Jarvis — Real-Time Product
Defect Intelligence at Scale
A cloud-native pipeline that ingests, deduplicates, and refines millions of product defect signals a day — turning noisy upstream events into a single trusted source of truth for the whole enterprise.
0+
events processed / hour
The pipeline, live
Raw defect events flow left to right — ingested, deduplicated, refined, and fanned out. Hover any node to inspect it and freeze its inbound traffic.
Upstream producer
Catalog Feeds
Bulk vendor and marketplace catalog feeds stream in item records with wildly varying completeness.
Amazon Kinesis Data Streams
Kinesis Ingest
The ingestion backbone. Absorbs high-throughput bursts with sub-second latency and buffers them across shards for parallel consumption.
AWS Lambda
Processing λ
Consumes Kinesis records, applies business rules, normalizes schemas, and enriches raw defect payloads into canonical records. Concurrency scales with shard load.
Amazon DynamoDB
DynamoDB
Composite keys + conditional writes guarantee idempotent, exactly-once processing across retries and shard replays. Duplicates are rejected here.
AWS Lambda
Refinement λ
Reconciles conflicting signals, resolves schema drift, and collapses many events into one authoritative record per product entity. Rejects malformed data.
Amazon Kinesis Data Streams
Kinesis Output
Publishes enriched, high-fidelity records to a downstream stream, preserving a loosely-coupled pub-sub contract across the enterprise.
Downstream consumer
Analytics
Data-quality dashboards read the canonical defect feed.
Drive the simulation. Push traffic, inject a bad record, or freeze the stream.
Events / sec
890
Duplicates blocked
0
P99 latency
47 ms
Downstream fan-out
3