Kim Schaefer
Senior DevOps Engineer
Austin, Texas, United States
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Kim Schaefer is a Senior DevOps and Cloud Engineer focused on Kubernetes, GitOps, and secure platform engineering. She designs and operates production Kubernetes platforms on Google Cloud, with a particular interest in how deployment authority, auditability, and automation intersect in real-world systems.
Kim’s work centers on building GitOps platforms that teams can actually trust in production, especially in environments where change must be deliberate, accountable, and defensible. She enjoys translating complex architectural and security requirements into practical patterns that platform and application teams can adopt without sacrificing developer experience.
Kim is an open-source contributor and has previously spoken at Open Source Summit and GrafanaCON. She is especially passionate about sharing lessons learned from operating real systems—what breaks, what scales, and where architectural assumptions tend to fall apart.
Area of Expertise
Topics
K8s Dungeon Crawl: Learning Kubernetes Controllers and Webhooks Through a Roguelike Project
In this session, we’ll explore Kubernetes controllers, CRDs, and admission webhooks using K8s Dungeon Crawl: a modified roguelike game where in-game monsters are represented by live Kubernetes resources running in the cluster.
As gameplay unfolds, the Kubernetes control plane becomes part of the game itself. Monsters are represented as Kubernetes Deployments, dungeon entities are modeled as CRDs, and admission webhooks dynamically mutate and validate cluster behavior as gameplay progresses.
Using KubeBuilder, we’ll walk through how controllers and webhooks interact with the Kubernetes API while demonstrating reconciliation loops, admission control, CRDs, declarative state management, runtime policy enforcement, and event-driven Kubernetes behavior.
The session demonstrates controllers reconciling game and cluster state, mutating and validating admission webhooks, GitOps deployment using Helm and Argo CD, and observability with Prometheus and Grafana.
Rather than treating Kubernetes concepts as abstract control-plane mechanics, this session turns them into visible gameplay interactions that make Kubernetes behavior easier to understand and reason about.
GitOps for AI Infrastructure: The Operational Gaps Nobody Talks About
Large language models fit naturally into Kubernetes demos. Operating them reliably is a different problem.
Most operational challenges AI workloads introduce have individual mitigations: model caching, GPU autoscaling, persistent storage, artifact replication. The operational gap is how they compound. Solving them individually still leaves platform teams with unreliable deployments.
This poster examines the assumptions GitOps and Kubernetes tooling quietly depend on that AI inference workloads break: artifacts are small enough for standard operations, pods start fast enough for default probes, sync completion implies readiness, infrastructure state is disposable between deploys, and dependencies are visible and explicit.
Drawing from operating multi-cluster AI inference infrastructure across multiple environments, this poster presents deployment lifecycle diagrams, failure-mode taxonomies, and practical operational patterns for improving AI infrastructure reliability.
Declarative Systems Still Have Hidden State
Declarative infrastructure promises reproducibility: desired state is defined, controllers reconcile drift, and redeployments should behave predictably.
Except they often don’t.
This talk explores the hidden operational state declarative systems quietly depend on: webhook certificates cached in cluster resources, infrastructure dependencies that survive deletion, controller ordering assumptions, persistent node state, and lifecycle coupling reconciliation engines cannot see.
These problems become especially visible when infrastructure spans multiple systems or workloads take minutes rather than seconds to initialize.
Using real operational examples from Kubernetes and GitOps environments, this lightning talk examines why “delete and redeploy” frequently fails to produce clean state and why many reliability problems are actually hidden state-management problems.
The core lesson: declarative systems still depend on operational history, even when the infrastructure appears fully declarative.
Where Deployment Authority Lives: A Cloud-Native Design Pitfall in GitOps
Many cloud-native GitOps systems quietly treat a Git merge as both a change proposal and a deployment authorization. While this works in low-risk environments, it collapses two very different responsibilities into a single decision. As systems grow more complex, that shortcut creates ambiguity around authorization, accountability, and audit trails that many environments simply cannot tolerate.
In this lightning talk, we’ll reframe that assumption as a cloud-native architectural concern, not just a tooling or security issue. Using GitOps as the example, we’ll look at how proposal, approval, and enforcement often become unintentionally coupled, and why that coupling makes it harder to reason about who is actually allowed to deploy.
The talk will walk through the architectural implications of letting Git act as the final authority, including where deployment decisions truly occur and how auditability and accountability can be lost when authority boundaries are unclear. We’ll then show how treating deployment authorization as a first-class architectural concept leads to clearer responsibility boundaries and more defensible cloud-native systems.
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