Legacy Rescue

Saved a failing API monolith and slashed infrastructure bills by 85%.

API Availability99.99%

Latency Reduction8,400ms → 45ms

Billing Optimization85% Reduction

LOG_01 / THE BREAKDOWN (PROBLEM)

A fintech client was paying $12,000/month for a monolithic API cluster that crashed multiple times daily. Connection leaks and poor queue configurations caused transaction write times to exceed 10 seconds.

LOG_02 / THE MITIGATION (SOLUTION)

We intervened to isolate memory bottlenecks. We decoupled the high-throughput payment processing layer, rewriting critical endpoints in Go and compiling them into Cloudflare Workers to run directly at the network edge.

LOG_03 / RECOVERY TIMELINE (PROCESS)

→Outage Diagnosis: Traced memory leaks to a poorly implemented database connection pool.

→Decoupling: Isolated hot API endpoints and routed them through an edge proxy.

→Edge Rewriting: Rewrote transaction pipelines using Workers and Durable Objects.

→Verification: Ran shadow load testing to ensure exact transaction parity.

LOG_04 / SYSTEM OUTCOMES

Monthly server overhead reduced from $12,000 to $1,800.
API availability stabilized to 99.99%.
Transaction latencies dropped from 8,400ms to 45ms.

LOG_05 / ENGINE DETAILS

RECOMPILED STACK:

Cloudflare Workers & Durable ObjectsGo & WebAssemblyPostgreSQL connection pooling

TECHNICAL CONSTRAINTS:

Migrating transaction processing live without stopping user transactions. We solved this by using a proxy that dynamically shadowed traffic to the serverless engine while database migrations were completed.

Have a system that needs scaling?Initiate Brief