- Implementing Cloud Design Patterns for AWS(Second Edition)
- Sean Keery Clive Harber Marcus Young
- 230字
- 2021-06-24 15:11:58
Fault tolerance
Power outages, hardware failures, and data center upgrades are just a few of the many problems that still bubble up to the engineering teams responsible for systems. Data center upgrades are common, and given enough time at AWS, your product team will get an email or notification stating that some servers will shut down, or experience brownouts, or small outages of power. We've shown that the best way to handle these is to span across data centers (AZs) so that, if a single location experiences issues, the systems will continue to respond. Your services should be configured in an N+1 configuration. If a single frontend is acceptable, then it should be configured for two. Spanning AZs gives us further protection from large-scale outages while keeping latency low. This allows for hiccups and brownouts, as well as an influx of traffic into the system with minimal impact to the end users.
An example of this architecture can be seen in the reference architecture for Cloud Foundry (http://www.cloudfoundry.org). Each subnet is in a different AZ. Components are deployed on each subnet to provide fault tolerance. A complete loss of two Amazon data centers would slow the system down, but it would continue to be available: https://docs.pivotal.io/pivotalcf/2-1/plan/aws/aws_ref_arch.html.
We can see how DNS is used for global traffic management and a set of load balancers creates a facade for LTM.
- Modern Web Testing with TestCafe
- 白話區塊鏈
- Arch Linux Environment Setup How-to
- Instant Handlebars.js
- SharePoint 2013 WCM Advanced Cookbook
- Linux內核設計的藝術:圖解Linux操作系統架構設計與實現原理
- Django Project Blueprints
- Windows 7實戰從入門到精通(超值版)
- Ubuntu Linux操作系統實用教程
- 嵌入式微系統
- Docker容器技術與應用
- Getting Started with UDK
- Less Web Development Essentials
- 電腦辦公(Windows 7+Office 2016)入門與提高
- Docker容器技術與運維