Poshmark — Scaling Social Commerce to 80M+ Users & $1.8B GMV
The results
Metric
Architecture Model
Transaction Concurrency
Search & Feed Latency
AI & Ops Productivity
Before
Monolithic architecture bottlenecking developer speed & release cycles
Frequent database locking & capacity challenges during peak sales spikes
High latency in item searches & lack of personalized social feeds
Manual customer feedback analysis & high trust/safety overhead
After
Event-driven microservices built on high-throughput cloud architecture
Global transaction platform handling $1.8B GMV & localized payments
Sub-second search indexing & ML-powered intelligent feed ranking
LLM voice-of-customer insights & multi-signal fraud mitigation
Key Features Used
- High-throughput microservices — Event-driven pipelines built with RabbitMQ, Redis, & MongoDB
- Global Payments & Payouts — Localization & integrations (Adyen, Braintree, PayPal, Razorpay)
- AI Personalization & LLMs — ML feed ranking & Voice-of-Customer customer intelligence platform
- Trust, Safety & KYC — Multi-signal fraud detection, SOCURE verification, & PCI DSS/GDPR compliance
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