Travis Reeder is a seasoned technology leader and Chief Technology Officer based in San Francisco with 16 years of experience building cloud-native, serverless, and blockchain systems. He founded and led Iron.io (raising $17M and powering services like IronWorker and IronMQ used by customers such as Walmart and CNN) and was the creator and lead architect of Oracle Cloud Functions and the open-source Fn Project. Currently CTO at Pearpop, he’s building an AI-first creator platform and also advises Chainparency after serving as its CTO, bridging product strategy with supply-chain blockchain proofs. A pragmatic engineer who “builds and breaks things,” his hands-on contributions span reverse-proxy and worker orchestration work in major serverless repos and low-level Docker/image infrastructure. That combination of founder grit, enterprise architecture, and DevOps depth helps him move complex distributed systems from prototype to production.
16 years of coding experience
27 years of employment as a software developer
BSc Computer Science, BSc Computer Science at University of Calgary
Contributions:87 commits, 22 PRs, 67 pushes in 1 year 4 months
Contributions summary:Travis primarily focused on creating and updating build scripts for various Docker images within the repository. They added new build scripts for languages like Java, Kotlin, and PHP, as well as modifying existing scripts for Ruby, Node.js, and Go. They also addressed bugs and updated base images, including Alpine, indicating a strong focus on infrastructure and image management.
IronFunctions - the serverless microservices platform by
Role in this project:
Back-end Developer & DevOps Engineer
Contributions:283 commits, 73 PRs, 125 pushes in 4 years 3 months
Contributions summary:Travis primarily contributed to the back-end functionality of the IronFunctions platform, specifically the router component. Their work involved creating reverse proxy features, incorporating IronCache, and managing the addition and removal of worker instances. Furthermore, they made changes to the function's codebase to start new tasks in response to connection errors, showing an understanding of the system's architecture and operational considerations. The user also updated the code to use more modern practices, such as JSON parsing and incorporating of config parameters.
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