Case studies — Frank Robert Anderson

org

Solving the one engineer can work on a codebase at once problem

One engineer per project was the ceiling. Using tooling and process to clear bottlenecks.

1 → 12 engineers per release

Situation: One project, one engineer. Having two people work together required a great deal of coordination and communication.
Constraint: Two or more engineers trying to work together could easily override each other's work. Config might be stored in the database and require extensive manual steps for deployment. This slowed down development cycles and forced every engineer to be a full stack expert; there was little room for a junior.
Decision: Switch to git and adopt GitLab. Start using a development workflow with merge requests and timed releases. We ignore vanilla scrum and gitflow in favor of semantic git.
Tradeoff: Dynamic content is no longer in version control. Branching with multiple developers is possible in SVN, but git is easier to manage and has better tooling and developer experience.
Result: Two engineers on a release used to be a struggle; five became routine, and over twelve during crunch periods. Any project could take any number of engineers at any time, and a release no longer waited for the one person with the expertise to be free.

scaling

Using AWS serverless to build a COPPA-compliant save-and-share feature that has run for ten years.

20M objects · 10 years · 100% uptime

Situation: Our client wanted a way to save and share the current state of the application.
Constraint: The audience was four-year-olds, so the feature had to comply with COPPA. Technically it had to scale from zero users to thousands while keeping storage and maintenance costs to a minimum.
Decision: I chose AWS serverless for the application and S3 for storage, deployed through AWS SAM — which was new at the time.
Tradeoff: Hosting the service on a dedicated machine was the comfortable route. It would have meant a beefy box, or several boxes and a load balancer, sized for a peak we could not predict. AWS's managed services ticked every box, and the free tier made it cheap to find out whether an unproven system would hold.
Result: Prototyped in 2016, launched in 2017, and still running mostly the code I wrote then. Seven contributors across five releases, most of them maintenance or language-compatibility updates. Ten years at 100% uptime. The monthly bill is S3 storage and bandwidth on more than 20 million objects and roughly a terabyte. For a well-architected system at a certain scale, serverless is unbelievable.