Perf onnance for Time-Shared Multibatch Virtual Machines
Monitoring Recommendations
First you must determine how many similar users can be run concurrently on a giv
en configuration before the throughput of individual users becomes unacceptable.
Every installation should use the automatic monitoring facilities to simplify and
automate the collection of performance data. A virtual machine should also be set
up to analyze and report the collected data. The VM/370 Performance/Monitor
Analysis Program(VMAP) does such a task. For more information about the
capabilities of this program and for details about ordering it, see the publicationVirtual Machine Facility/370 Performance/Monitor Analysis Program. This pro
gram or user-written analysis programs should be run on a daily basis to analyze
the collected data. Data reduction should preferably be run at off-peak hours to
minimize the effect on the performance of the system that is doing data reduction.
Initially, the data collected withMONITOR default options should be analyzed to
establish a familiarity with the load environment and performance profile of each
virtual machine system and its effect onCPo Once a performance profile is established for each system and associated virtual
machines, the analyst should be able to detect points of contention between
processor(s) storage,I/O, and paging subsystems.
Normally the spool file monitoring options should be used. However, if large vol
umes of trace data are to be collected, then monitoring to tape should be used.
Tape is also useful if benchmarking is frequently done and all of the new monitor
trace and sampled data must be archived for possible future use. The default mode
of operation of the Performance/Monitor AnalysisProgram is to keep the con
densed ACUM files and not the raw data.
If SEEKs data is needed, a sampling technique is suggested. A simple implementa
tion might be to use a CMS EXEC procedure to enable SEEKs for ten seconds
every ten minutes. This would produce SEEKs data while limiting the volume of
data collected. An alternative is to create a list of devices for which data for the
SEEKs class is to be collected.CP collects data for only those devices in the list.
To create the list, use the INCLUDE or EXCLUDE options of theMONITOR command's SEEK operand. If data is collected for only a few devices, consider col
lecting data for longer periods of time.
Load Environments of VM/SP
Two distinct uses ofVM/SP can be readily identified and, consequently some dif
ferences in criteria for acceptable performance may occur. The system may be
required to time share multiple batch-type virtual machines with interactive
machines performing minor support roles; or, the system may be primarily required
to provide good interactive time-sharing services in the foreground, with a batch
background absorbing spare resources of real storage and processor.
After determining the minimum acceptable performance, perform external observa
tions of turnaround time on benchmarks and specify a point beyond which the
addition of more users would be unacceptable. However, when that point is
reached, more sophisticated internal measurement is required to determine the
scarcest resource and how the bottleneck can be relieved by additional hardware.
Several possible conditions can be identified resulting from different bottlenecks.
They are:
Performance Observation and Analysis 59
Monitoring Recommendations
First you must determine how many similar users can be run concurrently on a giv
en configuration before the throughput of individual users becomes unacceptable.
Every installation should use the automatic monitoring facilities to simplify and
automate the collection of performance data. A virtual machine should also be set
up to analyze and report the collected data. The VM/370 Performance/Monitor
Analysis Program
capabilities of this program and for details about ordering it, see the publication
gram or user-written analysis programs should be run on a daily basis to analyze
the collected data. Data reduction should preferably be run at off-peak hours to
minimize the effect on the performance of the system that is doing data reduction.
Initially, the data collected with
establish a familiarity with the load environment and performance profile of each
virtual machine system and its effect on
machines, the analyst should be able to detect points of contention between
processor(s) storage,
Normally the spool file monitoring options should be used. However, if large vol
umes of trace data are to be collected, then monitoring to tape should be used.
Tape is also useful if benchmarking is frequently done and all of the new monitor
trace and sampled data must be archived for possible future use. The default mode
of operation of the Performance/Monitor Analysis
densed ACUM files and not the raw data.
If SEEKs data is needed, a sampling technique is suggested. A simple implementa
tion might be to use a CMS EXEC procedure to enable SEEKs for ten seconds
every ten minutes. This would produce SEEKs data while limiting the volume of
data collected. An alternative is to create a list of devices for which data for the
SEEKs class is to be collected.
To create the list, use the INCLUDE or EXCLUDE options of the
lecting data for longer periods of time.
Load Environments of VM/SP
Two distinct uses of
ferences in criteria for acceptable performance may occur. The system may be
required to time share multiple batch-type virtual machines with interactive
machines performing minor support roles; or, the system may be primarily required
to provide good interactive time-sharing services in the foreground, with a batch
background absorbing spare resources of real storage and processor.
After determining the minimum acceptable performance, perform external observa
tions of turnaround time on benchmarks and specify a point beyond which the
addition of more users would be unacceptable. However, when that point is
reached, more sophisticated internal measurement is required to determine the
scarcest resource and how the bottleneck can be relieved by additional hardware.
Several possible conditions can be identified resulting from different bottlenecks.
They are:
Performance Observation and Analysis 59