Distributed systems
Designing replicated event pipelines, recovery paths, and high-throughput services where correctness is part of the architecture.
I’m Thomas Cabral—an engineer and lifelong technologist working from product interface to distributed infrastructure. I turn opaque, underperforming systems into observable foundations that teams can build on.
What I bring
I work across the layers that make technology useful—from architecture and implementation to operations and technical direction.
Designing replicated event pipelines, recovery paths, and high-throughput services where correctness is part of the architecture.
Building analytical systems that stay interactive across enormous datasets by putting the right work in the right layer.
Owning what happens after the build: declarative infrastructure, GitOps delivery, observability, and pragmatic cloud operations.
Connecting deep backend work to interfaces people can actually understand, trust, and use—from zero to production.
What I’m building
Spillgate is the usage platform at the surface. Brod is the event backbone powering its pipeline—useful product infrastructure above, serious data and reliability work underneath.
Usage infrastructure
A developer-first platform for metering every event, enforcing customer quotas in real time, and turning consumption into transparent usage billing—powered by Brod underneath.
Explore SpillgateDistributed systems
The event backbone powering Spillgate: a high-throughput replicated log built around parallel ingestion, selective replay, predictable recovery, and analytical workloads.
Applied intelligence
Investigating how notes, signals, schedules, relationships, and bounded AI synthesis can become durable working context.
Open source / Spatial data
An open-source exploration of interactive spatial aggregation across billion-scale point sets, combining in-memory speed with columnar scale.
View on GitHubFrom the field
Notes on architecture, language design, AI tooling, and the judgment it takes to build software that lasts.
There's a version of this story where AI coding tools are the great equalizer — where anyone with a good idea can build production software regardless of experience. That story is being told constantly right now, and it's mostly wrong. The uncomfortable truth is that these tools are amplifiers. They take what you already know and make you faster a…
I have written production code in Kotlin, Typescript/Javascript, Java, Scala, Python, Go, C# and more. I have built metering systems in C# and Go and am constantly reminded of why I always pick up Go every time when given the choice. After years of working across these ecosystems, I keep coming back to the same conclusion: Go is the best language …
A recent conversation with a colleague highlighted a fundamental disconnect in how we discuss and market artificial intelligence capabilities. When exploring how large language models (LLMs) actually function, they expressed frustration with the gap between marketing promises and technical reality—drawing a pointed comparison to Tesla's self-drivin…
Experience.log
Product & systems engineering
Platform architecture & distributed systems
Software & product engineering
Technical range
Not a wall of badges—a working toolkit chosen according to the shape of the problem.
Start a conversation
I’m always interested in ambitious products, sharp technical challenges, and meeting people who care about the craft.
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