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?

Exploring centralized logging through Elasticsearch, Fluentd, and Kibana

Elasticsearch is probably the most commonly used in-memory database. At least, if we narrow the scope to self-hosted databases. It is designed for many other scenarios, and it can be used to store (almost) any type of data. As such, it is almost perfect for storing logs which could come in many different formats. Given its flexibility, some use it for metrics as well and, as such, Elasticsearch competes with Prometheus. We'll leave metrics aside, for now, and focus only on logs.

The EFK (Elasticsearch, Fluentd, and Kibana) stack consists of three components. Data is stored in Elasticsearch, logs are collected, transformed, and pushed to the DB by Fluentd, and Kibana is used as UI through which we can explore data stored in Elasticsearch. If you are used to ELK (Logstash instead of Fluentd), the setup...