Azure Storage Mover scale and performance targets
The performance of a storage migration service is a key aspect for any migration. In this article, we share performance test results, though because Azure Storage Mover is a new service, your experience may vary.
Scale targets
Azure Storage Mover is tested with 100 million namespace items (files and folders), migrated from a supported source to a supported target in Azure.
How we test
Azure Storage Mover is a hybrid cloud service. Hybrid services have a cloud service component and an infrastructure component the administrator of the service runs in their corporate environment. For Storage Mover, that hybrid component is a migration agent. Agents are virtual machines, ran on a host near the source storage.
Only the agent is a relevant part of the service for performance testing. To omit privacy and performance concerns, data travels directly from the Storage Mover agent to the target storage in Azure. Only control and telemetry messages are sent to the cloud service.
Performance baselines
These test results are created under ideal conditions. They're meant as a baseline of the components the Storage Mover service and agent can directly influence. Differences in source devices, disks, and network connections aren't considered in this test. Real-world performance varies.
Migration from SMB mount to Azure file share tests were executed as follows:
The following table describes the characteristics of the test environments that produced the performance test results from an SMB mount to an Azure file share.
| Test No. | No. of files | Total files weight | File size | Folder structure |
|---|---|---|---|---|
| 1 | 12 million | 12 GB | 1 KB each | 12 folders, each with 100 sub-folders containing 10,000 files |
| 2 | 30 | 20 GB | 1 folder | |
| 3 | 1 million | 100 GB | 100 KB each | 1,000 folders, each with 1,000 files |
| 4 | 1 | 4 TB | ||
| 5 | 117 million | 117 GB | 1 KB each | 117 folders, each with 100 sub-folders containing 10,000 files |
| 6 | 1 | 1 TB | ||
| 7 | 3.3 million | 45 GB | 13 KB each | 200,000 folders, each contains 16\17 files |
| 8 | 50 million | 1 TB | 20 KB each | 2,940,000 folders, each contains 17 files |
| 9 | 100 million | 2 TB | 20 KB each | 5,880,000 folders, each contains 17 files |
Different agent resource configurations are tested on SMB endpoints:
Minspec: 4 CPU / 8 GB RAM 4 virtual CPU cores at 2.7 GHz each and 8 GiB of memory (RAM) is the minimum specification for an Azure Storage Mover agent.
Test No. Execution time Scanning time 6 16 min, 42 sec 1.2 sec 7 55 min, 4 sec 1 min, 17 sec 8 9 Bootspec: 8 CPU / 16 GiB RAM 8 virtual CPU cores at 2.7 GHz each and 16 GiB of memory (RAM) is the minimum specification for an Azure Storage Mover agent.
Results: Standard storage account
Test No. Execution time Scanning time 1 15 hr, 59 min 2 hr, 36 min, 34 sec 2 1 min, 54 sec 3.34 sec 3 1 hr, 19 min, 27 sec 57.62 sec 4 1 hr, 5 min, 57 sec 2.89 sec Results: Standard storage account with large files enabled
Test No. Execution time Scanning time 1 3 hr, 51 min, 31 sec 41 min and 45 sec 5 25 hr, 47 min 23 hr, 35 min 6 11 min, 11 sec 0.7 sec 7 55 min, 10 sec 1 min, 3 sec 8 9 Results: Premium storage account
Test No. Execution time Scanning time 1 2 hr, 35 min, 14 sec 24 min, 46 sec 5 23 hr, 34 min 21 hr, 34 min
Review recommended agent resources for your migration scope in the agent deployment article.
Why migration performance varies
Fundamentally, network quality and the ability to process files, folders and their metadata impact your migration velocity.
Across the two core areas of network and compute, several aspects have an impact:
- Migration scenario
Copying into an empty target is faster as compared to a target with content. This behavior is due the migration engine evaluating not only the source, but also the target to make copy decisions. - Namespace item count
Migrating 1 GiB of small files takes more time than migrating 1 GiB of larger files. - Namespace shape
A wide folder hierarchy lends itself to more parallel processing than a narrow or deep directory structure. The file to folder ratio also plays a roll. - Namespace churn
How many files, folders, and metadata have changed between two copy runs from the same source to the same target. - Network
- bandwidth and latency between source and migration agent
- bandwidth and latency between migration agent and the target in Azure
- Migration agent resources
The amount of memory (RAM), number of compute cores, and even the amount of available, local disk capacity on the migration agent can have a profound impact on the migration velocity. More compute resources help to optimize the utilization of the available bandwidth, especially when large amounts of smaller files need to be processed in a migration.
For example, a traditional migration requires a strategy to minimize downtime of the workload that depends on the storage that is to be migrated. Azure Storage Mover supports such a strategy. It's called convergent, n-pass migration.
In this strategy, you copy from source to target several times. During these copy iterations, the source remains available for read and write to the workload. Just before the final copy iteration, you take the source offline. It's expected that the final copy finishes faster than say the first copy you've ever made and takes about as long as the one immediately preceding it. After the final copy, the workload is failed over to use the new target storage in Azure and available for use again.
During the first copy from source to target, the target is likely empty and all the source content must travel to the target. As a result, the first copy is likely most constrained by the available network resources.
Towards the end of a migration, when you've copied the source to the target several times already, only a few files, folders, and metadata has changed since the last copy. In this last copy iteration, comparing each file in source and target to see if it needs to be updated, requires more compute resources and fewer network resources. Copy runs in this late stage of a migration are often more compute-constrained. Proper resourcing of the Storage Mover agent becomes increasingly important.
Next steps
The following articles can help with a successful Azure Storage Mover deployment.
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