P

Parameter Set

Parameters Sets are a grouping mechanism for certain properties. A Parameter Set can be applied to a Dynamic Group or a Static Group of Systems.

The properties available for grouping are: Monitoring Parameters, Check Execution, Check Notification, and Monitoring Exception Parameters.

As you can easily see, there may be situations where a certain system belongs to more than one group. If you have the same property defined in two different Parameters Sets sharing a common subset of a system, you have to prioritize the Parameters Sets in order to decide which one is finally effective.

Furthermore, for every Parameter Set, you can define if the definition of a property in a Parameter Set can or cannot be overridden on a per-system level. If cannot, you can define a consistent set of properties throughout a class of the system. But even if you allow overriding, you can re-apply the properties at any time.

Parameters Sets can be scheduled. So, for example, it is possible to have different values for Monitoring Parameters of different periods of time. You may use schedules or service hours to define the validity period of a Parameter Set.

Please prioritize Parameters Sets carefully if they are scheduled!

Performance Data Collection

The following Key Performance Indicators are collected, aggregated, and reported:

System Type	Aggregation	Performance Resource Type	Source
Physical Server	Hourly, daily, and monthly	Total average CPU usage	CPULOAD Check
Total size and used space (kB) of every local filesystem, and accumulated over all local filesystems	FILESYSTEMS Check
Total amount of and used virtual memory	PAGINGSPACE Check
Amount of used physical memory	MEMORY Check
Network I/O transmitted and received kilobytes	NETWORK_IO Custom Check
Disk I/O number of reads and writes	DISK_IO Custom Check
Disk I/O read and written kilobytes
Network Response time	NW_RESPONSE Custom Check
HTTP Response time	HTTP_RESPONSE Custom Check
SAP Instance (ABAP and ABAP+Java)	Hourly, daily, and monthly	Maximum number of concurrent users	Monitoring Tree ActivitySnapshot ActiveUsersCount
Daily and monthly	Average dialog response time and number of dialog steps	Daily Check
Average response time and number of dialog steps for named transactions
Average response time and number of dialog steps of all named transactions together per instance
Top N transaction response times sorted by average response time, and sorted by number of steps
CCMS performance counters	CCMS and CCMS_MONSET Custom Checks
SAP Instance (Java-only)	Hourly, daily, and monthly	J2EE garbage collection runtime ratio	JVMGarbageCollector Check
J2EE DSR average action response time	Average of sum of times (cpu, gen, load, net…) per DSR record with action types unequal to 'unknown'
J2EE DSR number of actions
JVM memory used and allocated space	JVM_MEMORY Check
SAP Instance (Web Dispatcher)	Hourly, daily, and monthly	Number of connections	WD_ConnectionStat Check
Number of threads	WD_ThreadStat Check
Number of queues	WD_QueueStat Check
SAP System (ABAP and ABAP+Java)	Hourly, daily, and monthly	Number of concurrent users	TH_USER_LIST
Number of Transports	TMS_ImportStat Check
Daily and monthly	Average dialog response time and number of dialog steps	Daily Check
Average response time and number of dialog steps for named transactions
Average response time and number of dialog steps of all named transactions together per system
Top N transaction response times sorted by average response time, and sorted by number of steps
Hourly, daily, and monthly	End-to-End ABAP, Java, and HTTP response times	End-to-End Application Monitoring
CCMS performance counters	CCMS and CCMS_MONSET Custom Checks
Database (All Database types, except MySQL and PostgreSQL)	Hourly, daily, and monthly	Database size and used space	ADA_DATAAREA, DB2_TABLESPACES, MSS_DBUSAGE, SYB_DataSpaces, HDB_Disks, ANY_DBSpaces SIQ_DataSpaces and ORA_TABLESPACES Checks
Database (MaxDB)	Hourly, daily, and monthly	Number of sessions	Count of sessions belonging to connected users
Data cache hit ratio
Catalog cache hit ratio
Database (Microsoft SQL Server)	Hourly, daily, and monthly	Number of logons	OS Performance value of counter with name 'User Connections'
Buffer cache hit ratio
Lock wait time
Number of deadlocks
Database (Oracle)	Hourly, daily, and monthly	Tablespace size and used space	ORA_TABLESPACES Check
Number of logons	'logons current' from V$SYSSTAT
Data buffer hit ratio
DD cache hit ratio
User/recursive calls ratio
Sorts in memory
Short table scans
Number of waiting sessions
Enqueue deadlocks, timeouts, and waits
Database (DB2)	Hourly, daily, and monthly	Tablespace size and used space	DB2_TABLESPACES Check
Number of connections	Sum of local and remote connections SNAPDBM
Bufferpool hit ratio
Sort overflows %
LSN gab clean triggers
Time database waited on locks
Lock waits
Deadlocks
Lock escalations
Database (SAP HANA)	Hourly, daily, and monthly	Disk size/usage of named volume partition	Performance data tables M_VOLUMES and M_VOLUME_SIZES
Physical memory size/usage by host
Peak memory limit size/usage
CPU load by host
Number of total lock waits
Total lock wait time per server
Backup Size
Backup Throughput
Database (SAP ASE)	Hourly, daily, and monthly	Number of connections	Count of suids in master.sysprocesses
Cache hit ratio
Database (SAP SQL Anywhere)	Hourly, daily, and monthly	Number of connections	ConnCount from sa_db_properties
Cache hit ratio
Checkpoint urgency
Recovery urgency
Database (SAP IQ)	Hourly, daily, and monthly	Main Cache Size	SIQ_Cache check
Temp Cache Size
Main Cache Used
Temp Cache Used
Main Cache Hit Ratio
Temp Cache Hit Ratio
Catalog Cache Max Size
Catalog Cache Used
Catalog Cache Hit Ratio
Memory Allocated
Connections Active	SIQ_Connections check

System Type

Aggregation

Performance Resource Type

Source

Physical Server

Hourly, daily, and monthly

Total average CPU usage

CPULOAD Check

Total size and used space (kB) of every local filesystem, and accumulated over all local filesystems

FILESYSTEMS Check

Total amount of and used virtual memory

PAGINGSPACE Check

Amount of used physical memory

MEMORY Check

Network I/O transmitted and received kilobytes

NETWORK_IO Custom Check

Disk I/O number of reads and writes

DISK_IO Custom Check

Disk I/O read and written kilobytes

Network Response time

NW_RESPONSE Custom Check

HTTP Response time

HTTP_RESPONSE Custom Check

SAP Instance (ABAP and ABAP+Java)

Hourly, daily, and monthly

Maximum number of concurrent users

Monitoring Tree ActivitySnapshot ActiveUsersCount

Daily and monthly

Average dialog response time and number of dialog steps

Daily Check

Average response time and number of dialog steps for named transactions

Average response time and number of dialog steps of all named transactions together per instance

Top N transaction response times sorted by average response time, and sorted by number of steps

CCMS performance counters

CCMS and CCMS_MONSET Custom Checks

SAP Instance (Java-only)

Hourly, daily, and monthly

J2EE garbage collection runtime ratio

JVMGarbageCollector Check

J2EE DSR average action response time

Average of sum of times (cpu, gen, load, net…) per DSR record with action types unequal to 'unknown'

J2EE DSR number of actions

JVM memory used and allocated space

JVM_MEMORY Check

SAP Instance (Web Dispatcher)

Hourly, daily, and monthly

Number of connections

WD_ConnectionStat Check

Number of threads

WD_ThreadStat Check

Number of queues

WD_QueueStat Check

SAP System (ABAP and ABAP+Java)

Hourly, daily, and monthly

Number of concurrent users

TH_USER_LIST

Number of Transports

TMS_ImportStat Check

Daily and monthly

Average dialog response time and number of dialog steps

Daily Check

Average response time and number of dialog steps for named transactions

Average response time and number of dialog steps of all named transactions together per system

Top N transaction response times sorted by average response time, and sorted by number of steps

Hourly, daily, and monthly

End-to-End ABAP, Java, and HTTP response times

End-to-End Application Monitoring

CCMS performance counters

CCMS and CCMS_MONSET Custom Checks

Database (All Database types, except MySQL and PostgreSQL)

Hourly, daily, and monthly

Database size and used space

ADA_DATAAREA, DB2_TABLESPACES, MSS_DBUSAGE, SYB_DataSpaces, HDB_Disks, ANY_DBSpaces SIQ_DataSpaces and ORA_TABLESPACES Checks

Database (MaxDB)

Hourly, daily, and monthly

Number of sessions

Count of sessions belonging to connected users

Data cache hit ratio

Catalog cache hit ratio

Database (Microsoft SQL Server)

Hourly, daily, and monthly

Number of logons

OS Performance value of counter with name 'User Connections'

Buffer cache hit ratio

Lock wait time

Number of deadlocks

Database (Oracle)

Hourly, daily, and monthly

Tablespace size and used space

ORA_TABLESPACES Check

Number of logons

'logons current' from V$SYSSTAT

Data buffer hit ratio

DD cache hit ratio

User/recursive calls ratio

Sorts in memory

Short table scans

Number of waiting sessions

Enqueue deadlocks, timeouts, and waits

Database (DB2)

Hourly, daily, and monthly

Tablespace size and used space

DB2_TABLESPACES Check

Number of connections

Sum of local and remote connections SNAPDBM

Bufferpool hit ratio

Sort overflows %

LSN gab clean triggers

Time database waited on locks

Lock waits

Deadlocks

Lock escalations

Database (SAP HANA)

Hourly, daily, and monthly

Disk size/usage of named volume partition

Performance data tables M_VOLUMES and M_VOLUME_SIZES

Physical memory size/usage by host

Peak memory limit size/usage

CPU load by host

Number of total lock waits

Total lock wait time per server

Backup Size

Backup Throughput

Database (SAP ASE)

Hourly, daily, and monthly

Number of connections

Count of suids in master.sysprocesses

Cache hit ratio

Database (SAP SQL Anywhere)

Hourly, daily, and monthly

Number of connections

ConnCount from sa_db_properties

Cache hit ratio

Checkpoint urgency

Recovery urgency

Database (SAP IQ)

Hourly, daily, and monthly

Main Cache Size

SIQ_Cache check

Temp Cache Size

Main Cache Used

Temp Cache Used

Main Cache Hit Ratio

Temp Cache Hit Ratio

Catalog Cache Max Size

Catalog Cache Used

Catalog Cache Hit Ratio

Memory Allocated

Connections Active

SIQ_Connections check

Performance Indicators are shown in the UI and reported in the Service Level Reports for those Systems where Performance Data Collection is turned on. This can be turned on or off on a per-System (via PerfDataCollection Monitoring Parameter) level.

Performance Indicators are aggregated automatically into hourly, daily, and monthly values, whereas hourly and daily values are kept for six months and monthly values are kept for three years in Avantra (see also Performance.PERFDATA_KEEPTIME_MONTHLY).

PostgreSQL Database

Avantra allows you to monitor any PostgreSQL as a stand alone database. Similar to other monitored objects, Avantra provides a number of out of the box checks which are applied to a PostgreSQL monitored object automatically. To understand how to add a PostgreSQL database, please follow the guide covering Defining stand-alone Databases.

The out of the box checks include:

Predictive Analytics

Predictive Analytics is the Avantra Enterprise Edition approach to “spikey”, “bursty”, or “flapping” monitoring situations for checks based on time series data. It combines Machine Learning algorithms to predict future trends with classic threshold based monitoring.

This function is only available with the Avantra Enterprise Edition. For more information about editions please see the Avantra Editions Matrix.

There are situations where thresholds are too static, or become too strict. The intention of thresholds is to define a long term separator between good and not so good. Usually a situation only becomes critical if a threshold is exceeded over a longer period of time. Whenever resource usage is spikey, or there are usage bursts, thresholds can be exceeded for a short period of time, although this does not constitute a critical situation.

From a technical perspective it tricky is to decide: is a certain situation only a usage spike, or is it the beginning of a longer term problem?

Predictive Analytics tries to remediate this dilemma. The Avantra agent applies ML based algorithms to understand usage patterns and to predict - at every given point in time - how the usage will evolve in the near future. These predictions are used to determine a trend whenever the agent evaluates a check. And this trend is taken into account, in addition to the defined thresholds.

If a threshold is exceeded and the predictive analytics engine projects the situation clears again within a short period of time, the check status will not be changed. Only if the situation is projected to get worse the check status is changed immediately.

Staring with Avantra 21.11, the Predictive Analytics Engine is enabled in the CPULOAD and the HDB_CPULoad checks. It will successively be rolled out to other checks based on time series data.