DevOps & developer platforms
Systems for shipping
better software.
Selected work across developer experience, continuous delivery, infrastructure, productivity, and education.
01 Scope
- Engineering survey and structured interviews across product, platform, and operations teams
- Audit of deploy pipelines, local dev tooling, documentation practices, and platform team ownership
- Executive report synthesizing findings into prioritized recommendations and an org design
Key findings
- Manual deploy coordination via Trello and Jenkins was estimated to consume ~270 engineer-hours per week — roughly seven full-time developers' worth of time
- Docker and local development environments were the top frustration for 60% of surveyed developers, with resets taking up to 30 minutes
- Platform responsibilities were unclear across operations, developer systems, and data engineering — even among the teams themselves
- Documentation was fragmented across Confluence, repo READMEs, and ad-hoc tools, driving tribal knowledge and siloing
Deliverables
- Roadmap to replace manual deploy queues with automated continuous deployment and actionable deploy logging
- Plan to consolidate local dev containers, migrate off a home grown solution, and adopt Docker Compose with shared adjacent services
- Proposed Platform department reorganized into CI/CD, developer infrastructure, containers, and datastores teams — with hiring plan to address bus-factor risk
02 Scope
- Assessment of branch-deploy workflows, canary coverage, and deploy monitoring under rapid org growth
- Design of a state-machine deploy model with automated stage progression and rollback paths
- Integration with existing chatops entry points and a first-party deploy overview UI
Key findings
- A single high-traffic coordination channel could no longer track deploy state — developers pieced together hundreds of messages to follow one release
- A single low-percentage canary stage missed issues that only surfaced at full production traffic
- Developers spent significant time babysitting multi-step deploys instead of shipping
Deliverables
- Automated deploy progression from a single command, with timed gates between stages
- Multi-tier canary rollout to catch failures earlier without unacceptable blast radius
- Consolidated deploy UI replacing fragmented chat updates — informed later industry CD patterns
03 Scope
- Historical assessment of developer environment approaches across years of company growth
- Design and rollout of a command-line platform for cloning, bootstrapping, testing, and running services
- Architecture splitting application code on-host from shared infrastructure in a lightweight VM
Key findings
- Full-machine VMs were slow for code iteration; running everything on-host made services fragile and hard to reset
- Teams needed one command to go from zero to a working project, including migrations and dependencies
- Deviating from the standard stack was near-impossible, stifling experimentation
Deliverables
- Unified developer CLI adopted across the majority of active repositories
- Service VM pattern separating code from MySQL, Redis, and reverse proxy infrastructure
- Documented migration path toward container-native local environments and remote service mocks
04 Scope
- Framework for tests and error messages as just-in-time education at organizational scale
- Dependency graph analysis across ~1,000 repositories to identify representative test targets
- Performance profiling and boot-time optimization for a widely used Ruby toolchain
- Mitigations for version-control pain points in very large repositories
- Managed developer tooling suites for teams with thousands of engineers & developers
Key findings
- Word-of-mouth standards break down as teams grow — automated guardrails scale better than policy
- Developers need errors that explain what went wrong, why it matters, and how to fix it
- Large dependency changes require representative repo clusters, not ad-hoc manual selection
- Boot-time friction compounds across every test run and every developer machine
Deliverables
- Test-driven deprecation patterns and actionable error messaging adopted org-wide
- Graph-based clustering methodology for safe large-scale dependency rollouts
- 60% reduction in Ruby application boot time through profiling and toolchain improvements
- Documented strategies for clone, fetch, and pull performance in monolithic repositories
05 Scope
- Founded and organized an annual industry day connecting students with developers, data scientists, product managers, and recruiters
- Taught the capstone design course through a university innovation lab, exposing students to startup technologies, ideas, and processes
- Founded a not-for-profit teaching children aged 7–13 the basics of coding, technology, and design
Key findings
- Students benefit most when industry contact is structured and recurring, not limited to one-off career fairs
- Capstone courses need real startup constraints — ambiguity, timelines, and shipping — not isolated toy projects
- Early computing education works best with hands-on, age-appropriate curriculum and sustained community support
Deliverables
- Multi-year industry day program at a leading computer science department
- Capstone cohorts guided from product idea through design, implementation, and demo
- Not-for-profit reaching children across multiple communities with a repeatable coding curriculum