Carson Anderson is a Principal Engineer with 13 years of hands-on experience designing and automating infrastructure, currently focused on Linux administration, Docker, and Kubernetes-based Infrastructure as a Service. He excels at solving complex production problems and building elegant automation — from automated package and Docker image pipelines to Kubernetes CRD refactors and topology compression for Vitess. At Weave and prior roles in Site Reliability and CloudOps, he has driven reliability and deployment improvements at scale while mentoring teams on robust operational practices. An active open-source contributor, he enhanced Kubernetes and Prometheus integration in notable projects, demonstrating both deep platform knowledge and pragmatic engineering. Based in Provo, Utah, Carson pairs a systems-first mindset with a developer’s appreciation for streamlined build and deployment workflows.
13 years of coding experience
12 years of employment as a software developer
Box Elder High School
Bachelor's degree Information Technology, Bachelor's degree Information Technology at Utah Valley University
Vitess is a database clustering system for horizontal scaling of MySQL.
Role in this project:
DevOps Engineer
Contributions:5 reviews, 11 commits, 9 PRs in 2 years 10 months
Contributions summary:Carson primarily contributed to the project's infrastructure and deployment aspects. Their work includes implementing Kubernetes-specific topology implementations, enhancing the build process through scripts like `k3s-up.sh` and `bootstrap.sh`, and refactoring the Custom Resource Definition (CRD) for Kubernetes compatibility. The user also added compression to the stored data within the K8s topology, indicating a focus on resource optimization for Kubernetes environments.
An implementation of the custom.metrics.k8s.io API using Prometheus
Role in this project:
Backend Developer
Contributions:1 review, 5 commits, 2 PRs in 2 months
Contributions summary:Carson primarily focused on modifying the Prometheus adapter's backend logic. They implemented a feature to allow metrics to be defined as namespaced, including code changes in `metric_namer.go`, `config.go`, and `metrics_query.go`. Additionally, the user added documentation, tests, and refactored the code by splitting `ExternalMetricsQuery` and `MetricsQuery` functions, demonstrating an understanding of the project's architecture.
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