about, skills, or projects to explore.Type a command, or press Tab to complete it. Or switch to .
about, skills, or projects to explore.Senior Platform Engineer • PLATFORM · CLOUD · DEVELOPER EXPERIENCE
I build cloud platforms, delivery systems, and developer tooling that help engineers and data teams ship reliable software and compute workloads across Azure, GCP, and AWS.

Azure landing zones rebuilt from an unusable Pulumi prototype, with the first development environment delivered in 10 days before extending the foundation to staging, production, GCP, AWS, and on-prem.
Azure · GCP · AWS · Pulumiplatform / evolvingDelivery standardized across AKS, GKE, and EKS with Argo CD, Helmfile, and Kustomize. Progressive rollouts and Vault-backed secret sync gave teams a consistent release path without committing secrets to Git.
Kubernetes · Argo CD · Argo Rollouts · Helmobservability / evolvingMetrics, logs, traces, and profiles unified across multi-cloud Kubernetes clusters in Grafana. Prometheus, Loki, Tempo, and Pyroscope support workload investigation, complemented by New Relic infrastructure and cluster instrumentation.
Grafana · Prometheus · Loki · Tempotooling / evolvingDeveloped custom Go CLIs, Kubernetes admission controllers, and image lifecycle controllers to automate operations and enforce policy as code.
Go · Python · Kubernetes · Admission Webhooks / completedA failed Pulumi prototype rewritten into an Azure development environment delivered in 10 days, followed by staging and production.
Pulumi · Azure · Infrastructure as Code · Landing Zones / completedHow a stale image pipeline became a controlled Packer lifecycle for CPU and GPU Azure DevOps runner pools.
Azure DevOps · Azure VMSS · Azure Compute Gallery · Packer / completedHow Kubernetes delivery moved from pipeline control to Argo CD through explicit, workload-by-workload handoffs.
Argo CD · ApplicationSet · Kubernetes · Helmplatform / completedA governed Azure delivery platform for Stellardian’s revamped connected-mobility and fleet workflows.
Azure · Terraform · Azure Kubernetes Service (AKS) · Azure Monitorplatform / completedTerraform-managed Azure environments and governed AKS delivery for KIRRK’s connected rental and fleet platform.
Azure · Terraform · Azure Kubernetes Service (AKS) · Azure Monitor / completedHow identity-driven provisioning and scheduled lifecycle controls turned varied cloud workstations into a managed platform capability.
GCP · Pulumi · Microsoft Entra ID · Google OS Loginplatform / completedTerraform and Kubernetes delivery automation reduced tenant and environment setup from days to minutes.
Azure · Terraform · Azure Kubernetes Service (AKS) · Azure Monitor / completedHow generated ComputeClasses matched workload constraints to GPU and provisioning fallbacks instead of waiting on one capacity source.
GKE · Kubernetes · GPU · ComputeClass / completedHow a pull-request label triggered an isolated Kubernetes application environment for focused review and testing.
Azure Pipelines · Kubernetes · Helm · Preview EnvironmentsTools shown in context: each area pairs the work with the platforms behind it.
Cloud landing zones, hub networking, and workload dependencies kept local to each provider.
Build landing zones, hub networking, and shared services for Azure workloads.
Run GKE and GPU workloads while keeping their runtime dependencies cloud-local.
Extend the platform with isolated AWS accounts, services, and Kubernetes capacity.
Consistent AKS, GKE, and EKS operations through GitOps, reusable charts, progressive delivery, and admission policy.
Run application and platform workloads on Azure Kubernetes Service.
Run platform management and GPU workloads on Google Kubernetes Engine.
Extend multi-cluster operations to Amazon Elastic Kubernetes Service.
Package and version Kubernetes applications as reusable charts.
Declare and coordinate releases across multiple Helm charts.
Maintain environment-specific Kubernetes overlays without copying manifests.
Continuously reconcile cluster state from Git repositories.
Deliver changes with canary and blue-green rollout strategies.
Manage service-to-service traffic, security, and telemetry with a service mesh.
Route external traffic into Kubernetes services through ingress and gateway configuration.
Enforce policy-as-code at Kubernetes admission boundaries.
Cloud infrastructure defined through repeatable Pulumi and Terraform programs; shared services packaged as reusable resources.
Provision cloud platforms with reusable, versioned infrastructure programs.
Define and manage repeatable cloud infrastructure from declarative plans.
Expose cloud infrastructure as Kubernetes-managed platform resources.
Reusable delivery pipelines, CPU/GPU runner images, and pull-request preview environments.
Build reusable pipelines and self-hosted CPU/GPU runner pools.
Automate build, validation, and release workflows across repositories.
Run repository-native build, test, and deployment pipelines.
Connect GCP source, build, and deployment steps for cloud workloads.
Coordinate source, build, and deploy stages in AWS delivery workflows.
Run managed build and test jobs as part of AWS delivery workflows.
Automate application rollout steps to AWS compute targets.
Metrics, logs, traces, and profiles brought into one investigation workflow alongside cloud-native monitoring.
Correlate dashboards for metrics, logs, traces, and profiles across clusters.
Collect and query platform and workload metrics for alerting and capacity analysis.
Aggregate and query Kubernetes logs alongside Grafana metrics and traces.
Store and explore distributed traces across services and clusters.
Profile continuous CPU and memory usage to find application hot spots.
Monitor application performance and service health with APM telemetry.
Use Elasticsearch, Logstash, and Kibana alongside metrics and tracing for log investigations.
Inspect distributed traces to follow requests across service boundaries.
Inspect AWS service health, logs, and operational signals.
Track Azure resource health, metrics, and alerts.
Trace application behavior and diagnose service issues with Azure telemetry.
SSO and workload identity integrated with cluster services; Vault-backed secrets synchronized without storing values in Git.
Provide centralized secret storage and Kubernetes workload authentication.
Sync secrets from external stores into Kubernetes without committing values to Git.
Integrate workforce sign-on and workload identity with cloud services.
Connect workforce identity and single sign-on to application access.
Add managed authentication and authorization to application services.
Operate self-hosted identity, SSO, and federation for platform applications.
Managed databases, local caches, and retrieval stores selected to fit workload needs and runtime boundaries.
Run relational workloads with dependable transactions and query flexibility.
Use managed PostgreSQL-compatible services for cloud-hosted data workloads.
Run managed relational databases close to AWS-hosted services.
Use managed SQL databases integrated with Azure application platforms.
Support globally distributed applications with managed document data.
Run managed document databases for flexible application data.
Keep frequently accessed data close to services with an in-memory cache.
Cache hot application data to reduce repeated backend reads.
Index embeddings for semantic search and retrieval workflows.
Explore document and graph relationships for connected-data applications.
Retrieval and multi-step LLM workflows composed, traced, and evaluated.
Compose retrieval and model calls into reusable LLM application flows.
Represent multi-step, stateful agent workflows as explicit graphs.
Trace runs and evaluate LLM workflow behavior.
Go, Python, TypeScript, and C# for platform CLIs, controllers, infrastructure code, and backend services.
Build platform CLIs, services, and automation tooling.
Automate infrastructure workflows and build backend and data tools.
Develop web interfaces, APIs, and infrastructure automation.
Build backend services and internal platform applications.
Built Azure landing zones from existing subscriptions and an unreliable Pulumi prototype, then expanded the platform across GCP, AWS, and on-prem infrastructure for Kubernetes and GPU-backed compute.
Built a repeatable Azure delivery foundation across Qomben, KIRRK, and Stellardian: Terraform-managed environments, governed AKS, and secure CI/CD. KIRRK and its Stellardian evolution added connected-device and event-processing workloads.
Built the application services behind RedFabriQ client products, then carried software-engineering practices into the platform work that followed.
Delivered end-to-end application work for freelance clients, spanning Windows desktop software, backend APIs, and deployment automation.
Started in product engineering, building shared mobile experiences across iOS, Android, and Windows Phone with Apache Cordova and Ionic.
Let’s talk about infrastructure, delivery systems, and developer experience.
helpList available commands (help, man)aboutRead profile and engineering focus (about, bio)profileShow profile, focus, and delivery loop (profile, neofetch, fetch)skillsBrowse technology areas, logos, and details (skills)experienceView career history and role summaries (experience, jobs)projectsExplore published case studies (projects, work, collabs)githubOpen GitHub profile (github, gh)linksOpen contact and profile links (links, contact)theme [name]Switch terminal palette (dracula | green | amber | cyan | mono | cappuccino)lsList portfolio sections (ls)gui / cliSwitch dashboard or terminal viewclearClear terminal transcript (clear, cls)I build cloud platforms, delivery systems, and developer tooling that help engineers and data teams ship reliable software and compute workloads across Azure, GCP, and AWS.
Platform engineer with a software engineering background. I work across the full infrastructure lifecycle, including architecture, automation, delivery, observability, security, and operations, with a focus on multi-cloud Kubernetes platforms and developer enablement.
Cloud landing zones, hub networking, and workload dependencies kept local to each provider.
Build landing zones, hub networking, and shared services for Azure workloads.
Run GKE and GPU workloads while keeping their runtime dependencies cloud-local.
Extend the platform with isolated AWS accounts, services, and Kubernetes capacity.
Consistent AKS, GKE, and EKS operations through GitOps, reusable charts, progressive delivery, and admission policy.
Run application and platform workloads on Azure Kubernetes Service.
Run platform management and GPU workloads on Google Kubernetes Engine.
Extend multi-cluster operations to Amazon Elastic Kubernetes Service.
Package and version Kubernetes applications as reusable charts.
Declare and coordinate releases across multiple Helm charts.
Maintain environment-specific Kubernetes overlays without copying manifests.
Continuously reconcile cluster state from Git repositories.
Deliver changes with canary and blue-green rollout strategies.
Manage service-to-service traffic, security, and telemetry with a service mesh.
Route external traffic into Kubernetes services through ingress and gateway configuration.
Enforce policy-as-code at Kubernetes admission boundaries.
Cloud infrastructure defined through repeatable Pulumi and Terraform programs; shared services packaged as reusable resources.
Provision cloud platforms with reusable, versioned infrastructure programs.
Define and manage repeatable cloud infrastructure from declarative plans.
Expose cloud infrastructure as Kubernetes-managed platform resources.
Reusable delivery pipelines, CPU/GPU runner images, and pull-request preview environments.
Build reusable pipelines and self-hosted CPU/GPU runner pools.
Automate build, validation, and release workflows across repositories.
Run repository-native build, test, and deployment pipelines.
Connect GCP source, build, and deployment steps for cloud workloads.
Coordinate source, build, and deploy stages in AWS delivery workflows.
Run managed build and test jobs as part of AWS delivery workflows.
Automate application rollout steps to AWS compute targets.
Metrics, logs, traces, and profiles brought into one investigation workflow alongside cloud-native monitoring.
Correlate dashboards for metrics, logs, traces, and profiles across clusters.
Collect and query platform and workload metrics for alerting and capacity analysis.
Aggregate and query Kubernetes logs alongside Grafana metrics and traces.
Store and explore distributed traces across services and clusters.
Profile continuous CPU and memory usage to find application hot spots.
Monitor application performance and service health with APM telemetry.
Use Elasticsearch, Logstash, and Kibana alongside metrics and tracing for log investigations.
Inspect distributed traces to follow requests across service boundaries.
Inspect AWS service health, logs, and operational signals.
Track Azure resource health, metrics, and alerts.
Trace application behavior and diagnose service issues with Azure telemetry.
SSO and workload identity integrated with cluster services; Vault-backed secrets synchronized without storing values in Git.
Provide centralized secret storage and Kubernetes workload authentication.
Sync secrets from external stores into Kubernetes without committing values to Git.
Integrate workforce sign-on and workload identity with cloud services.
Connect workforce identity and single sign-on to application access.
Add managed authentication and authorization to application services.
Operate self-hosted identity, SSO, and federation for platform applications.
Managed databases, local caches, and retrieval stores selected to fit workload needs and runtime boundaries.
Run relational workloads with dependable transactions and query flexibility.
Use managed PostgreSQL-compatible services for cloud-hosted data workloads.
Run managed relational databases close to AWS-hosted services.
Use managed SQL databases integrated with Azure application platforms.
Support globally distributed applications with managed document data.
Run managed document databases for flexible application data.
Keep frequently accessed data close to services with an in-memory cache.
Cache hot application data to reduce repeated backend reads.
Index embeddings for semantic search and retrieval workflows.
Explore document and graph relationships for connected-data applications.
Retrieval and multi-step LLM workflows composed, traced, and evaluated.
Compose retrieval and model calls into reusable LLM application flows.
Represent multi-step, stateful agent workflows as explicit graphs.
Trace runs and evaluate LLM workflow behavior.
Go, Python, TypeScript, and C# for platform CLIs, controllers, infrastructure code, and backend services.
Build platform CLIs, services, and automation tooling.
Automate infrastructure workflows and build backend and data tools.
Develop web interfaces, APIs, and infrastructure automation.
Build backend services and internal platform applications.
Senior Platform Engineer
Built Azure landing zones from existing subscriptions and an unreliable Pulumi prototype, then expanded the platform across GCP, AWS, and on-prem infrastructure for Kubernetes and GPU-backed compute.
Built a repeatable Azure delivery foundation across Qomben, KIRRK, and Stellardian: Terraform-managed environments, governed AKS, and secure CI/CD. KIRRK and its Stellardian evolution added connected-device and event-processing workloads.
Built the application services behind RedFabriQ client products, then carried software-engineering practices into the platform work that followed.
Delivered end-to-end application work for freelance clients, spanning Windows desktop software, backend APIs, and deployment automation.
Started in product engineering, building shared mobile experiences across iOS, Android, and Windows Phone with Apache Cordova and Ionic.
Azure landing zones rebuilt from an unusable Pulumi prototype, with the first development environment delivered in 10 days before extending the foundation to staging, production, GCP, AWS, and on-prem.
platform / evolvingDelivery standardized across AKS, GKE, and EKS with Argo CD, Helmfile, and Kustomize. Progressive rollouts and Vault-backed secret sync gave teams a consistent release path without committing secrets to Git.
observability / evolvingMetrics, logs, traces, and profiles unified across multi-cloud Kubernetes clusters in Grafana. Prometheus, Loki, Tempo, and Pyroscope support workload investigation, complemented by New Relic infrastructure and cluster instrumentation.
tooling / evolvingDeveloped custom Go CLIs, Kubernetes admission controllers, and image lifecycle controllers to automate operations and enforce policy as code.
/ completedA failed Pulumi prototype rewritten into an Azure development environment delivered in 10 days, followed by staging and production.
/ completedHow a stale image pipeline became a controlled Packer lifecycle for CPU and GPU Azure DevOps runner pools.
/ completedHow Kubernetes delivery moved from pipeline control to Argo CD through explicit, workload-by-workload handoffs.
platform / completedA governed Azure delivery platform for Stellardian’s revamped connected-mobility and fleet workflows.
platform / completedTerraform-managed Azure environments and governed AKS delivery for KIRRK’s connected rental and fleet platform.
/ completedHow identity-driven provisioning and scheduled lifecycle controls turned varied cloud workstations into a managed platform capability.
platform / completedTerraform and Kubernetes delivery automation reduced tenant and environment setup from days to minutes.
/ completedHow generated ComputeClasses matched workload constraints to GPU and provisioning fallbacks instead of waiting on one capacity source.
/ completedHow a pull-request label triggered an isolated Kubernetes application environment for focused review and testing.
Source, tools, and project activity.
GitHubhttps://github.com/obeyda