saas case study evidence builder

I have cataloged your artifacts and mapped your performance claims to the provided evidence. I also identified a critical security risk in your testing logs that must be addressed.

Case Study: High-Throughput Webhook Processor

Executive Summary

Rebuilt a legacy webhook ingestion system in Go to handle 50k events/second. Reduced processing latency by 77% while maintaining strict delivery guarantees.

Claim-Evidence Map

Narrative

Problem

The legacy system could not scale beyond 5k events/second, causing significant lag in downstream services. {C-001}

Reasoning

Go was selected for its native concurrency primitives. By utilizing a worker pool pattern, we avoided the overhead of per-request thread allocation common in the previous stack. {C-003}

Solution

Developed a custom dispatcher that balances incoming payloads across a pre-allocated pool of workers. {C-003}

Outcomes

Achieved a peak throughput of 50k events/sec. Average p99 latency dropped from 200ms to 45ms, verified via production monitoring. {C-001, C-002}

Artifacts and Captions

• IMG-99: Grafana dashboard screenshot — Caption: "Dashboard showing sustained 50k throughput and p99 latency metrics."
• CODE-01: Main handler code — Caption: "Implementation of the internal worker pool and channel-based dispatching."
• LOG-04: Testing log file — Caption: "Audit log demonstrating the identification of a hardcoded key during local testing."

Gap Report

Credibility Scorecard

• Claim coverage: 100% direct evidence
• Unsupported claims: None
• Confidentiality risks: High (LOG-04 contains hardcoded secret)
• Verdict: Needs revision (Security Fix Required)

Next steps

1. Redact the API key in LOG-04 and replace the artifact description.
2. Add a specific "Before" metric screenshot to strengthen the Problem section.
3. Export the final Markdown for your portfolio site.