[Opendnssec-user] Unclear SoftHSM behavior.
Spadoni Marco
Marco.Spadoni at italiaonline.it
Tue Jul 17 16:10:36 UTC 2018
Hi all,
we would like to have your help in order to understand the behavior of SoftHSM token described herein.
We developed a multi-threaded, C++ implemented, FastCGI module for Apache embedding an instance of SoftHSM v2.0 token.
The service, named HBM (as per: HSM Broker Module) accept HTTP POST requests (for encryption and decryption), and is executed on a bare-metal DELL server R-710 model, with the following characteristics:
2 CPU 6-core Intel(R) Xeon(R) CPU E5645 @2.40GHz
Hyper-threading enabled
RAM: 96 GB @1333MHz DDR3 (8 GB banks)
6 x 600 GB HDD in RAID 10, HW RAID (total end-user capacity: about 1.5 TBytes)
Operating System: Centos 7.2 - 64 bit
The installed version of the SoftHSM package is:
softhsm.x86_64 2.1.0-2.el7 @base
On another machine with the same characteristics, we sent into execution the Siege benchmarking utility, having populated the Siege input file with half HBM encryption commands, and half decryption ones.
The Siege run lasts five minutes, and is executed at concurrency level set at 16; this is the command through which each Siege run is sent into execution:
/home/kafka/siege/bin/siege -q -f/tmp/siege.in.$$ -l$PWD/h.log -m "$MESSAGE" -b -i -t300S -c16
Each encryption and decryption request is associated to a (AES-256-CBC) key identifier, but, in the test, we always used the same key identifier.
A request to the service is taken in charge by a freshly created thread, to which is associated a private (but non-volatile) cache containing the PKCS#11 handle of the key to be used to satisfy the request. Thus, we do not need to execute the C_FindObject() PKCS#11 routine for each request: after some requests, new threads are likely to find their private cache yet filled by a previously executed thread (which dies after the request is serviced).
We measured the throughput reported by Siege after modifications (keys added to or removed from the SoftHSM token), and we have the following table, where the "HBM reboot" boolean indicates if, before the corresponding run, the HBM service was rebooted or not.
Run ID | Number of keys | HBM reboot | Throughput
1 | 52 | Y | 12951.84
2 | 1 | N | 13456.31
3 | 52 | N | 3566.23
4 | 52 | Y | 12930.80
5 | 26 | N | 6427.34
6 | 38 | N | 4583.19
7 | 52 | N | 3505.33
8 | 52 | Y | 12865.59
9 | 26 | N | 6427.05
10 | 1 | N | 13310.76
As can be seen (going from run 2 to run 3) adding keys to the token without rebooting HBM causes a notable drop in throughput, and the same happens when removing keys (runs 4 to 5 and 8 to 9). However, when only the (unique) used key is left in the token, the throughput rises again.
This happens also when the HBM service is rebooted (runs 3 to 4, and 7 to 8).
We do not understand this behavior, and any hint to interpret it would be much appreciated.
Regards,
Marco Spadoni
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