StackLayer

What it is

StackLayer is a reproducible platform engineering environment for exploring modern Internal Developer Platform, GitOps, observability, and developer experience patterns in a controlled, enterprise-style setting.

Core Question

How can platform teams deliver self-service capabilities that improve developer productivity while maintaining governance, consistency, and operational visibility?

Why I built it

Throughout my career, I have consistently gravitated toward platform engineering and developer enablement. Whether building private cloud platforms, Internal Developer Platforms, automation frameworks, or developer tooling, the common theme has been reducing friction and improving engineering productivity.

Design Goals

• Reproducibility: Every component should be deployable and recoverable through automation rather than manual configuration.
• Self-service: Platform capabilities should reduce operational dependencies and help developers provision and consume services independently.
• GitOps: Infrastructure and platform changes should be managed declaratively through source control and automated reconciliation.
• Observability by default: Metrics, dashboards, and monitoring should be treated as first-class platform capabilities.
• Governance: Platform capabilities should encourage consistency, standards, and operational controls without creating unnecessary friction.
• Developer experience: The platform should simplify common workflows and reduce the cognitive load required to build, deploy, and operate applications.

Architecture

StackLayer follows a layered architecture similar to enterprise platform engineering organizations.

• Infrastructure layer: VMware Workstation, Vagrant, Linux virtual machines, and private networking provide the compute, networking, isolation, and lifecycle foundation.
• Kubernetes layer: kubeadm, a control plane, and worker nodes provide container orchestration, workload scheduling, service management, and cluster operations.
• Platform services layer: MetalLB, NGINX Ingress, persistent storage, and TLS management provide traffic routing, service exposure, storage abstraction, and reliability foundations.
• Delivery layer: GitHub, ArgoCD, and GitOps repositories provide continuous delivery, declarative deployments, environment consistency, and operational automation.
• Observability layer: Prometheus and Grafana provide metrics collection, dashboards, capacity monitoring, and platform health visibility.

Current Capabilities

• Reproducible Kubernetes environments.
• GitOps-driven deployment workflows.
• Platform service validation.
• Observability and monitoring.
• Infrastructure automation.
• Platform experimentation and testing.

The environment enables realistic testing of platform patterns commonly found in enterprise engineering organizations.

Roadmap

• Internal Developer Platform: Backstage, service catalogs, golden paths, and developer portals.
• AI platform services: Ollama, local LLM hosting, AI governance, and AI-assisted development workflows.
• Platform governance: Policy-as-code, compliance validation, and standardized platform controls.
• Developer productivity: Self-service provisioning, developer onboarding workflows, platform templates, and platform scorecards.

Key Learnings

• Platform engineering is about abstraction: The value of a platform is not the infrastructure itself. The value comes from simplifying complexity for platform consumers.
• GitOps improves consistency: GitOps improves reproducibility and operational consistency, but requires careful repository and workflow design.
• Observability must be built in: Operational visibility is more effective when treated as a platform capability rather than an afterthought.
• Developer experience matters: Technically sound platforms still struggle with adoption when workflows are difficult to understand or use.
• Governance and self-service must coexist: Successful platforms provide autonomy while still enforcing organizational standards and controls.

Why it matters