Craig Peterson is a pragmatic software engineer with 14 years building reliable backend systems, SRE tooling, and DevOps automation, currently contributing at Datadog after a multi-year SRE role at Grafana Labs. He has a strong open-source footprint across notable projects like Bosun, Grafana Tanka, Grafana Agent, and StackExchange dnscontrol, where he improved alerting, observability pipelines, Kubernetes workflows, and ACME certificate automation. Comfortable across backend, DevOps, and some frontend work, he repeatedly focuses on operational readiness—installation, deployment manifests, instrumentation, and state management—to make systems more resilient and manageable. Based in New Rochelle, NY, he brings practical production experience from companies including Stack Overflow and Ancestry, and a pattern of shipping small, high-impact contributions (e.g., fmt checks, state-file backups, label selectors) that reduce operational friction.
Contributions:10 releases, 156 commits, 492 PRs in 4 years 4 months
Contributions summary:Craig primarily focused on maintaining and improving the alerting framework. Their contributions include fixing queuing notifications, integrating a go fmt check into the build process, adding instrumentation for state file size, and providing an endpoint to backup the state file. Furthermore, the user addressed issues related to the handling of incidents and implemented code for different alert schedules and also added a feature to backfill OpenTSDB metrics.
Contributions:167 reviews, 58 commits, 244 PRs in 2 years 8 months
Contributions summary:Craig primarily contributed to the operational aspects of the Grafana Agent, focusing on build, deployment, and configuration management. They updated installation scripts, deployment manifests, and image versions, specifically targeting Kubernetes deployments. The user also made changes to the operator configuration, incorporating new features and addressing issues related to deployment, including enabling HTTP/2 and allowing privileged containers where necessary. The work demonstrates a clear focus on improving the agent's operational readiness and integration with Kubernetes.
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