i build observability and infrastructure at rivian × volkswagen group technologies — the joint venture between rivian and vw. day to day that means kubernetes, datadog, grafana, ebpf, and a lot of yaml.
i've led our datadog tenant migration across 10+ engineering teams, built a custom crossplane provider in go when the official one didn't cut it, tuned apache druid for high-throughput vehicle telemetry, and architected a self-hosted LGTM stack (loki, grafana, tempo, mimir). i also serve as on-call SRE for production incidents.
more recently i've been defining observability strategy for our internal AI/ML teams and building AI agents with a custom tool-calling framework that integrates across slack, argocd, crossplane, and EKS.
before this, i interned at rivian where i built an anomaly detection system on grafana OSS for vehicle telemetry and designed CI/CD pipelines that cut deployment lead times by 60%.
studied computer science at georgia tech. based in palo alto.
single-binary observability platform — a self-hosted alternative to datadog/grafana/pagerduty. uses ebpf kernel probes for zero-config TCP tracking, HTTP tracing, and wire-format parsing of mysql, postgres, and redis. includes a cost intelligence engine that estimates equivalent vendor costs and a control plane for cardinality analysis and data shaping. written in go and c.
This is a test post to demonstrate the new publishing workflow.