Available for software engineering roles - backend systems, production reliability, cloud deployment, and AI-assisted workflows.

Production & Infrastructurecase-study

Production Recovery & Performance Rebuild

NDA-safe ransomware recovery case study covering data restoration, infrastructure hardening, CI/CD setup, and performance optimization for a service marketplace.

Case file

Main outcome

Restored 100% of production data with zero loss.

Secondary signal

Reduced page load time from 25 seconds to 3 seconds.

Evidence count

3 proof points

01

Problem

A production service marketplace needed recovery after a ransomware incident, safer access boundaries, and performance improvements without exposing private client details.

02

Solution

Restored service functionality, rebuilt safer cloud access patterns, hardened database access, rotated credentials, introduced Docker and GitHub Actions deployment workflows, and tuned the application path that was causing slow page loads.

03

Role

Incident recovery lead · Infrastructure and deployment owner · Performance optimization contributor · Stakeholder communication support

Impact

  • Restored 100% of production data with zero loss.
  • Reduced page load time from 25 seconds to 3 seconds.
  • Moved deployment work toward repeatable Docker and GitHub Actions workflows.

Technical Highlights

  • AWS infrastructure restoration and access hardening
  • MongoDB Atlas migration and safer network access controls
  • Credential rotation and IP restriction boundaries
  • Dockerized deployment path with GitHub Actions CI/CD
  • Performance profiling across frontend, backend, and database query paths
  • Non-technical incident communication for stakeholders

Proof

  • Ask Jay Services contract experience
  • Resume-aligned production recovery and performance claims
  • NDA-safe public case study only

Constraints

  • No private client screenshots, credentials, database names, or proprietary workflows are published.
  • Security incident details are intentionally summarized at a high level.
  • Claims are limited to externally safe operational outcomes.

Limitations

  • This case study is intentionally sanitized and does not include internal architecture diagrams.
  • Some implementation details cannot be public because they relate to client operations and security posture.

Roadmap

  • Add a generic incident-response diagram that avoids client-specific topology.
  • Add a public runbook template for production recovery workflows.

Next conversation

Let's make the next system less fragile.

Open to software engineering roles across full-stack systems, platform and reliability work, workflow automation, and applied AI. I value teams where I can keep learning while contributing to real systems and clear delivery outcomes.

Also open to freelance or contract work across full-stack builds, practical automation, technical SEO, and cloud delivery.