Book Image

The DevOps 2.5 Toolkit

By : Viktor Farcic
Book Image

The DevOps 2.5 Toolkit

By: Viktor Farcic

Overview of this book

Building on The DevOps 2.3 Toolkit: Kubernetes, and The DevOps 2.4 Toolkit: Continuous Deployment to Kubernetes, Viktor Farcic brings his latest exploration of the Docker technology as he records his journey to monitoring, logging, and autoscaling Kubernetes. The DevOps 2.5 Toolkit: Monitoring, Logging, and Auto-Scaling Kubernetes: Making Resilient, Self-Adaptive, And Autonomous Kubernetes Clusters is the latest book in Viktor Farcic’s series that helps you build a full DevOps Toolkit. This book helps readers develop the necessary skillsets needed to be able to operate Kubernetes clusters, with a focus on metrics gathering and alerting with the goal of making clusters and applications inside them autonomous through self-healing and self-adaptation. Work with Viktor and dive into the creation of self-adaptive and self-healing systems within Kubernetes.
Table of Contents (9 chapters)
8
What Did We Do?

Using internal metrics to debug potential issues

We'll re-send requests with slow responses again so that we get to the same point where we started this chapter.

 1  for i in {1..20}; do
 2      DELAY=$[ $RANDOM % 10000 ]
 3      curl "http://$GD5_ADDR/demo/hello?delay=$DELAY"
 4  done
5 6 open "http://$PROM_ADDR/alerts"

We sent twenty requests that will result in responses with random duration (up to ten seconds). Further on, we opened Prometheus' alerts screen.

A while later, the AppTooSlow alert should fire (remember to refresh your screen), and we have a (simulated) problem that needs to be solved. Before we start panicking and do something hasty, we'll try to find the cause of the issue.

Please click the expression of the AppTooSlow alert.

We are redirected to the graph screen with the pre-populated expression from the alert. Feel free...