// capabilities
Scaling that holds up
- Designing scaling strategies based on causal signals (requests, saturation, backpressure)
- Balancing responsiveness, churn, & cost along with reliable scaling
Signals that tell the truth
- End-to-end design & maintenance of observability systems
- Designing systems that use AI agents to automate incident resolution & reporting
- Improving log delivery, query performance, & debuggability at scale
Datastores & migrations, zero drama
- Scaling both data & observability stores for performance & reliability
- Executing near-zero-downtime migrations of storage systems
- Improving time-dependant & performance-based scaling
Kubernetes platforms teams ship on
- Evolving Kubernetes platforms in an org-wide setup for parallel & rapid development
- Enabling security & compliance-first development environments
- Treating Kubernetes, networking, & cloud infra as a single system
Reliable without the bill shock
- Cost optimization without sacrificing reliability
- Using SLOs to align engineering decisions with user impact
- Treating cost as a first-class operational signal
... I can do linux too xD