Introduction to Schema Registry in Kafka | Part 1

Schema Registry is a simple concept but it's really powerful in enforcing data governance within your Kafka architecture.

This video explains fundamental concepts related to Kafka Schema Registry.

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[ADayinMyBrain]

This is exactly what i have been looking to know about Avro SR, Excellent, Thanks.

[manojt]

To be honest. I have been searching for a clear explanation on this Schema registry topic in many video. But your explanation was the best of best!

[jeetkp]

Best video out there !! I have been searching about the topic a lot, fortunately got this video, so good and easy to grasp the way you explained w diagram and explanation.

[SHINEUPTILLAST]

Man, the way you elucidate the topic is pretty amazing. You cleared all my concerns related to this topic. Thanks

[dineshkarunanithi]

Really great explanation and keep up the good work. This really helps.

[sagar]

Thank you. You teach well. Best of luck :)

[rabindrajaiswal]

Great, finally understood schema registry in very simple way
Thank hou so much ❤

[snehikpodder]

Really great explanation. Could you please make some video around subject name schema strategy when we have to support multiple schemas under one topic using python code examples?

[anilsangula]

Hi, May I know schema registry can we implement using windows as well. where can we get files, schema-registry-run-class and schema-registry-start files for windows.

[rahulkakade]

Sir I'm going to create one poc using lamda, redshift, glue, s3 so I want to generate huge ammount of data for batch as well as streaming can you please make video how we can generate huge ammount of data

[SpiritOfIndiaaa]

#KnowledgeAmplifier thanks a lot bro. any vid on CONDUCTOR ?

[ohuuthai]

Where will that topic be saved on the computer?

[sanjaybedwal]

Nice video . One question though ..
If schema validation is already happening at producer level . What are the chances or in which scenario does the schema validation can fail at consumer side ?

[andreybraslavskiy]

It is not well explained. Always should be an example of failure. This video makes it hard to imagine when consumers can fail to parse the message. Following the video, it says that the consumer get an ID of the schema from the message itself. So how is it possible that the message will not match the schema if the message will not be published with this ID in case of mismatch in the first place?