MessageRelay Digital Academy

Data · Intermediate

Stream Processing with Kafka

Design topics, consumer groups, and fault-tolerant stream jobs with hands-on broker labs.

Learn to model event streams for operational dashboards and downstream warehouse loads. You configure local Kafka clusters, implement at-least-once consumers, and explore compaction strategies. Mentors simulate production incidents—broker restarts, poison messages, and lag spikes—so you practice runbooks, not slides.

₩1,450,000 · 10 weeks · Live online

Request information Refund & Cancellation
Engineer reviewing real-time metrics dashboard in dim lighting

Included in this cohort

  • Docker-compose broker stacks per learner
  • Consumer lag dashboards in Grafana
  • Dead-letter queue pattern lab
  • Schema registry introduction (Avro)
  • Incident response tabletop exercise
  • Mentor-led architecture critique
  • Stream-to-warehouse handoff module

Outcomes you can show

  1. Operate a three-topic pipeline with monitoring
  2. Document retry and idempotency choices
  3. Tune consumer parallelism for a sample workload
Portrait of Eun-ji Han

Mentor

Eun-ji Han

Stream platform lead; built real-time fare reconciliation for a mobility startup.

Common questions

Core labs are local for cost control. An optional module covers Confluent Cloud patterns with your own trial account.

Learner notes

"Replaying the poison-message lab with our team changed how we write consumer configs. Clear, though broker tuning week was intense."

Jae-min · Backend developer · LogiFlow

"Kafka lag tabletop was the highlight—felt like an on-call shift without the pager."