Stream Processing System Design Architecture

Whether you're a data engineer, architect, or simply curious about real-time data processing, this video is your essential guide!
What You'll Learn:
Grasp the fundamentals: Understand key concepts like AWS Kinesis, AWS Lambda
Architect your system: Explore different design patterns and choose the right one for your needs.
Scale with confidence: Learn techniques for building highly scalable and fault-tolerant systems.
Real-world use cases: See stream processing in action through practical examples.
System Design Interview Basics Playlist:
► • System Design Intervie...
AWS Certification:
►AWS Certified Cloud Practioner: • How to Pass AWS Certif...
►AWS Certified Solution Architect Associate: • How to Pass AWS Certif...
►AWS Certified Solution Architect Professional: • How to Pass AWS Certif...

[@santosh_bhat]

Awesome, like from my side How do you create such amazing aninations? Any tools ?

[@sethu14]

the video is awesome mate, the audio quality could be better..

[@ByteMonk]

thanks for the feedback, will work on it.

[@cripz4203]

Theres a difference between message broker and message queue, no?

[@ByteMonk]

Yes. A message queue acts as a data structure, essentially a temporary storage for messages. A message broker, on the other hand, is a software component that manages message queues. It acts as an intermediary between the sender (producer) and receiver (consumer) of messages. Please checkout system design playlist in my channel, I have covered messaging in details.

[@jpactor155]

Great video! I work for a cloud database company - would you be open to chat and potential collab? Your videos are awesome!

[@ByteMonk]

Thank you I will be happy to, I will have some time next month

[@landocodes]

This unfortunately feels like an Amazon sponsored video.

[@ByteMonk]

These are the ways I am aware of to implement stream processing. My knowledge is limited to AWS at this time, will keep it more generic in future for generic topics like this. Thanks for the feedback!

[@landocodes]

@@ByteMonk np! I appreciate your willingness to take feedback. I love your content.