Operations software portfolio

Field data, made useful.

I design practical software for operational teams: tools that turn changing live data into clear, reliable decisions.

Explore selected work View Frac Plotter case study

LIVE OPERATIONS FLOW

Field sourceCSV / TCP / readings

Reliable ingestionValidate / retry / normalize

Operations viewMonitor / report / act

Built for incomplete files, changing schemas, and real field workflows.

Operational dashboardsLive data reliabilityPython toolingCloud workflows

Selected work

Built for the way field teams actually work.

These projects show an operations-first approach across monitoring, reliability, cloud workflows, and usable reporting.

01Centralized operations dashboard

Beckmann Frac Plotter

A local-first command center that brings live treatment, chemical, wellbore, and reporting context together for frac operations.

Technical focus

Live CSV monitoringTime-series viewsAlarms & reportsCloudflare

Designed to keep working when field files are incomplete, temporarily locked, reordered, or still being written.

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02Python telemetry test tool

Beckmann Data Simulator

A desktop Python application that replays recorded frac data as real-time CSV and captures or parses TCP records for repeatable testing.

Technical focus

PythonTCP streamsReplay testingData quality

Makes live-data behavior reproducible without waiting for a field event.

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03Field operations platform

FieldOps

A mobile-ready workspace paired with a React operations dashboard and secured REST API for controlled site visibility.

Technical focus

PWAReact dashboardREST API.NET 8 APIFirebase

Connects dependable field entry with governed operational data for administrators and integrations.

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How I work

Software that respects the reality of operations.

Field data is often late, incomplete, or changing. Good operational software does not hide that complexity from users - it handles it safely and makes the next decision easier.

Operational UX

Tools shaped around actual treatment, inventory, and handoff work.

Resilient ingestion

Retries, complete-record handling, schema stability, and last-known-good data.

Cloud workflows

Secure access, audit trails, deployment discipline, and scoped data models.

Systems thinking

A clear path from field data to reporting, troubleshooting, and decisions.

Reliability story

When a live reader reported a schema change, I separated the real data issue from the concurrent-read race.

The resulting reader reacquires files before each read, retries transient errors, accepts only complete records, and preserves the last known-good view while it safely tries again.

Reliable datainstead of false alarms