> Jepsen evaluated MongoDB version 4.2.6, and found that even at the strongest levels of read and write concern, it failed to preserve snapshot isolation. Instead, Jepsen observed read skew, cyclic information flow, duplicate writes, and internal consistency violations. Weak defaults meant that transactions could lose writes and allow dirty reads, even downgrading requested safety levels at the database and collection level.
Could you expand on the techniques you use to implement idempotency in your workers/queues and in your rpcs?
I have seen a mix of doing nothing if there is nothing to do, locking, using a idempotency key and so on. But I am always curious to see what others do.
Since launching in June 2014 - Foko has users in 10% of the Fortune 100, and boast high profile clients like Whole Foods, Trend Micro, Maxim Integrated, and One Medical Group. Monthly active usage is over 45% - nearly 3X industry average for enterprise services. http://www.foko.co
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Come work with passionate people! Come make a difference and be part of an awesome team!
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Since launching in June 2014 - Foko has users in 10% of the Fortune 100, and boast high profile clients like Whole Foods, Trend Micro, Maxim Integrated, and One Medical Group.
Monthly active usage is over 45% - nearly 3X industry average for enterprise services.
Since launching in June 2014 - Foko has users in 10% of the Fortune 100, and boast high profile clients like Whole Foods, Trend Micro, Maxim Integrated, and One Medical Group. Monthly active usage is over 45% - nearly 3X industry average for enterprise services. http://www.foko.co
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Come work with passionate people! Come make a difference and be part of an awesome team!
Hahaha I love that sentence : In the process, I’m evaluating a bunch of J2EE portlet-enabled JSR-compliant MVC role-based CMS web service application container frameworks...
> Jepsen evaluated MongoDB version 4.2.6, and found that even at the strongest levels of read and write concern, it failed to preserve snapshot isolation. Instead, Jepsen observed read skew, cyclic information flow, duplicate writes, and internal consistency violations. Weak defaults meant that transactions could lose writes and allow dirty reads, even downgrading requested safety levels at the database and collection level.