Philip Norman is a seasoned infrastructure and observability engineer with 13 years of experience building and leading teams across cloud-native and AI infrastructure in the San Francisco Bay Area. He has driven observability and metrics work at Mesosphere, Stripe, and Determined AI (HPE), and now manages infrastructure for AGI Autonomy at Amazon, bringing production-grade monitoring and test automation expertise. Philip is a practical technical lead who blends hands-on engineering with product ownership, having improved Prometheus-focused integration tests for the well-known DC/OS project to reduce flakiness and adapt to changing metric formats. His background spans front-end beginnings to deep systems work, and his BA in Classics underscores a habit of clear thinking and precise communication in complex distributed systems.
13 years of coding experience
14 years of employment as a software developer
BA (Hons) Classics, BA (Hons) Classics at University of Liverpool
Contributions:174 commits, 85 PRs, 348 comments in 2 years 1 month
Contributions summary:Philip primarily focused on enhancing the integration tests for the DC/OS platform's metrics collection. They modified existing tests to accommodate changes in metrics formats, including the transition from labels to tags and the addition of fault domain awareness. Their contributions involved updating tests to validate Prometheus metrics and ensuring that the metrics server is available across all nodes, reflecting an understanding of testing and monitoring within the DC/OS environment. They made modifications to tests to address flaky behavior.
Contributions:18 pushes, 1 branch in 6 years 7 months
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Philip Norman - Member Of Technical Staff at Amazon