Making OKE Easier to Run at Scale
Focused on the platform gaps that made OKE harder to run in production.
The problem
The real blockers were operational: slow or brittle node bring-up, image availability issues, limited observability, and rough edges that became painful at scale.
My contribution
Worked across customer signals, internal constraints, and roadmap tradeoffs to focus on the platform gaps that most directly blocked adoption.
Helped drive investments around Ubuntu images, observability, and other platform improvements so OKE better matched how infrastructure teams actually run demanding workloads.
Treated the work as platform product design, not just feature intake, by pushing on operational clarity and the day-two experience.
The decisions
A lot of the pain sat at the seams between imaging, capacity, and adjacent infrastructure teams, so progress required alignment across multiple systems rather than one isolated feature.
The challenge was deciding which platform issues were true product blockers versus one-off edge cases, then prioritizing the ones that would materially improve production confidence.
Where it landed
Helped move OKE toward a stronger fit for demanding production workloads.
Reinforced my approach to infrastructure product work: adoption is often won by reducing operational drag, not just adding surface area.