I build the parts of a system that have to be right, not just fast β workflow engines, async data layers, streaming pipelines, and the compilers and schedulers underneath them.
Durable workflows in YAML, powered by Temporal |
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#568 β Merged Β· An intermittent |
π Listed in zigflow's AUTHORS Β· more on the way β I'm upstreaming a set of engine fixes one at a time.
- βοΈ Workflow orchestration & durable execution β Temporal, compensation, state you can reason about a week later
- π§© Compilers & DSLs β graph traversal, lowering, validation, normalisation; the interesting bits are all edge cases
- β‘ Async Python at the data layer β SQLAlchemy 2.0, connection lifecycle, migration discipline
- π Scheduling correctness β recurrence rules, occurrence generation, timezone-aware scheduling
- π Auth & access control β asymmetric JWT, centralised verification, RBAC that holds at the fifth service
- π₯ Real-time media β RTSP, HLS, WebRTC, and the bandwidth arithmetic behind choosing between them
- π Observability of distributed work β tracing an execution back to the intent that produced it
Languages & Frameworks
Orchestration & Data
Infrastructure
Media & Protocols
- π Deep in workflow orchestration β compilers, durable execution, making failures legible
- πΉ Learning Go properly, mostly by fixing things in a runtime written in it
- π Contributing upstream instead of carrying patches locally
- βοΈ Getting better at the non-code half β design ownership, root-cause analysis, and writing things down
π Python backend & distributed systems Β· βοΈ Workflow orchestration & Temporal Β· π§© Compilers, DSLs and developer tooling Β· π Open source