amazon-sqs-java-messaging-lib VS cadence

Save to SQS (i.e. save each Event to Amazon’s SQS queuing service)

Amazon SQS

Messaging/Queueing Systems (Amazon SQS, RabbitMQ, Beanstalkd)

The last stage is productionizing the model. The goal of this phase is to create a system to process each image/video, gather the relevant features and inputs to the models, integrate the models into a hosting service, and relay the corresponding model predictions to downstream consumers like the MCF system. We used an existing Safety service, Content Classification Service, to implement the aforementioned system and added two specialized queues for our processing and various service integrations. To use the model for online, synchronous inference, we added it to Gazette, Reddit’s internal ML inference service. Once all the components were up and running, our final step was to run A/B tests on Reddit to understand the live impact on areas like user engagement before finalizing the entire detection system.

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Work with an amazing team responsible for the infrastructure software that makes Uber’s data centers around the world reliable and scalable. If you want to solve the toughest engineering challenges alongside some of the smartest people in the industry, Uber Aarhus is the right place for you.

The team in Aarhus build and operate the stateless and stateful compute platforms used by nearly every other engineer in the company (Up - https://www.uber.com/en-GB/blog/up-portable-microservices-re... and Odin - https://www.uber.com/en-GB/blog/how-uber-optimized-cassandra...) as well as other related infrastructure projects such as Cadence - https://github.com/uber/cadence.

May be this..https://cadenceworkflow.io/

a managed esb orchestration for example is exactly same as step functions and workflow engines like cadence - https://github.com/uber/cadence

Having done a reasonable amount of messaging code in my time, I would say the final form of this sort of thing might look more like Cadence[0] than anything like this.

[0] https://github.com/uber/cadence

Emit events from your primary DB (postgres, etc.) to something like kafka or rabbitmq and then catch that in your search engine. There's also some end-to-end solutions like temporal (temporal.io) or cadence (https://cadenceworkflow.io/)