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更新于 : Nov 14, 2018
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
Nov 2018
试验 ? 值得一试。了解为何要构建这一能力是很重要的。企业应当在风险可控的前提下在项目中尝试应用此项技术。

With the increased adoption of a microservices architecture, we're building more distributed applications than before. Although there are many benefits of a decoupled architecture, the complexity and the effort involved in proving the correctness of the overall system has dramatically increased. Jepsen provides much needed tooling to verify correctness in coordination of task schedulers, test eventual consistency, linearizability and serializability characteristics of distributed databases. We've used Jepsen in a few projects and we like the fact that we can test drive configurations, inject and correct faults, and verify the state of the system after recovery.

Apr 2016
评估 ? 在了解它将对你的企业产生什么影响的前提下值得探索

With the growth in usage of NoSQL data stores, and the growth in popularity of polyglot approaches to persistence, teams now have many choices when it comes to storing their data. While this has brought many advantages, product behavior with flaky networks can introduce subtle (and not so subtle) issues that are often not well understood, even in some cases by the product developers themselves. The Jepsen toolkit and accompanying blog have become the de-facto reference for anyone looking to understand how different database and queuing technologies react under adverse conditions. Crucially, the approach to testing, which includes clients in the transactions, shines a spotlight on possible failure modes for many teams building microservices.

发布于 : Apr 05, 2016


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