Preface
Software serves more people more critically than ever before. These two demands are generalized as scale and reliability. Over the past decade, the software industry has pursued scale and reliability with tactics, infrastructure, and cultural initiatives like DevOps, which sees developers share the operational responsibility of keeping applications running.
One set of tactics is the automation of operations chores: writing software to run your software. The automation of repetitive toil is among the keystones of Site Reliability Engineering (SRE), an IT discipline defined by the O’Reilly title of the same name. DevOps and its younger cousin GitOps both apply SRE’s automation ideas to development machinery and to the practice of building software. The simplest form might be the triggering of automatic construction and deployment processes whenever an application’s source code changes.
Modern software infrastructure pursues scale and reliability through distributed computing. Despite all the syllables, distributed computing just means making many computers act like one big computer. The assembled system can do more work (scale), and it can cast understudies for potential points of failure (reliability).
Kubernetes is a system for managing applications on distributed computers by encapsulating them in discrete, interchangeable artifacts called containers. Kubernetes can manage where and when containers run without knowing all about them and their dependencies. Kubernetes ...
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