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Intended Audience and Course Requirements

Autoscaling Deployments and StatefulSets

8 Lessons

Observe Metrics Server Data

Install Metrics Server

Get Started with Auto-Scaling Pods

Auto-Scale Pods Based on Resource Utilization

Specify Replicas in Deployments or Statefulsets?

Auto-Scaling Nodes Of A Kubernetes Cluster

8 Lessons

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

Collecting and Querying Metrics and Sending Alerts

18 Lessons

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

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

Debugging Issues Discovered Through Metrics and Alerts

6 Lessons

Use Instrumentation to Provide More Detailed Metrics

Face a Disaster

Using Internal Metrics to Debug Potential Issues

Extending HorizontalPodAutoscaler With Custom Metrics

10 Lessons

Using HorizontalPodAutoscaler Without Metrics Adapter

Creating a Cluster

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

Visualizing Metrics And Alerts

10 Lessons

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

Collecting And Querying Logs

13 Lessons

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?

Conclusion

1 Lessons

What did we do?

Course Author

Viktor Farcic

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