Enable javascript in your browser for better experience. Need to know to enable it? Go here.

Focus on mean time to recovery

本页面中的信息并不完全以您的首选语言展示,我们正在完善其他语言版本。想要以您的首选语言了解相关信息,可以点击这里下载PDF。
更新于 : May 05, 2015
不在本期内容中
这一条目不在当前版本的技术雷达中。如果它出现在最近几期中,那么它很有可能仍然具有相关参考价值。如果这一条目出现在更早的雷达中,那么它很有可能已经不再具有相关性,我们的评估将不再适用于当下。很遗憾我们没有足够的带宽来持续评估以往的雷达内容。 了解更多
May 2015
采纳 ?

Traditionally operations groups look to improve the mean time between failures. While avoiding failures is obviously still important, lessons from cloud computing have taught us to expect failure and instead to focus on mean time to recovery. Continuous Delivery automation makes rolling out rapid fixes easier and we are also seeing a growth in monitoring techniques to spot failures quickly through a ‘production immune system’. Teams are also successfully using semantic monitoring and synthetic transactions to exercise production systems in non-destructive ways. This combined focus allows teams to move rapidly with higher confidence, it can also reduce the emphasis on expensive test-execution in pre-production environments and is particularly important in responding to the ever-growing list of security vulnerabilities that are being discovered.

Jan 2015
采纳 ?
Jul 2014
试验 ?
In DevOps-savvy organizations delivery teams often configure production monitoring and respond to incidents themselves. This visibility and access into production environments allows those teams to make changes to their systems to improve their ability to recover quickly when something goes wrong. This focus on mean time to recovery improves quality of service overall, and allows teams to safely deploy more frequently. This can also reduce the emphasis on expensive test execution in non-production environments. Techniques we've used include end-to-end 'semantic monitoring' or reconciliation of real business transactions, and the injection of 'synthetic transactions' which exercise systems in non-destructive ways in production.
Jan 2014
评估 ?
In previous radars we recommended arranging automated acceptance tests into longer journeys and, in what we call semantic monitoring, running these tests continuously against a production environment. We still believe that this is an important technique for scenarios the team can anticipate in advance. A variation of this approach, seen especially with startups, is to reduce the number of tests while increasing monitoring and automatic alarms. This shifts the focus from avoiding problems that can be anticipated to reducing mean time to recovery for all problems.
May 2013
评估 ?
发布于 : May 22, 2013

下载 PDF

 

English | Español | Português | 中文

订阅技术雷达简报

 

立即订阅

查看存档并阅读往期内容