Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Kubernetes in Production Best Practices
  • Toc
  • feedback
Kubernetes in Production Best Practices

Kubernetes in Production Best Practices

By : Saleh, Karslioglu
5 (9)
close
Kubernetes in Production Best Practices

Kubernetes in Production Best Practices

5 (9)
By: Saleh, Karslioglu

Overview of this book

Although out-of-the-box solutions can help you to get a cluster up and running quickly, running a Kubernetes cluster that is optimized for production workloads is a challenge, especially for users with basic or intermediate knowledge. With detailed coverage of cloud industry standards and best practices for achieving scalability, availability, operational excellence, and cost optimization, this Kubernetes book is a blueprint for managing applications and services in production. You'll discover the most common way to deploy and operate Kubernetes clusters, which is to use a public cloud-managed service from AWS, Azure, or Google Cloud Platform (GCP). This book explores Amazon Elastic Kubernetes Service (Amazon EKS), the AWS-managed version of Kubernetes, for working through practical exercises. As you get to grips with implementation details specific to AWS and EKS, you'll understand the design concepts, implementation best practices, and configuration applicable to other cloud-managed services. Throughout the book, you’ll also discover standard and cloud-agnostic tools, such as Terraform and Ansible, for provisioning and configuring infrastructure. By the end of this book, you’ll be able to leverage Kubernetes to operate and manage your production environments confidently.
Table of Contents (12 chapters)
close

Logging and tracing

In this section, we will learn about the popular logging solutions in the cloud-native ecosystem and how to get a logging stack quickly up and running.

Handling logs for applications running on Kubernetes is quite different than traditional application log handling. With monolithic applications, when a server or an application crashes, our server can still retain logs. In Kubernetes, a new pod is scheduled when a pod crashes, causing the old pod and its records to get wiped out. The main difference with containerized applications is how and where we ship and store our logs for future use.

Two cloud-native-focused popular logging stacks are the Elasticsearch, Fluentd, and Kibana (EFK) stack and the Promtail, Loki, and Grafana (PLG) stack. Both have fundamental design and architectural differences. The EFK stack uses Elasticsearch as an object store, Fluentd for log routing and aggregation, and Kibana for the visualization of logs. The PLG stack is based on...

Unlock full access

Continue reading for free

A Packt free trial gives you instant online access to our library of over 7000 practical eBooks and videos, constantly updated with the latest in tech
bookmark search playlist download font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete