Live webinarEvent-DrivenArchitectureQueues

Event-driven architectures behind modern AI products

Request-response melts under AI workloads. Event-driven is the shape that holds.

Param Harrison

Param Harrison

Cofounder, AEOsome.com · Chief Mentor, learnwithparam.com

60 minutes · advanced
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Why this one matters

AI workloads are slow, expensive, and bursty. Traditional request-response patterns melt under them. This session walks the event-driven architectures that modern AI products rely on: queues that absorb bursts, workers that scale on cost signals, idempotent consumers that retry without blowing up spend, and the observability layer that keeps the whole thing legible.

Who should watch

  • Backend engineers running async AI workloads in production
  • Platform engineers building the AI infrastructure for other teams
  • Senior engineers whose synchronous AI API is melting under traffic

What's on the menu

  • Why AI traffic shape breaks classic request-response assumptions
  • Queues that absorb bursts without torching your bill
  • Workers that scale on cost signals, not just queue depth
  • Idempotent consumers that retry safely against flaky models
  • Observability across an event-driven AI pipeline

Leave with a blueprint

  • Shape AI traffic through queues so bursts do not take the system down
  • Design workers that scale on token cost, not request count
  • Build idempotent consumers that retry without doubling the spend
  • Trace a request across an event-driven AI pipeline for debugging
  • Apply the pattern to your own product in the next sprint