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?

The complete HorizontalPodAutoscaler flow of events

Metrics Server is fetching memory and CPU data from Kubelets running on the worker nodes. In parallel, Prometheus Adapter is fetching data from Prometheus Server which, as you already know, pulls data from different sources. Data from both Metrics Server and Prometheus Adapter is combined in Metrics Aggregator.

HPA is periodically evaluating metrics defined as scaling criteria. It's fetching data from Metrics Aggregator, and it does not really care whether they're coming from Metrics Server, Prometheus Adapter, or any other tool we could have used.

Once scaling criteria is met, HPA manipulates Deployments and StatefulSets by changing their number of replicas.

As a result, rolling updates are performed by creating and updating ReplicaSets which, in turn, create or remove Pods.

Figure 5-3: HPA using a combination of...