Clarifies lot of high level things, thanks
Very well explained
wouldn't the producer going down be a single point of failure?
Great video
wonderful explanation
Thank you sir, very well explanation.. can you tell me which extension are you using in VS code?
Hi...Well explained....Which tool did you used to create arch diagrams?
Thank you very much for another great video, Karthik
Does memory has any impact while the event is sitting on the topic of the kafka forever ?
DJ Karthik on air! Starting from 06:43 😃👍🏻
Hi Karthik, Very well explained. Event driven architecture results in "Eventual consistency", so automating at API level becomes challenging at times. So far I used retry to overcome these flaky tests. Any suggestions from your side Karthik.
Hello Karthik, good video. I hope you are well in level 4. I have built a test strategy on a few micro-service orgs now and I am curious what your take is (given the example in this video).
This Bellemare fellow is mighty handsome
If you are preparing for a system design interview, try https://get.interviewready.io.
All the best 😁
This is more of an Event Sourcing
What is event consumer and event consumer buffer size? There is a use of this in circuitbreaker design pattern but it is not clear what this does
One good thing about your videos is that you smile often, I feel that is much needed for the audience to be engaged through out your videos.
Java vertex also uses evenbus architectures
I love your content! Thank you for sharing your videos!
"You want headshots" 😂
This is more of event sourcing. Event notifications can however work without event sources IMO
Wondering if Jenkins uses event-driven arch
amazing
just for Counter strike example. I understood it :)
I like your videos (I even took your paid course). But this video is not up to your standards. You are mixing event sourcing with event driven design (whtout mentioning).
Good diagram - it is very well explain
It is called chronical event sourcing
It has many cons and one pros
I hope no one consider to implement it into production instead take it as an option to takle mostly
Kind of State design pattern partly.. You seem very happy though
Couple more points
Your last few lines were “Node JS supports it”. Architecture has nothing to do with language/framework. One can use NodeJS, Python, Golang, java anything that supports EventBus tool (Kafka, Redis, etc)
With this architecture, (micro)scalability can be a problem. Unless there’s a way to handle race-conditions between multiple subscribers to a channel, you may end up with duplicate data & processing. Or else, you are struck with single instances of a micro service for the rest of your life.
Need more videos with real time examples with micro service architecture
Hi, nice video Gaurav!
Just to be clear FPS doesn't work like that right? I know you just used it as an example.. but there must be some problem implementing EDD for FPS. If there is none..I don't know why I still have to suffer from latency issues in 2021. Am I missing something?
@gaurav sen- enjoy watching your videos. You are very knowledgeable. Not many recent videos. you should do more. all the best
This is not event sourcing...
Excellent presentation that talks about different types of application architecture patterns leading to micro services and then different patterns and concerns for micro services architecture
But everyone should make their own assessment on whether microservices is the right architecture for what they are trying to solve
Oracle monolithic computing - RDBMS Kafka distributed computing and data stores Long live the king !!
RedPanda
Thanks ...
Good discussion and clear explanation of architectural aspect
This is best presentation and tech talk I heard in recent days. Surely the presenter is highly experienced and precise, concise in explaining the whole picture.
This was a very nice talk. Thank you.
Confused explanations
serde --->producer to consumer in-between a schema store known an schema registry
of of of of of of of of of....
From listening to this topic you begin to see how we can't really decide on our choice of architecture. We've done request-response, we've done events, and yet we keep changing vacillating back and forth between the two. Coupled but simple, Decoupled but complex. Kafka's main feature that is different is replaying event streams and it's scale. That is what is driving all of this re-evaluation of architecture design. However, microservices have produced a similar consternation over system design about how these services should interact with each other and how much each service should be responsible for its own destiny (ie a service unto itself, or a collaborative member of a larger system). And, now we're suggesting duplication of storage within the microservices. Each service will now store a copy of all of the data its dependent upon is the advice du jour. At best this is mere duplication of work at worst this has the potential to just recreate many monoliths especially for services that depend upon many things which always happens as product cycles demand. Certainly this can't be good advice for storing user information which has PII concerns and security implications. It doesn't make sense to spread data across many storage tiers that requires extract careful logic and governance unless you're just trying to make your CISO's job harder. Reusing APIs isn't just about data; it's also logic encapsulation! Which if you follow this advice of storing other microservice's means you now have to follow the logic that goes with that data too. Just having the data doesn't absolve you from the responsibilities of using and managing that data. The utopian dream of events everywhere and little to zero request response will be limited by these inconvenient facts. Then there is the issue of microservices need reuse to keep them small. If I can push off logic that isn't central to my problem domain then I can simply reuse someone else's work, and that keeps me light and small. Yes it creates a dependency, but I'm trading off my independence for convenience and a smaller footprint.
There is lots to like about Kafka and event streams, and persistence of streams really is what's new here, but I'd be careful about how much this "changes everything" mentality you take away from this because we've seen this play before.
Awesome....
Very informative and insightful talk, thank you!
Thank you
hi Guido, Interessing slides and work!! But i'd like to seek attention on the part about microsevices database. you say "microservice might share a central database to exchange states at low level with other (Micro) seevices". I think that's against the microservices principles, patterns and best practices, namely independency and non-centralization. As of a statefull case (vs stateless) and self-boundary , a microservice must handle data (input) contained in its scope (domain/context/subcontext). Thefore, Payment can't share state at low level with Order. But paiment can only do so with a microservice part of its domain context/subcontext boundary. Any external-domain microservice must exchange through endpoint, topic, etc.Because a microservice is and must be responsible for its own inner logic. So when presenting SOA along side microsevices we need to be carefull, as soa is used to implement component-based services:)
I really appreciate your job
Thanks
Well presented.
ppt for this event i found at https://static.rainfocus.com/oracle/oraclecode18/sess/1523054308218001XeLm/PF/microservices-with-kafka-ecosystem_1527748535903001rXOu.pdf
This is a great talk, one question that I have is: People treat order Pizza as a typical async scenario and a good example for event driven architecture, like I put an order event, then get back the order finished event etc.
Most cases, the client-side just want to get the realtime data, like I try to get my messages, get the latest emails, use credit card to purchase something. Does this mean we can't use event driven architecture here for the online process? Only for the offline BI/Search purpose?
Must watch! Covers all the questions you may have moving a traditional monolithic application to microservices and scale it.