Concurrency proof
Load-tested and operated beyond 10k concurrent sessions during peak windows.
Payments/api5 screens
Payment Infrastructure
Hardened payment-adjacent services for 10,000+ concurrent users with clear failure modes and recovery paths.
Screen walkthrough
A fuller gallery for the product story.
This gallery is meant to show progression, not just a single hero frame. Use it to talk through navigation depth, records, analytics, and workflow context during a call.
/api
Chapter 01
Brand-aligned visual — client interfaces are anonymized for this launch story.
Overview
A payments-heavy product needed to survive traffic spikes without silent data loss. We redesigned hot paths, added backpressure and idempotency, and instrumented the pipeline so operators could see incidents before customers did.
Strongest story angle
Best for teams asking whether you have seen real money movement at scale — latency, retries, and reconciliation included.
Observable modules
Ingestion workersIdempotent APIsReconciliation jobsRate limitsDashboards
Client story
Problem, approach, and outcomes
Context
A fintech platform processing high volumes of payment-adjacent traffic needed reliability during marketing-driven spikes.
Problem
Burst traffic caused queue backlogs, duplicate processing risk, and opaque failures. Engineers were firefighting without good traces.
Approach
Mapped the critical path, added idempotency and deduplication at boundaries, tuned worker pools with backpressure, and shipped observability (metrics, traces, structured logs) tied to business KPIs.
Architecture
Edge API → Redis-backed queues → horizontally scaled workers → ledger writer with optimistic concurrency → Postgres + read replicas → Grafana/OTel for SLOs.
Tech stack
FastAPIPostgreSQLRedisDockerAWS ECSOpenTelemetryGrafana
Results
- 10,000+ concurrent users handled during peak tests and live campaigns
- Duplicate payment incidents driven down via idempotent command handling
- Mean time to detect/restore improved with actionable dashboards
Timeline
Stabilization sprint: 3 weeks. Hardening + load program: 5 weeks. Continuous improvement: monthly cadence.
Why this one works
Three angles worth carrying into the final write-up.
Operational clarity
Structured logging, tracing, and runbooks so on-call engineers could respond quickly.
Safe deploys
Canary releases and feature flags for risky payment paths.
Motion outline
This sequence can still become a short teaser.
- 01
Start from the spike that broke the old stack.
- 02
Show the worker topology and idempotency keys.
- 03
End on steady-state dashboards and customer-visible latency wins.
Next publishing pass
The structure is now cleaner: better screenshots, stronger conversion paths, and shared page chrome that behaves correctly. The next layer is adding repository-backed build notes and verified outcome data.
Still worth adding
- 1. Verified repository context for stack and architecture notes.
- 2. Approved proof points to replace generic performance language.
- 3. Short teaser renders once the repository evidence is in place.