Platform Engineer making AWS and Kubernetes easier to debug, operate, and evolve.

A Go service that turns 30–60 minutes of manual AWS route investigation into minutes.

Problem

Tracing connectivity across accounts meant manually following VPC route tables, Transit Gateways, and Cloud WAN. A typical investigation took 30–60 minutes.

Outcome

Reduced typical manual investigations from 30–60 minutes to minutes with a repeatable tracing workflow.

Root-cause analysis of EKS CPU saturation that connected workload sizing, autoscaling, and .NET runtime behavior.

Problem

A production EKS workload experienced CPU saturation at approximately 15 load per core. Understanding the failure required investigating the interaction between resource sizing, scaling behavior, and the application runtime.

Outcome

Designed a reusable rightsizing policy for latency-sensitive workloads to address the failure mechanism and reduce the risk of recurrence across critical workloads.

Kyverno Chainsaw tests that validate a shared application chart through upgrades, canaries, and rollback, catching multiple regressions before publication.

Problem

Developers rely on an existing shared Helm chart to deploy images into EKS with configurable platform defaults for Argo Rollouts canaries, Datadog integration and monitoring, labels, KEDA autoscaling, and Istio configuration and HTTP routing. Faulty rollout and Kubernetes Service-selector configuration in patch releases had caused production outages. With developers advised to allow patch updates within major/minor version constraints, validating compatibility before publication was especially important.

Outcome

Caught multiple regressions before shipping, particularly selector-label changes that could break API endpoints. Established repeatable validation of chart upgrades, canary progression, traffic, workload health, and rollback before publication.

Repeatable dependency discovery across 200+ components, later reused to map six applications in less than a day.

Problem

Disaster-recovery planning needed a dependency view across more than 200 platform and application components, with evidence spread across repositories, infrastructure, and AWS cost data.

Outcome

Mapped dependencies across 200+ components for disaster-recovery planning. Later reused the tooling to map dependencies for six applications in less than one day.