Long-form notes on software, distributed systems, and the craft of building. Shipping one a week.
6 posts · Engineering
A 0-click query for `dbos ontime` showed up in my Search Console last week. The reader is not asking about DBOS — they are asking how to run a job every minute, exactly once, across a fleet. From my own notes, an etcd lease, the `concurrency.Election` package, and a fencing token cover that case in under 100 lines of Go, without pulling in a workflow engine.
When the log is the source of truth, every schema change is permanent. A Kotlin/Avro walkthrough of the rename that passed the Schema Registry check and silently corrupted every old event, plus the Protobuf and Avro invariants I now keep pinned above my desk.
Notes from two weekends of digging into DSPy. I stopped treating prompts as the source of truth and started treating them as compiled output from a typed signature, a metric, and an optimizer. Here is the smallest end-to-end program I kept, how MIPROv2 actually searches, and where the approach breaks down in practice.
DBOS reuses Postgres as the durability layer for workflows, while Temporal runs a dedicated cluster. The right choice depends on team size, workload shape, and where you want your operational budget to go. This is a practical rubric for picking between them.
The transactional outbox is a ledger, not a queue. Treating it like one is what breaks Postgres under load. This post walks through the specific failure modes — autovacuum stalls, xmin horizon drift, replication slot lag, poison pills — and the operational rules that actually keep it working in production.
JEP 491 removed the `synchronized` pinning problem that kept virtual threads out of production. The interesting question now isn't whether to enable them — it's which bottleneck shows up next. A field guide for Spring Boot / Kotlin services running on JDK 24+.