Labs
Each lab takes under an hour on a laptop and turns a claim from this mechanism into a number you measured yourself. Prices in the labs are illustrations: use your own vendor's.
- 1
Price a workload from the metering definition, not the rate
Bill one workload three ways — quantity × rate, with a minimum increment, and batched — then compare effective prices.
SimulatePython - 2
Find the small-file crossover on your own bucket
Read 1,000 small objects and one large one from an S3-compatible store: concurrency changes the time, never the request count.
Real systemDocker, Python - 3
Measure the top-1% share of your query log
How much of a warehouse bill the most expensive 1% of queries carry, for cost distributions of different tail weights.
SimulatePython with NumPy - 4
Simulate the spot gang
A job that needs 100 spot nodes at once: its hourly survival, and how checkpointing sets its completion time.
SimulatePython with NumPy - 5
Test the commitment-sizing rule
Find the commitment level that minimises a year of cost under skewed demand, and how a falling price moves it.
SimulatePython with NumPy - 6
Dry-run before you run
Estimate a query's scanned bytes from Parquet metadata four ways: every column, two columns, a partition filter, an uncorrelated filter.
MeasurePython with PyArrow