caching2

@startuml title Cache Miss → Hydrate → AI Tables → Consumer Query (Minimal) skinparam sequence { ArrowColor black ArrowThickness 1 ParticipantBorderColor black ParticipantBackgroundColor #FFFFFF LifeLineBorderColor black LifeLineBackgroundColor #FFFFFF } actor Consumer as C participant "Kafka Brokers" as K participant "Fast Cache (NVMe/SSD)" as FC participant "Cold Tier (Object Store)" as CT participant "AI Pipelines\n(Chunk/Embed, Feature Compute)" as AIP database "Lakehouse\n(AI Tables: Features, Embeddings, Labels)" as LH == Operational read == C -> K : Subscribe / poll for records K -> FC : Read segment/key FC --> K : MISS FC -> CT : Hydrate segment/key (fetch) CT --> FC : Segment bytes FC --> K : Segment pointer / data (PROMOTE) K --> C : Deliver records (ms SLO) note over FC,CT Hydrate under SLO (e.g., p95 < 250 ms). Segment promoted to cache on success. end note == Stream → AI tables (parallel/continuous) == K -> AIP : Stream events/docs AIP -> LH : Write/merge to AI Tables LH --> AIP : Ack / checkpoint note over AIP,LH Features, embeddings, labels materialized for training & RAG. end note == Analytics / AI batch reads == C -> LH : BI/ML/RAG query on AI Tables LH --> C : Result set @enduml