Lesson 70 - Preventing Data Loss When Using Messaging

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Great videos. Simple and straight to the point

Sensibles
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Mark, great video. You answered a question i have had in my mind for a while

dataguy
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What about outbox/inbox pattern? We may prevent sync communication with the queue and decrease chance of error on receiver side. As service B might want to run business logic on the message first which increases a number of points of failure. Anyway this more a complimentary approach plus to the described in the video.

nikaburu
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can you please create a youtube playlist for these lesson? this will make it easy for folks to share your lesson around

mubarak
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Great Video. I'm dealing with another use case for message loss. What if Service B upon sending the ack to Kafka, terminates due to any factor, exception, app pool reset, etc.

Or, Service B takes a long time to process the message, Kafka can't wait for any consumer to come back at anytime it wants and only then changes the offset. So what I did was to use a second persistent layer by using Hangfire integrated in Service B. but I hate this solution cause not only it's one more component to worry about, but also it defeats the whole value of messaging since I'm practically duplicating the queue. I don't know if I make sense or not!

pouyanpiano
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I think you missed the DLQ (Dead Letter Queue) pattern here for handling the case that for whatever reason, service B can't process the message

coolcoolj