Curtis Gagliardi

San Francisco, California, United States

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Summary

🤩

Rockstar

🎓

Top School

Curtis Gagliardi is a pragmatic full-stack engineer with 13 years of experience, based in San Francisco, focused on Ruby on Rails and Clojure for part-time and contract work. He combines hands-on backend and performance engineering — evident from his optimized parallelization work on a fast code-counting tool — with cloud/DevOps expertise, contributing meaningful improvements to kube-aws and Kubernetes deployment automation on AWS. Curtis has shipped production Rails applications and improved operational UX by adding better error handling, Route53 automation, and clearer CLI messaging for cluster tooling. He brings a systems-minded approach from earlier roles scripting data pipelines and automation in Python and Bash for research environments. Active on GitHub and in open source, he balances practical product work with low-level performance tuning and infrastructure reliability. Reach out to see both his OSS contributions and a few closed-source projects he’s quietly been building.

13 years of coding experience

2 years of employment as a software developer

BS, Computer Science, BS, Computer Science at Florida State University

English, Spanish

Github Skills (19)

kubernetes10

multithreading10

memory-mapping10

aws-cloudformation10

go10

aws10

performance-optimization10

kubernetes-pods10

error-handling10

rust10

route539

automation9

code-analysis9

infrastructure-as-code9

automations9

Programming languages (17)

JavaC++CRustGoHTMLKotlinShell

Github contributions (5)

cgag/loc

Jul 2016 - Feb 2022

Count lines of code quickly.

Role in this project:

Back-end Developer & Performance Engineer

Contributions:5 releases, 216 commits, 61 PRs in 5 years 8 months

Contributions summary:Curtis primarily worked on optimizing the `loc` repository, a tool designed for counting lines of code. They implemented a parallelization strategy to speed up the code counting process, experimenting with different approaches such as memory mapping and multi-threading. They also focused on performance improvements by integrating libraries like `memchr` and experimenting with madvise and fadvise system calls to enhance performance. Their work resulted in significant improvements in the code counting speed, as evidenced by their iterative approach and the emphasis on optimization.

linesrustcount-lineslines-of-codecount-lines-of-code

coreos/coreos-kubernetes

Mar 2016 - Oct 2016

CoreOS Container Linux+Kubernetes documentation & Vagrant installers

Role in this project:

DevOps Engineer & Cloud Engineer

Contributions:23 commits, 23 PRs, 1 branch in 6 months

Contributions summary:Curtis primarily contributed to improving the `kube-aws` tool, which is used for deploying Kubernetes clusters on AWS. Their work included enhancing success messages, fixing missing cluster name issues in the status command, and refining error handling related to AWS credential chains. They also added functionality to automatically create DNS records using Route53. These efforts focused on improving the user experience and automating aspects of cluster deployment and management on AWS.

containersvagrantinstallerscoreosansible

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