Chaos Engineering: System Resiliency in Practice. Questo articolo non è disponibile.
Lingua: inglese
Editore: O'Reilly Media, 2020
- Brossura
- Usato

Da: Dream Books Co., Denver, CO, U.S.A.Dream Books Co.
Venditore AbeBooks dal 23 novembre 2023
Condizione: Usato - Discreto
EUR 16,72
Descrizione dell’articolo da parte del venditore
This copy has clearly been enjoyed—expect noticeable shelf wear and some minor creases to the cover. Binding is strong, and all pages are legible. May contain previous library markings or stamps.
Codice articolo DBV.1492043869.A
- Titolo
- Chaos Engineering: System Resiliency in Practice
- Autore
- Rosenthal, Casey; Jones, Nora
- Editore
- O'Reilly Media
- Anno di pubblicazione
- 2020
- Condizione
- acceptable
- Rilegatura
- Brossura
- Lingua
- inglese
- ISBN 10
- 1492043869
- ISBN 13
- 9781492043867
As more companies move toward microservices and other distributed technologies, the complexity of these systems increases. You can't remove the complexity, but through Chaos Engineering you can discover vulnerabilities and prevent outages before they impact your customers. This practical guide shows engineers how to navigate complex systems while optimizing to meet business goals.
Two of the field's prominent figures, Casey Rosenthal and Nora Jones, pioneered the discipline while working together at Netflix. In this book, they expound on the what, how, and why of Chaos Engineering while facilitating a conversation from practitioners across industries. Many chapters are written by contributing authors to widen the perspective across verticals within (and beyond) the software industry.
- Learn how Chaos Engineering enables your organization to navigate complexity
- Explore a methodology to avoid failures within your application, network, and infrastructure
- Move from theory to practice through real-world stories from industry experts at Google, Microsoft, Slack, and LinkedIn, among others
- Establish a framework for thinking about complexity within software systems
- Design a Chaos Engineering program around game days and move toward highly targeted, automated experiments
- Learn how to design continuous collaborative chaos experiments
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