Monday, March 17, 2014
#em12c Metrics - Part 1: An Introduction
From the middle of 2013, I’d been busy in preparation for one of my presentations for IOUG’s Collaborate 14 Conference in Las Vegas. It is on Capacity Planning Enterprise Manager 12c’s Metrics (available on slideshare), one which I had the honor of presenting earlier at a Georgia Oracle User Group meeting in Atlanta, GA this past week. Metrics in any version of Enterprise Manager are collected (via the Enterprise Manager agents) and stored in its repository database, to be used for rendering historical viewing, but only at each targets respective home page. With EM12c, the list of monitored targets has grown to a staggering amount, especially with the advent of Extensibility Exchange and Metric Extensions (previously known as User Defined Metrics).
From Oracle Databases, multiple Unix Platforms, various types of Middleware products, Oracle VM, The Oracle Cloud, Engineered Systems such as Exadata, Exalogic, and the Big Data Appliance, and many other targets, this tool sure does cover a wide spectrum with an even wider range of metrics (or insights) into each managed target. In addition, using Plug-ins developed either by Oracle or by third party vendors, external hardware/software monitoring is also possible on technology such as VMware, NetApp, Cisco, Brocade, HP Storage, EMC Storage, F5 Load Balancers, and like wise many others. All of this monitored data is indeed stored somewhere, and as I have mentioned earlier, it is simply kept in the Enterprise Managers repository.
Starting with this post, I’d like to begin a series that discusses the various parts and pieces associated with Metrics in Enterprise Manager 12c.
I have already established that data is collected from managed/monitored targets, but have yet to explain the delicate intricacies of that collection. By default, once a target is discovered and promoted in EM12c, the collection of certain metrics that are enabled on a collection schedule. Both of which depend on the target type. As an example, lets take a look at an “Oracle Database”. Each time one is added to the EM inventory, we automatically assume that information regarding its configuration, status, etc will be displayed. That is precisely the kind of “default collection of metrics on a schedule” that I mentioned earlier.
So, how does the data get to the repository? One way to look at it, and some of depictions are straight out of my presentation, is that data from targets is collected by the EM Agents, and pulled into the Management Repository. This is a big shift from the previous releases of Enterprise Manager because they employed the push method (from agents) as opposed to a pull method from the Management Server.
The data lands in the em_metric_value table which contains the “raw” data. A quick look at this table’s structure and data reveals the rawness of the information that is collected.
desc em_metric_values Name Null Type --------------- -------- ----------------------- METRIC_ITEM_ID NOT NULL NUMBER(38) COLLECTION_TIME NOT NULL DATE MET_VALUES NOT NULL EM_METRIC_VALUE_ARRAY()
col metric_item_id format 9999999 heading "Metric Item ID"
col collection_time format a25 heading "Collection Time"
col met_values format a100 heading "Metric Values"
select metric_item_id
,collection_time
,met_values
from em_metric_values
where rownum < 11; -- Only used to restrict the data returned.
Metric Item ID Collection Time Metric Values
-------------- ------------------------- ----------------------------------------------------------------------------------------------------
1561578 13-FEB-14 12.13.46 AM SYSMAN.EM_METRIC_VALUE_ARRAY(null,null,0,0.209,null,0,72.899,null,null,16,0,null,0.018)
1561578 13-FEB-14 12.28.46 AM SYSMAN.EM_METRIC_VALUE_ARRAY(null,null,0,0.191,null,0,68.343,null,null,15,0,null,0.017)
1561578 13-FEB-14 12.43.46 AM SYSMAN.EM_METRIC_VALUE_ARRAY(null,null,0,3.604,null,0,651623.938,null,null,2310,0,null,2.57)
1561578 13-FEB-14 12.58.46 AM SYSMAN.EM_METRIC_VALUE_ARRAY(null,null,0,0.187,null,0,68.343,null,null,15,0,null,0.017)
1561578 13-FEB-14 01.13.46 AM SYSMAN.EM_METRIC_VALUE_ARRAY(null,null,0,0.206,null,0,68.343,null,null,15,0,null,0.017)
1561578 13-FEB-14 01.28.46 AM SYSMAN.EM_METRIC_VALUE_ARRAY(null,null,0,0.184,null,0,68.343,null,null,15,0,null,0.017)
1561578 13-FEB-14 01.43.46 AM SYSMAN.EM_METRIC_VALUE_ARRAY(null,null,0,4.53,null,0,958473.112,null,null,3347,0,null,3.723)
1561578 13-FEB-14 01.58.46 AM SYSMAN.EM_METRIC_VALUE_ARRAY(null,null,0,0.195,null,0,68.343,null,null,15,0,null,0.017)
1561578 13-FEB-14 02.13.46 AM SYSMAN.EM_METRIC_VALUE_ARRAY(null,null,0,0.191,null,0,72.899,null,null,16,0,null,0.018)
1561578 13-FEB-14 02.28.46 AM SYSMAN.EM_METRIC_VALUE_ARRAY(null,null,0,0.19,null,0,63.786,null,null,14,0,null,0.016)
10 rows selected
At regular intervals, this table’s data is aggregated into hourly and daily metric values. The corresponding tables are em_metric_values_hourly and em_metric_values_daily.
To ensure adequate performance, all three tables are partitioned as per the chart below. More information regarding the partitioning strategy can be found in “12c Cloud Control Repository: How to Modify the Default Retention and Purging Policies for Metric Data? (Doc ID 1405036.1)”.
Now, I probably know what you are thinking. If I query the raw data, then what good is it to me in the above format. To understand and view the data coherently, the mgmt$metric_values, mgmt$metric_values_hourtly, mgmt$metric_values_daily OR gc$metric_values, gc$metric_values_hourly, gc$metric_values_daily views which are compliments of the tables mentioned earlier.
You might have seen various queries that use the mgmt$ tables, but from what I seen the gc$ tables are newer versions with slightly different metric column names and labels.
Let’s take a quick look at the gc$metric_values and its contents.
desc gc$metric_values Name Null Type ------------------------- -------- ------------- ENTITY_TYPE NOT NULL VARCHAR2(64) ENTITY_NAME NOT NULL VARCHAR2(256) TYPE_META_VER NOT NULL VARCHAR2(8) METRIC_GROUP_NAME NOT NULL VARCHAR2(64) METRIC_COLUMN_NAME NOT NULL VARCHAR2(64) COLUMN_TYPE NOT NULL NUMBER(1) COLUMN_INDEX NOT NULL NUMBER(3) DATA_COLUMN_TYPE NOT NULL NUMBER(2) METRIC_GROUP_ID NOT NULL NUMBER(38) METRIC_GROUP_LABEL VARCHAR2(64) METRIC_GROUP_LABEL_NLSID VARCHAR2(64) METRIC_COLUMN_ID NOT NULL NUMBER(38) METRIC_COLUMN_LABEL VARCHAR2(64) METRIC_COLUMN_LABEL_NLSID VARCHAR2(64) DESCRIPTION VARCHAR2(128) SHORT_NAME VARCHAR2(40) UNIT VARCHAR2(32) IS_FOR_SUMMARY NUMBER IS_STATEFUL NUMBER NON_THRESHOLDED_ALERTS NUMBER METRIC_KEY_ID NOT NULL NUMBER(38) KEY_PART_1 NOT NULL VARCHAR2(256) KEY_PART_2 NOT NULL VARCHAR2(256) KEY_PART_3 NOT NULL VARCHAR2(256) KEY_PART_4 NOT NULL VARCHAR2(256) KEY_PART_5 NOT NULL VARCHAR2(256) KEY_PART_6 NOT NULL VARCHAR2(256) KEY_PART_7 NOT NULL VARCHAR2(256) COLLECTION_TIME NOT NULL DATE COLLECTION_TIME_UTC DATE VALUE NUMBER
col entity_type format a10 heading "Entity|Type"
col entity_name format a25 heading "Entity|Name"
col metric_group_label format a7 heading "Metric|Group|Label"
col metric_group_name format a14 heading "Metric|Group|Name"
col metric_column_label format a50 heading "Metric|Column|Label"
col metric_column_name format a14 heading "Metric|Column|Name"
col short_name format a15 heading "Short|Name"
col value format 99.99 heading "Value"
select entity_type
,entity_name
,metric_group_name
,metric_column_name
,metric_group_label
,metric_column_label
,short_name
,collection_time
,value
from gc$metric_values
where rownum < 11; -- Only used to restrict rows returned.
Metric Metric Metric Metric
Entity Entity Group Column Group Column Short
Type Name Name Name Label Label Name Collection Time Value
---------- ------------------------- -------------- -------------- ------- -------------------------------------------------- --------------- ------------------------- ------
host server01.planet.net Load cpuLoad_1min Load Run Queue Length (1 minute average,per core) CPU Load (1min) 13-FEB-14 12.01.56 AM 4.08
host server01.planet.net Load cpuLoad_1min Load Run Queue Length (1 minute average,per core) CPU Load (1min) 13-FEB-14 12.06.56 AM 4.11
host server01.planet.net Load cpuLoad_1min Load Run Queue Length (1 minute average,per core) CPU Load (1min) 13-FEB-14 12.11.56 AM 4.03
host server01.planet.net Load cpuLoad_1min Load Run Queue Length (1 minute average,per core) CPU Load (1min) 13-FEB-14 12.16.56 AM 4.03
host server01.planet.net Load cpuLoad_1min Load Run Queue Length (1 minute average,per core) CPU Load (1min) 13-FEB-14 12.21.56 AM 4.01
host server01.planet.net Load cpuLoad_1min Load Run Queue Length (1 minute average,per core) CPU Load (1min) 13-FEB-14 12.26.56 AM 4.00
host server01.planet.net Load cpuLoad_1min Load Run Queue Length (1 minute average,per core) CPU Load (1min) 13-FEB-14 12.31.56 AM 4.01
host server01.planet.net Load cpuLoad_1min Load Run Queue Length (1 minute average,per core) CPU Load (1min) 13-FEB-14 12.36.56 AM 4.11
host server01.planet.net Load cpuLoad_1min Load Run Queue Length (1 minute average,per core) CPU Load (1min) 13-FEB-14 12.41.56 AM 4.01
host server01.planet.net Load cpuLoad_1min Load Run Queue Length (1 minute average,per core) CPU Load (1min) 13-FEB-14 12.46.56 AM 4.00
10 rows selected
I know this blog posts probably lends itself to more questions. What data, other than the one showed above, do we actually have access to in Enterprise Manager? How can we obtain the information and then create reports on resource utilization for trend analysis, and capacity planning? How does Enterprise Manager allow data visualization? Which tools could I use for custom reports? Enterprise Manager does indeed monitor, keep track of, and enables the user to gather a myriad of information from each target.
The data is there.
Stay tuned for future posts which will cover the topics I have touched on in the sections above. If you are headed to Collaborate this year, and are interested in hearing further in-person, my Session # is 102 Capacity Planning: How to Leverage OEM12c for Engineered Systems.
Cheers!
Great post!
ReplyDeleteThanks! Be on the lookout for more, as I have only scratched the surface :)
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