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Kubernetes in Production Best Practices

Kubernetes in Production Best Practices

By : Saleh, Karslioglu
5 (9)
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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)
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Monitoring, metrics, and visualization

In this section, we will learn about popular monitoring solutions in the cloud-native ecosystem and how to get a monitoring stack quickly up and running. Monitoring, logging, and tracing are often misused as interchangeable tools; therefore, understanding each tool's purpose is extremely important.

The most recent 2020 Cloud Native Computing Foundation (CNCF) survey suggests that companies use multiple tools (on average five or more) to monitor their cloud-native services. The list of the popular tools and projects includes Prometheus, OpenMetrics, Datadog, Grafana, Splunk, Sentry, CloudWatch, Lightstep, StatsD, Jaeger, Thanos, OpenTelemetry, and Kiali. Studies suggest that the most common and adopted tools are open source. You can read more about the CNCF community radar observations at https://radar.cncf.io/2020-09-observability.

Prometheus and Grafana used together is the most relevant combined solution for Kubernetes workloads...

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