Kubernetes Patterns e-bog
359,43 DKK
(inkl. moms 449,29 DKK)
The way developers design, build, and run software has changed significantly with the evolution of microservices and containers. These modern architectures offer new distributed primitives that require a different set of practices than many developers, tech leads, and architects are accustomed to. With this focused guide, Bilgin Ibryam and Roland Huss provide common reusable patterns and princi...
E-bog
359,43 DKK
Forlag
O'Reilly Media
Udgivet
1 september 2022
Længde
392 sider
Genrer
UTC
Sprog
English
Format
epub
Beskyttelse
LCP
ISBN
9781098131647
The way developers design, build, and run software has changed significantly with the evolution of microservices and containers. These modern architectures offer new distributed primitives that require a different set of practices than many developers, tech leads, and architects are accustomed to. With this focused guide, Bilgin Ibryam and Roland Huss provide common reusable patterns and principles for designing and implementing cloud native applications on Kubernetes.Each pattern includes a description of the problem and a Kubernetes-specific solution. All patterns are backed by and demonstrated with concrete code examples. This updated edition is ideal for developers and architects familiar with basic Kubernetes concepts who want to learn how to solve common cloud native challenges with proven design patterns.You'll explore:Foundational patterns covering core principles and practices for building and running container-based cloud native applicationsBehavioral patterns that delve into finer-grained concepts for managing various types of container and platform interactionsStructural patterns for organizing containers within a Pod for addressing specific use casesConfiguration patterns that provide insight into how application configurations can be handled in KubernetesSecurity patterns for hardening the access to cloud native applications running on KubernetesAdvanced patterns covering more complex topics such as operators and autoscaling