Deep dives into specific technical problems — what broke, how I diagnosed it, and what changed.
Pages that used to take 3 seconds to load now respond almost instantly.
108× faster on list queries, up to 666× faster on single-record lookups, no hardware changes.
8.8M rows
Dataset
666×
Best speedup
99.85%
Latency reduction
A batch job that used to run over 3 minutes, or crash outright, now finishes in 20 seconds.
1M records processed in 20s using batched inserts and concurrency, down from 3m19s or an out-of-memory crash.
1M rows
Dataset
20s
Best time
3m 19s
Worst (completed)
An import that blocked the operations team for 40 minutes, with no feedback on success or failure, now finishes in about a minute.
97% faster (40 min → ~1 min) after fixing N+1 queries and switching to bulk inserts.
40 min
Before
~1 min
After
97% faster
Improvement
A face-lookup feature shipped as a working API in under a second per request, without the scale infrastructure it didn't need yet.
3 endpoints, ~737ms–1.8s latency across 20K+ facial records on CPU-only inference.
20K+
Facial records
737 ms
Fastest endpoint
FaceNet512
Model