Chris
Wisecarver
Data engineer. Database whisperer. Owner of more lenses than sense, and a man who genuinely paid $999 for a monitor stand.
The Chris, in numbers
Independently verified by absolutely no one. Subject to change the moment a new Apple accessory drops.
- Primary language
- SQL, then regret
- Coffee per incident
- 2.4 cups
- Polishing cloths owned
- 1 (cherished)
- Avg. pipeline uptime
- Aspirational
- Apple devices
- All of them
- Time to over-engineer
- < 4 minutes
- Production incidents (cause)
- “It worked locally”
- Battery health
- Worse than the M-series
Pipeline status: Degraded
A real-time look at Chris's data platform. It has been like this for a while. It will be like this for a while longer.
nightly_sync
customer_events_etl
warehouse_backfill
legacy_cron_job
the_one_dashboard_that_works
Indexing a 10-row table
A case study in scaling for the future. The table has ten rows. It has had ten rows since 2019. Chris added an index. Then a composite index. Then a partial index, just in case.
db=# SELECT count(*) FROM users;
count
-------
10
db=# CREATE INDEX CONCURRENTLY idx_users_supercharged
ON users (id, email, created_at, last_seen)
INCLUDE (avatar_url);
CREATE INDEX
db=# EXPLAIN ANALYZE SELECT * FROM users;
Seq Scan on users (index ignored)
Planning Time: 0.041 ms
Execution Time: 0.018 ms
-- worth it. definitely worth it.Read performance
Improved by an unmeasurable amount, because the planner does a sequential scan anyway. Ten rows. It's ten rows.
Write performance
Four indexes to update on every insert. The table gets one insert per quarter. Robustly future-proofed.
Peace of mind
Immense. Chris sleeps soundly knowing the table is ready to scale to its inevitable eleventh row.
More lenses than sense
A curated selection from Chris's collection. The $19 cloth and the $5,000 lens get equal reverence. Add things to the cart. You won't buy them. Neither should he have.
Polishing Cloth
Monitor Stand (no monitor)
600mm f/4 Telephoto
Tower Wheels
Carbon Tripod, Mk IV
8TB of RAW Photos
What he actually does all day
A balanced portfolio of genuine talent and expensive distractions.
Data engineering
Builds elegant pipelines, then spends the rest of his life keeping them upright. The pipelines are the job. The job is the pipelines.
Databases
Normalizes to 6th normal form, indexes everything that moves, and can recite query plans like bedtime stories. Knows your data better than you do.
Software development
Ships clean code, then refactors it three more times because the abstraction could be slightly more abstract.
Apple devotion
Owns the ecosystem. The whole ecosystem. Has opinions about the matte nano-texture display and is not afraid to share them.
Photography
Phenomenal taste in glass, questionable follow-through on editing. The hard drive of unprocessed RAWs is its own form of art.
Incident response
Calm under pressure at 3 AM, mostly because he has been there so many times it now feels like home.
On the record
Affectionate, accurate, and entirely deserved. Press the button for another.
His tech stack has more moving parts than a Swiss watch and roughly the reliability of a chocolate teapot.
Page him during an incident
He's almost certainly awake. The pipeline is almost certainly degraded. These two facts are related.
Need a pipeline diagnosed or a lens recommended? Same enthusiasm, either way.
Best reached after midnight. Worst reached before coffee.