Azure Blob Storage automatically partitions data based on blob name prefixes. Sequential or timestamp-prefixed names can create hot partition servers. This simulator helps you visualize how different naming conventions affect partition distribution and throughput.
Estimated blob count per partition range (based on name-prefix bucketing)
Estimated requests/sec per partition range
| Naming Pattern | Partition Spread | Risk |
|---|---|---|
0001, 0002, ... | Poor — all names share prefix range | High — hot partition |
20260228/data_* | Moderate — grouped by date prefix | Today's range overloaded |
a3f_blobname | Excellent — hash distributes evenly | Low |
9876543210_* (reverse ticks) | Good — shifts hot range constantly | Low |
guid/blobname | Excellent — random distribution | Loses natural grouping |