Software Engineering
These are real projects I have written, with working examples locally tested on LocalStack, Postgres and Minikube.
Software Engineering
Software engineering examples deployed and running in kubernetes.
Hyperliquid Markets Crawler
I crawl the live Hyperliquid markets into Postgres. It keeps the latest state with idempotent upserts and a snapshot history that only ever grows. 20 tests, one of which hits the real API.
Infrastructure and Observability
These are the 12 tools I actually reach for to build and run trading infrastructure. They come from real production work, not a wishlist. Where a tool has a tested example you will find it on the card, along with how deep I go.
Cloud and Compute
Where trading systems run, and how they scale while the market is live.
AWS
My main cloud across every role. Networking, IAM, and keeping the bill sane for trading infrastructure.
Kubernetes
Runs the trading and venture builder workloads. I ran EKS in production while trades were live.
Amazon EKS
I designed the EKS and Fargate setup across a whole venture builder portfolio.
AWS Fargate
Serverless containers. It took node management off my plate on the EKS platform.
Infrastructure as Code
Infrastructure I can reproduce and review. Nothing is held up by hand.
Terraform
How I describe and version cloud infrastructure. I have used it to provision real production infra.
CI/CD and Automation
A solid lifecycle so changes ship safely and often.
CI/CD Pipelines
I automate the whole path from commit to production. Here, GitHub Actions runs every example test suite on each push.
Feature branch environments
A throwaway environment for every branch, so every change can be reviewed on its own.
Observability
Monitoring as code, because you cannot run what you cannot see.
OpenTelemetry
Traces, metrics, and logs I own across the services, portable to any backend.
Prometheus
Collects the metrics and drives the alerts for production trading systems.
Grafana
Dashboards for the health of the systems and the trading on top of them.
FinOps and Cost
Reliability and efficiency are the same discipline.
AWS Budgets
Guardrails that keep cloud spend predictable.
Cost Anomaly Detection
I used anomaly analysis to cut cloud cost across a portfolio of projects.