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Foglight 5.9.7 - Performance Tuning Field Guide

Overview Hardware and Operating System Tuning Management Server Tuning Java Virtual Machine Tuning Backend Database Tuning High Availability (HA) Tuning Agent Tuning Appendix: Performance Health Check Appendix: Analyzing a Support Bundle

---- com.quest.nitro:service=Derivation

This is the derivation service. Its most useful attributes are:

•
DerivationRuletteCount—the number of derivation rulettes.
•
ComplexDerivationDefinitionCount—the number of derivation definitions.
•
EvaluationCount—the number of derivation evaluations made. From release 5.2.3, this is a delta value for the previous 30 seconds. Prior to release 5.2.3, it was a cumulative count from when the server started, so it was not as useful.

This service also provides more detailed information for each derivation definition, and each derivation rulette, including the number of evaluations, the last time it was evaluated, the result of last evaluation, and so on.

Derivation Related Issues

This service is most often the cause of diagnostic snapshots that are 500 to 600 MB in size. Large file sizes indicate you may have an issue with an excessive number of derivations.

Identifying and Resolving Derivation Related Issues

Search the file for: with .* derivation rulettes. The results should resemble the following:

DATA_DRIVEN with 115 derivation rulettes

DATA_DRIVEN with 115 derivation rulettes

DATA_DRIVEN with 187230 derivation rulettes

DATA_DRIVEN with 97 derivation rulettes

DATA_DRIVEN with 115 derivation rulettes

The third line (187230 derivation rulettes) indicates an issue because the number of derivation rulettes is significantly larger than any other rulettes listed. Locate the complex derivation definition (located above the with .* derivation rulettes section in the file), and make a note of the topology type and metric name. For example:

Complex derivation definition: DBSS_Total_Elapsed_Time_Per_Exec (null) : DerivationCalculation for DBSS_Top_Sql

where DBSS_Top_Sql is the topology type and DBSS_Total_Elapsed_Time_Per_Exec is the metric name.

If there is evidence of derivation problems, contact Quest Support with this information for further assistance and to determine if the issue has been resolved in the latest version of the affected cartridge.

---- com.quest.nitro:service=Topology

This is the topology service.

The most useful part of this service is in the extra information, which lists all topology types and, for each type, the number of instances, the number of instance versions, the maximum versions, and the effective instance versions. This information helps you determine if the topology is too large, or if there is a topology churn. Look for a high number of versions of instances, as well as a high maximum versions.

The topology table has the following six columns:

1
Topology Type—name of the topology object type.
2
Num Instance Version—number of versions of all instances of this topology type combined.
3
Max Version—version number of the single most changing instance.
4
Num Effective—number of active instances of this object.
5
Num Recent Versions—number of new versions of all instances in the last seven days.
6
Num Recent Instances—number of new instances created in the last seven days.

Topology Related Issues

Topology churn is defined as the constant changing and creation of new versions of existing topology objects. Each time a property is updated on an instance, a new version of that instance is created. Topology churn can cause high CPU usage as the Management Server propagates the changes across the rest of the topology model.

Topology growth is defined as the continuous creation of new instances of a type of topology object. Topology growth can cause high CPU usage as models and rulettes are updated, as well as increased JVM heap usage. The entire topology model is stored in memory, so as the number of objects added increases, so does the heap usage.

Identifying and Resolving Topology Churn and Growth

If the values in columns five and six in the table above are greater than 5000, examine the highest numbers and work your way down the list. Resolving issues with the higher ones can sometimes resolve other churn issues, since topology changes to one object can cause changes in other objects.

For example, consider the sample rows of the topology table below:

| DBO_Alert_Log | 76 | 2 | 38 | 76 | 38 |

This is an example of a good model. There are 38 instances (column 4), with a maximum of 2 versions (column 3), for a total of 76 versions (column 2). The numbers are in balance.

| DBO_Datafile | 5816 | 2 | 2908 | 2 | 1 |

This is also an example of a good, stable model. Even though the numbers are higher, 2908 x 2 = 5816, so the numbers are in balance. Additionally, in the last 7 days, there was only 1 new object, with 2 changes. There is no large growth or churn in this example.

| DBO_Undo_Activity_Info | 393761 | 16810 | 39 | 0 | 0 |

This is an example of a model that was bad but has become good. There are 393761 total versions in history, but no new changes (0) in the last 7 days.

| HostNetwork | 238231 | 4472 | 846 | 234543 | 42 |

This is a bad topology model. A large number (234543) of new versions have been created in the past 7 days.

| VMWESXServerPhysicalDisk | 28652 | 3 | 3530 | 10590 | 5295 |

This is also a bad model. In the past 7 days, 5295 new instances have been created. Column 4 indicates that some stale object cleanup has been done, but unless the root cause is found, the instances will keep being created.

If there is evidence of topology problems, contact Quest Support with this information for further assistance and to determine if the issue has been resolved in the latest version of the affected cartridge.

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