Workbench/resume/projects/proj_3d12bb7f03edcb77e7360644
Event Pipeline Rebuild
One project stays anchored as the deep-dive unit: context on the left, session history on the right, and explicit project prompts ready to practice.
- project_id
- proj_3d12bb7f03edcb77e7360644
- sessions
- 0
- highlights
- 3
- tech_stack
- 4
Project context
Project context stays visible because the deep-dive flow should practice storytelling, not generic chatting.
Rebuilt a synchronous order-processing flow into an event-driven pipeline for better throughput and resilience.
Highlights
Highlights give the deep-dive session concrete material to probe.
Cut p95 latency by 42 percent after decoupling hot-path calls.
Designed idempotent consumers, retry handling, and DLQ recovery.
Balanced consistency trade-offs with compensating workflows and monitoring.
Suggested deep-dive questions
Suggested prompts come from the structured project entity and seed the first session turns.
What problem was Event Pipeline Rebuild solving, and what part did you personally own?
Why did you choose Java and Kafka for Event Pipeline Rebuild?
Walk through the hardest part of Event Pipeline Rebuild and how you delivered "Cut p95 latency by 42 percent after decoupling hot-path calls.".
What outcome, metric, or business impact proves Event Pipeline Rebuild worked well?
Tech stack
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JavaKafkaMySQLRedis
Session history
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Empty state
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