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Designing Distributed Systems: Patterns and Paradigms for Scalable, Reliable Systems Using Kubernetes 2nd

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Designing Distributed Systems: Patterns and Paradigms for Scalable, Reliable Systems Using Kubernetes 2nd - фото 1 - id-p2484311315

Характеристики и описание

Друкчорно-білий
ЯзыкEnglish
ОбложкаМягкая
Папірбілий, офсет
Рік2025
Состояниенова книга
Сторінок217

Every distributed system strives for reliability, performance, and quality, but building such a system is hard. Establishing a set of design patterns enables software developers and system architects to use a common language to describe their systems and learn from the patterns and practices developed by others.

The popularity of containers and Kubernetes paves the way for core distributed system patterns and reusable containerized components. This practical guide presents a collection of repeatable, generic patterns to help guide the systems you build using common patterns and practices drawn from some of the highest performing distributed systems in use today. These common patterns make the systems you build far more approachable and efficient, even if you've never built a distributed system before.

Author Brendan Burns demonstrates how you can adapt existing software design patterns for designing and building reliable distributed applications. Systems engineers and application developers will learn how these long-established patterns provide a common language and framework for dramatically increasing the quality of your system.

This fully updated second edition includes new chapters on AI inference, AI training, and building robust systems for the real world.

Understand how patterns and reusable components enable the rapid development of reliable distributed systems

Use the sidecar, adapter, and ambassador patterns to split your application into a group of containers on a single machine

Explore loosely coupled multinode distributed patterns for tion, scaling, and communication between components

Learn distributed system patterns for large-scale batch data processing covering work queues, event-based processing, and coordinated workflows

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