Engineering Labs
"Turning proofs-of-concept into production-ready architectures."
This is my engineering lab. I use these repositories to build, test, and refine cloud and data patterns before deploying them to client environments. They serve as reference architectures (blueprints) focused on security, scalability, and engineering best practices.
Project Status
These repositories are public baselines containing templates and general standards. Client-specific production code is kept in private repositories.
Cloud & Data Baselines
Reference repositories focused on structure, security, and incremental activation.
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Cloud Infra
Terraform baseline and reference architecture for GCP. Eight modules with per-environment toggles, defense-in-depth testing, Sigstore plan attestation, and OpenSSF Best Practices silver.
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Cloud Data
Data platform baseline defining hybrid warehouse/lakehouse patterns, batch/stream operating modes, and runtime blueprints without exposing personal production pipelines.
Emerging Tech Explorations
Current research spikes and evaluations for potential enterprise adoption:
- Generative AI Agents: Prototyping autonomous workflows with LangChain and Vertex AI.
- Rust for Data: Benchmarking Polars performance against Pandas for local processing tasks.
- LLM Integration: Evaluating open-source models for private NLP workflows.
- Platform Tooling: Building CLI utilities to streamline developer workflows.