Andrew Glaude is a software engineer with 12 years' experience building reliable, cloud-native backend systems and developer tooling from Cambridge, MA. Currently at Datadog, he contributes to high-impact open-source projects such as the Datadog Agent and dd-trace-go, improving tracing, container detection, and performance of monitoring infrastructure. Previously he led a squad at Cimpress designing event-driven availability services in Go and Rust for 100k+ products on Kubernetes and Google Cloud, pairing hands-on coding with mentoring. He brings deep systems and observability expertise—evident in work on APM, Kafka tracing, and flaky-test hardening—combined with strong academic foundations (BS/MS Computer Science, RIT). Notably, he blends low-level agent/DevOps intuition with product-scale system design, making him effective across both operational and engineering domains.
12 years of coding experience
5 years of employment as a software developer
B.S./M.S., Computer Science, UGRAD: 3.93 GRAD: 3.78, B.S./M.S., Computer Science, UGRAD: 3.93 GRAD: 3.78 at Rochester Institute of Technology
Datadog Go Library including APM tracing, profiling, and security monitoring.
Role in this project:
Back-end Developer
Contributions:3 releases, 545 reviews, 71 commits in 1 year
Contributions summary:Andrew primarily contributed to the Datadog Go library, focusing on features related to tracing and APM. Their work included bumping the library version, adding the B3 flag for header propagation, and integrating tracing for SQL database connection times. Further contributions include implementing tracing for Kafka readers and writers and fixing support for deprecated interfaces. They also added context logging hook to logrus.
Contributions:433 reviews, 60 commits, 145 PRs in 8 months
Contributions summary:Andrew primarily contributed to the Datadog Agent's trace-agent functionality, focusing on performance improvements and bug fixes. Their work included enhancing support for JSON array syntax in environment variables, stopping the use of deprecated features, and refactoring code to reduce duplication and improve efficiency. Additionally, the user addressed testing flakiness and implemented enhancements to container ID detection, demonstrating expertise in system-level aspects of the agent.
golangdatadog-agentagentobservabilitypmm
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