluster Autoscaler Scale up the Cluster Scale down the Cluster Can We Scale up Too Much or De-scale to Zero Nodes?Cluster Autoscaler Compared in GKE, EKS, and AKS Revise and Test the Concepts

Collecting and Querying Metrics and Sending Alerts

Introduction Create a Cluster Choose the Tools for Storing and Querying Metrics and Alerting Defining Alert Rules Seeing Green Alerts in Action Seeing Red Alerts in Action Which Metric Types Should We Use?Alerting on Latency-related Issues Alerting on Traffic-related Issues Alerting on Error-related Issues Alerting on Saturation-related Issues Saturation-related Issues: Measure Memory Usage Alerting on Unschedulable or Failed Pods Upgrading Old Pods Measuring Containers Memory and CPU Usage Comparing Actual Resource Usage with Defined Requests Comparing Actual Resource Usage with Defined Limits Revise and Test the Concepts

Debugging Issues Discovered Through Metrics and Alerts

Introduction Create a Cluster Face a Disaster Use Instrumentation to Provide More Detailed Metrics Using Internal Metrics to Debug Potential Issues Revise and Test the Concepts

Extending HorizontalPodAutoscaler With Custom Metrics

Introduction Creating a Cluster Using HorizontalPodAutoscaler Without Metrics Adapter Exploring Prometheus Adapter Create HPA with Custom Metrics pulled through Exporters Create HPA with Custom Metrics pulled through Instrumented metric Combine Metric Server Data with Custom Metrics The Complete HorizontalPodAutoscaler Flow of Events Reaching Nirvana Revise and Test the Concepts

Visualizing Metrics And Alerts

Introduction Create a Cluster Which Tools Should We Use for Dashboards?Installing And Setting up Grafana Importing and Customizing Pre-Made Dashboards Creating Custom Dashboards Creating Semaphore Dashboards A Better Dashboard for Big Screens Prometheus and Graph Alerts, Grafana Notifications, Semaphores Revise and Test the Concepts

Collecting And Querying Logs

Introduction Create a Cluster Exploring Logs Through kubectl Choosing a Centralized Logging Solution Exploring Logs Collection and Shipping Explore Centralized Logging Through Papertrail Combine GCP StackDriver with a GKE Cluster Combine AWS CloudWatch with an EKS Cluster Combine Azure Log Analytics with an AKS Cluster Explore Centralized Logging Switching to Elasticsearch for Storing Metrics What Should We Expect from Centralized Logging?Revise and Test the Concepts

Conclusion

What did we do?

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Final Remarks

Final Remarks

Here's a quick summary of the 'Kubernetes Monitoring, Logging and Auto-Scaling' module for you.

Congratulations, you have successfully completed the module: Kubernetes Monitoring, Logging and Auto-Scaling. 🎉

Summary

We explored quite a few topics that are beyond “normal” Kubernetes usage. We learned how to scale Pods using HorizontalPodAutoscaler. We explored how to do ...