You're reading from Mastering Kubernetes, - Third Edition

Product typeBook

Published inJun 2020

PublisherPackt

ISBN-139781839211256

Edition3rd Edition

Tools

Kubernetes

Concepts

Containerization

Author (1)

Gigi Sayfan

High Availability and Reliability

In Chapter 2, Creating Kubernetes Clusters, we learned how to create Kubernetes clusters in different environments, experimented with different tools, and created a couple of clusters. Creating a Kubernetes cluster is just the beginning of the story. Once the cluster is up and running, you need to make sure it stays operational.

In this chapter, we will dive into the topic of highly available clusters. This is a complicated topic. The Kubernetes project and the community haven't settled on one true way to achieve high availability nirvana. There are many aspects to highly available Kubernetes clusters, such as ensuring that the control plane can keep functioning in the face of failures, protecting the cluster state in etcd, protecting the system's data, and recovering capacity and/or performance quickly. Different systems will have different reliability and availability requirements. How to design and implement a highly available...

High availability concepts

In this section, we will start our journey into high availability by exploring the concepts and building blocks of reliable and highly available systems. The million (trillion?) dollar question is, how do we build reliable and highly available systems from unreliable components? Components will fail; you can take that to the bank. Hardware will fail; networks will fail; configuration will be wrong; software will have bugs; people will make mistakes. Accepting that, we need to design a system that can be reliable and highly available even when components fail. The idea is to start with redundancy, detect component failure, and replace bad components quickly.

Redundancy

Redundancy is the foundation of reliable and highly available systems at the hardware and data levels. If a critical component fails and you want the system to keep running, you must have another identical component ready to go. Kubernetes itself takes care of your stateless pods via...

High availability best practices

Building reliable and highly available distributed systems is a non-trivial endeavor. In this section, we will check some of the best practices that enable a Kubernetes-based system to function reliably and be available in the face of various failure categories. We will also dive deep and see how to go about constructing your own highly available clusters.

Note that you should roll your own highly available Kubernetes cluster only in very special cases. Tools such as Kubespray provide battle-tested ways to create highly available clusters. You should take advantage of all the work and effort that went into these tools.

Creating highly available clusters

To create a highly available Kubernetes cluster, the master components must be redundant. That means etcd must be deployed as a cluster (typically across three or five nodes) and the Kubernetes API server must be redundant. Auxiliary cluster-management services such as Heapster storage...

High availability, scalability, and capacity planning

Highly available systems must also be scalable. The load on most complicated distributed systems can vary dramatically based on the time of day, weekdays versus weekends, seasonal effects, marketing campaigns, and many other factors. Successful systems will have more users over time and accumulate more and more data. That means that the physical resources of the clusters—mostly nodes and storage—will have to grow over time too. If your cluster is under-provisioned, it will not be able to satisfy all the demand and it will not be available because requests will time out or be queued up and not processed fast enough.

This is the realm of capacity planning. One simple approach is to over-provision your cluster. Anticipate the demand and make sure you have enough of a buffer for spikes of activity. But be aware that this approach suffers from several deficiencies:

For highly dynamic and complicated distributed...

Live cluster updates

One of the most complicated and risky tasks involved in running a Kubernetes cluster is a live upgrade. The interactions between different parts of the system in different versions are often difficult to predict, but in many situations, it is required. Large clusters with many users can't afford to be offline for maintenance. The best way to attack complexity is to divide and conquer. Microservice architecture helps a lot here. You never upgrade your entire system. You just constantly upgrade several sets of related microservices, and if APIs have changed, then you upgrade their clients, too. A properly designed upgrade will preserve backward-compatibility at least until all clients have been upgraded, and then deprecate old APIs across several releases.

In this section, we will discuss how to go about updating your cluster using various strategies such as rolling updates, blue-green deployments, and canary deployments. We will also discuss when it&apos...

Large cluster performance, cost, and design trade-offs

In the previous section, we looked at live cluster upgrades and application updates. We explored various techniques and how Kubernetes supports them. We also discussed difficult problems such as breaking changes, data contract changes, data migration, and API deprecation. In this section, we will consider the various options and configurations of large clusters with different reliability and high availability properties. When you design your cluster, you need to understand your options and choose wisely based on the needs of your organization.

The topics we will cover include various availability requirements, from best effort all the way to the holy grail of zero downtime. Finally, we will settle down on the practical site-reliability engineering approach. For each category of availability, we will consider what it means from the perspectives of performance and cost.

Availability requirements

Different systems...

Summary

In this chapter, we looked at reliable and highly available large-scale Kubernetes clusters. This is arguably the sweet spot for Kubernetes. While it is useful to be able to orchestrate a small cluster running a few containers, it is not necessary, but at scale, you must have an orchestration solution in place you can trust to scale with your system, and provide the tools and the best practices to do that.

You now have a solid understanding of the concepts of reliability and high availability in distributed systems. You delved into the best practices for running reliable and highly available Kubernetes clusters. You explored the nuances of live Kubernetes cluster upgrades and you can make wise design choices regarding levels of reliability and availability, as well as their performance and cost.

In the next chapter, we will address the important topic of security in Kubernetes. We will also discuss the challenges of securing Kubernetes and the risks involved. We will...

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Author (1)

Gigi Sayfan

Gigi Sayfan has been developing software for 25+ years in domains as diverse as instant messaging, morphing, chip fabrication process control, embedded multimedia applications for game consoles, brain-inspired ML, custom browser development, web services for 3D distributed game platforms, IoT sensors, virtual reality, and genomics. He has written production code in languages such as Go, Python, C, C++, C#, Java, Delphi, JavaScript, and even Cobol and PowerBuilder for operating systems such as Windows (3.11 through 7), Linux, macOS, Lynx (embedded), and Sony PlayStation. His technical expertise includes databases, low-level networking, distributed systems, containers, unorthodox user interfaces, modern web applications, and general SDLC.
Read more about Gigi Sayfan

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