Cloud platforms, DevSecOps & reliable operations

Challenge: When alerts fire, operational knowledge is scattered across runbooks, RCAs, dashboards, and chat history. AI-assisted triage without citations drifts into weakly grounded recommendations.

Approach: Built HARP to turn alerts and Git-tracked operational knowledge into cited evidence packs. AI clients receive read-only context through MCP, while workflow state and remediation approval remain under human control. Under the hood: BM25 + hybrid search, optional OpenRAG semantic retrieval, synthetic monitoring signal paths, and Nero-Camp for approval state.

Challenge: The homelab’s synthetic log canary and Prometheus metrics path are separate. Extending observability to cloud adds cost, access, and failure boundaries to resolve before deployment; application traces are not collected today.

Approach: Documented the existing synthetic Alloy-to-Loki canary separately from the Prometheus metrics path, then designed an isolated, single-EC2 AWS Compose PoC with private Tailscale operator access and a staged Terraform/Ansible delivery plan. Azure is a reference architecture only; application OpenTelemetry tracing remains future work.

Challenge: Teams want AI-assisted document search without pushing sensitive material into a broad public SaaS workflow.

Approach: Set up a private RAG stack with vector search, reranking, and cited answers on self-hosted infrastructure, while using cloud LLM services selectively.

Challenge: Kubernetes incidents often start with scattered context across logs, alerts, and cluster state, which slows down first-pass diagnosis.

Approach: Built a containerized Python/FastAPI workflow to structure incident context for Kubernetes triage. AWS Bedrock, Lambda, API Gateway, and EKS describe a proposed deployment path, not a production service.

Challenge: Engineering teams need actionable spend insights, not raw billing data — and the infrastructure itself should demonstrate cost awareness.

Approach: Modeled V1 with ECS Fargate + ALB at about $27/month and V2 with EC2 t4g.nano + Caddy at about $6/month. The estimates represent about 78% lower modeled infrastructure cost; both options use the same Lambda + Athena pipeline and GitLab CI lifecycle assumptions.

Challenge: Portfolio systems are hard to evaluate if they only exist as diagrams or code snippets.

Approach: Built a small self-hosted platform with Proxmox, Kubernetes, storage, and internal tooling so projects can be deployed and operated end to end.

Challenge: Browser and operating-system speech voices vary, making pronunciation inconsistent for language learners.

Approach: Built a static-first learning SPA with reviewed lesson data, deterministic audio manifests, Amazon Polly generation, normal/slow MP3s, client-side progress, and accessible playback controls.

Challenge: Developers need repeatable remote workspaces and temporary app/test environments, with clear ownership so stopping a workspace preserves its files and expiring an app environment cannot delete workspace data.

Approach: Deployed a single-user Coder Community control-plane pilot on the existing homelab Kubernetes cluster, with external PostgreSQL and monitoring. A Terraform template defines an unprivileged workspace and persistent home volume, but has not been imported or applied. First-admin setup and workspace launch remain pending; persistence, recovery, and the separate app/test lifecycle are not qualified.