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VM Trace

The trace contains a representative subset of the first-party Azure VM workload in one geographical region.
This jupyter notebook directly compares the main characteristics of the this trace and the a complete Azure workload in 2019, showing that they are qualitatively very similar (except for VM deployment sizes).

The main trace characteristics and schema are:

Main characteristics:

  • Dataset size: 235GB
  • Compressed dataset size: 156GB
  • Number of files: 198 files
  • Duration: 30 consecutive days
  • Total number of VMs: 2,695,548
  • Total number of Azure subscriptions: 6,687
  • Timeseries data: 5-minute VM CPU utilization readings, VM information table and subscription table (with main fields encrypted)
  • Total VM hours: 104,371,713
  • Total number of VM CPU utilization readings: 1,942,780,023
  • Total virtual core hours: >380,000,000


  1. Encrypted subscription id
  2. Encrypted deployment id
  3. Timestamp in seconds (starting from 0) when first VM created
  4. Count VMs created
  5. Deployment size (we define a “deployment” differently than Azure in our paper)
  6. Encrypted VM id
  7. Timestamp VM created
  8. Timestamp VM deleted
  9. Max CPU utilization
  10. Avg CPU utilization
  11. P95 of Max CPU utilization
  12. VM category
  13. VM virtual core count bucket
  14. VM memory (GBs) bucket
  15. Timestamp in seconds (every 5 minutes)
  16. Min CPU utilization during the 5 minutes
  17. Max CPU utilization during the 5 minutes
  18. Avg CPU utilization during the 5 minutes
  19. VM virtual core count bucket definition
  20. VM memory (GBs) bucket definition

Downloading instructions

You can download the dataset from Azure Blob Storage using the links available here.