Splunk® Supported Add-ons

Splunk Add-on for Microsoft Cloud Services

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Performance reference for the Azure Storage Blob input in the Splunk Add-on for Microsoft Cloud Services

The following tables show reference information about performance testing of the Azure Storage Blob input in the Splunk Add-on for Microsoft Cloud Services. Use this information to enhance the performance of your own Azure Storage Blob data collection tasks.

Many factors impact performance results, including file size, file compression, event size, deployment architecture, and hardware. These results represent reference information and do not represent performance in all environments.

Version 5.2.1 and above Blob input performance characteristics

Common architecture setup Scenario Blob type File size Ingest rate IDM CPU

CO2 Stack - Victoria Search Head Cluster

  • 1 cluster master (c5.xlarge)
  • 3 search head (m6i.4xlarge)
    • 16 CPU
    • 64 GiB Memory
  • 3 indexer cluster (im4gn.4xlarge)
    • 16 CPU
    • 64 GiB Memory
  • Default TA configs
1 input AppendBlob 1MB 16324 kb/s 10.95%
5 inputs AppendBlob 1MB 39814 kb/s 27.69%
1 input BlockBlob 1MB 24364 kb/s 9.42%
5 inputs BlockBlob 1MB 40810 kb/s 16.34%

CO2 Stack - Classic Cluster (1 IDM)

  • 1 cluster master (c5.xlarge)
  • 3 search head (m6i.4xlarge)
    • 16 CPU
    • 64 GiB Memory
  • 3 indexer cluster (im4gn.4xlarge)
    • 16 CPU
    • 64 GiB Memory
  • 1 Inputs Data Manager (IDM) (m6i.4xlarge)
    • 16 CPU
    • 64 GiB Memory
  • Default TA configs
1 input AppendBlob 1MB 8717 kb/s 8.44%
5 inputs AppendBlob 1MB 39815 kb/s 28.41%
1 input BlockBlob 1MB 11577 kb/s 6.4%
5 inputs BlockBlob 1MB 41857 kb/s 28%

Version 5.1.2 and above Blob input performance characteristics

Common architecture setup Scenario Blob type File size Ingest rate IDM CPU

CO2 Stack - Victoria Search Head Cluster

  • 1 cluster master (c5.xlarge)
  • 3 search head (m6i.4xlarge)
    • 16 CPU
    • 64 GiB Memory
  • 3 indexer cluster (im4gn.4xlarge)
    • 16 CPU
    • 64 GiB Memory
  • Default TA configs
1 input AppendBlob 1MB 8277 kb/s 25.34%
5 inputs AppendBlob 1MB 37963 kb/s 28.09%
1 input BlockBlob 1MB 11532 kb/s 18.45%
5 inputs BlockBlob 1MB 40810 kb/s 29.82%

CO2 Stack - Classic Cluster (1 IDM)

  • 1 cluster master (c5.xlarge)
  • 3 search head (m6i.4xlarge)
    • 16 CPU
    • 64 GiB Memory
  • 3 indexer cluster (im4gn.4xlarge)
    • 16 CPU
    • 64 GiB Memory
  • 1 Inputs Data Manager (IDM) (m6i.4xlarge)
    • 16 CPU
    • 64 GiB Memory
  • Default TA configs
1 input AppendBlob 1MB 7405 kb/s 9.45%
5 inputs AppendBlob 1MB 39815 kb/s 28.64%
1 input BlockBlob 1MB 20030 kb/s 10.12%
5 inputs BlockBlob 1MB 40810 kb/s 29.09%


Version 5.0.0 and above Blob input performance characteristics

Common architecture setup Scenario Blob type File size Ingest rate IDM CPU

CO2 Stack - Victoria Search Head Cluster

  • 1 cluster master (c5.xlarge)
  • 3 search head (m6i.4xlarge)
    • 16 CPU
    • 64 GiB Memory
  • 3 indexer cluster (is4gen.4xlarge)
    • 16 CPU
    • 96 GiB Memory
  • Default TA configs
1 input AppendBlob 1MB 8155.26 kb/s N/A
5 inputs AppendBlob 1MB 21390.76 kb/s N/A
1 input BlockBlob 1MB 13100.21 kb/s N/A
5 inputs BlockBlob 1MB 24328.95 kb/s N/A

CO2 Stack - Classic Cluster (1 IDM)

  • 1 cluster master (c5.xlarge)
  • 3 search head (m6i.4xlarge)
    • 16 CPU
    • 64 GiB Memory
  • 3 indexer cluster (is4gen.4xlarge)
    • 16 CPU
    • 96 GiB Memory
  • 1 Inputs Data Manager (IDM) (m6i.4xlarge)
    • 16 CPU
    • 64 GiB Memory
  • Default TA configs
1 input AppendBlob 1MB 6850.66 kb/s 55.85%
5 inputs AppendBlob 1MB 8049.20 kb/s 33.35%
1 input BlockBlob 1MB 3808.87 kb/s 44.55%
5 inputs BlockBlob 1MB 3838.31 kb/s 32.00%
Continuous append scenario
Append 6 files sequentially to 1GB.
  • A single user creates an append blob.
  • Append 1MB each time in each file.
  • Pause up to 1 second after each append.
  • Append 1024 times to get to 1GB for the file.
  • In total, append 6 files to 1GB in parallel.
  • Total event size matches the original file size in Azure.

Version 4.1.4 Blob input performance characteristics

Block blob

Common architecture setup Blob type File size Ingest rate Events per minute Data lag IDM CPU Cores % (Percentage of total IDM cores)

Scaled up stack

  • 20 containers
  • 20 add-on inputs
  • 1 cluster master (c5.xlarge)
  • 1 search head (c5.2xlarge)
  • 3 indexer cluster (i3.large)
    • 32 CPU cores
    • 244 GB memory
  • 1 input data manager (c5.9xlarge)
    • 32 CPU cores
    • 72 GB memory
  • 20 Splunk Add-on for Microsoft Cloud Services inputs
  • 120 seconds collection interval
block blob 10kb 48GB/day 3522 ~120 seconds 1.8%
1MB 50GB/day 36 ~121 seconds 1.84%


Append blob

Common architecture setup Blob type File size Ingest rate Events per minute Data lag IDM CPU Cores % (Percentage of total IDM cores)
Scaled up stack
  • 20 containers
  • 20 add-on inputs
  • 1 cluster master (c5.xlarge)
  • 1 search head (c5.2xlarge)
  • 3 indexer cluster (i3.large)
    • 32 CPU cores
    • 244 GB memory
  • 1 input data manager (c5.9xlarge)
    • 32 CPU cores
    • 72 GB memory
  • 20 Splunk Add-on for Microsoft Cloud Services inputs
  • 120 seconds collection interval
append blob 1 kb 33GB/day 21522 ~120 seconds 3.7%
10 kb 281GB/day 20496 ~121 seconds 2.67%
100 kb 2.69TB/day 18402 ~129 seconds 6.5%


Additional Blob input scenarios

Scenario Workflow Result
Append file up to 4GB
  • A single user creates an append blob.
  • Append 100 kb each time.
  • Append 40000 times.
  • Pause up to 100 ms in each append.
  • All 40000 append blocks pulled back.
  • Total event size matches original file size in Azure.
  • Minimal to no data lag.
  • Collection interval is 12 seconds.
Append 3 files sequentially to 100 MB
  • A single user creates an append blob.
  • 100000 append each time.
  • Pause up to 100 ms after each append.
  • Append 1000 times to get to 100 MB for the file.
  • Move on to the next file and repeat.
  • In total, append 3 files to 100 MB sequentially.
  • All 3000 append blocks pulled back.
  • Total event size matches original file size in Azure.
Last modified on 05 February, 2024
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This documentation applies to the following versions of Splunk® Supported Add-ons: released


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