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Tools Implementation Details

The following sections describe the details of the tools implemetation.


The IronView product set monitors and manages the networking equipment from Foundry Networks. IronView provides a console for direct access to the network topology. Its main function is the administration of the network topology. It was implemented on the deladmin server.

The Foundry Network devices issue SNMP traps directly to Netcool for the Network Operations Center (NOC) and SLA processing. In this implementation, IronView is installed co-resident with the Message Server (Sun ONE) delegated administrator services because the IronView processing requirements are very low.

Sun Management Center 3.0

The SunMC 3.0 software is an element manager that details and monitors the operation of Sun servers, peripherals, and applications. In the context of the iFRC program, SunMC is used primarily to provide low-level monitoring of the application servers to report on hardware and operating system stresses and faults.

Loren Pearce from SunPS collected and described the following details on Sun Management Center 3.0.

SunMC 3.0 has a three-tier architecture. The first tier includes the "agents" that collect information and alerts from the individual systems being monitored. The second tier is a server component that collects information from the monitoring agents and reports this information to the clients. This tier also provides automation capabilities.

The third tier is the client tier that is usually provided by the server, console, and an agent component all executing on one system. Additional agents are deployed to the application servers for monitoring of these systems. The console is viewed using Sun Ray™ appliance displays. While this is not unusual, it is not necessary to combine the three components of SunMC 3.0 on one system.

In addition to monitoring and reporting on the application servers, SunMC 3.0 agents are deployed on the systems management servers in order to monitor their operation and alert the systems administrator to any problems within the monitoring complex.

Figure 3FIGURE 3 SunMC 3.0 Configuration

TABLE 2 details how the various components of SunMC 3.0 are distributed throughout the system topology.

TABLE 2 SunMC 3.0 Component Distribution





SunMC server











SunMC console




SunMC agent



SunMC agent replaces standard snmp daemon


























































The Netcool SunMC probe collects alerts for reporting to the NOC and the SLA manager. This probe acts as a client to SunMC to capture the system level events and forwards them to the Netcool database.

SunMC also provides investigation and alert management through its console. The console is made available as part of the system administration view so that a system operator can obtain additional details pertaining to outages detected in the environment. With this information, the system administrator can determine the correct course of action for resolving the operational impact.


TeamQuest performance software monitors the performance metrics of the environment against the best practices as defined in the Sun Professional ServicesSM (SunPS) program performance tuning and capacity planning methodology, outlined in the "Implementation Requirements" section of the previous article. When performance target violations are detected, alerts are sent to Netcool in the form of SNMP traps that are then processed and forwarded to the NOC and SLA views.

TeamQuest also provides capacity planning and performance tuning capabilities.

This section describes the details of how the iFRC implemented certain aspects of performance management. It was provided by Scott Johnson, Senior Engineer and Joe Rich, Manager Corporate Technical Relations, from TeamQuest Corporation, who provided the technical expertise and tools.

TeamQuest View and TeamQuest Model were the two products used in the iFRC to provide a mechanism to capture and report on the performance and capacity of the systems in the architecture.

TeamQuest View is a comprehensive, analytical tool that reports system performance and helps locate bottlenecks. Performance data is collected from several different sources on the system and stored into a local database for real-time or historical analysis.

TeamQuest Model provides predictive analysis required for long-term capacity planning. This tool, using data retrieved from the architecture systems, was used to build models of the systems and applications. These models were validated against the benchmark data and were used to experiment with "what-if" questions relating to the number of users and the effects of equipment changes.

TeamQuest View

TeamQuest View consists of a server-based component (framework) that is responsible for (among other things) performance data collection and storage and threshold violation notification. TeamQuest View also has a Motif-based client GUI (TQView) which, when connected over TCP/IP to the server component, produces graphical displays of both real-time and historical performance data. In the iFRC, the client GUI with associated reports is located on a separate server with automatic login capability from any one of several management stations connected to a SunRay server. Upon login, TQView automatically establishes a connection to the desired architecture server and produces a series of predefined performance reports (operational views). The reports consist of a number of statistics that were selected from baseline performance monitoring metrics as defined in the SunPS performance tuning and capacity planning methodology. FIGURE 4 is one example, showing important CPU metrics, the top 10 busiest disks, the number of RPC client calls per second and the buffer read and write cache hit percentages. In addition to these reports, TeamQuest provides a large number of pre-defined reports and also supports ad hoc report generation.

Figure 4FIGURE 4 Operational View Example of the Message Server (Sun ONE) from TeamQuest View

Threshold Violation Detection and Notification

The TeamQuest Framework component samples data at a preset interval and stores that data into its performance database. default sampling rate of one minute is implemented. As the data is collected, TeamQuest automatically checks the values of the statistics against any defined threshold levels. A set of thresholds, based on baseline performance monitoring metrics as defined in the SunPS performance tuning and capacity planning methodology, was established for all of the servers in the architecture.

When a threshold criterion is met, an alert is issued. The default action is to log the event into the performance database in the alarm log. In addition, the iFRC team chose to send all alerts through an SNMP trap to the MicroMuse Netcool Omnibus console. MicroMuse assisted in the integration of the TeamQuest View client as a tool under Netcool so that it could be launched in context to the server that issued the alert. In this way, a report showing a graph of the statistic in violation can automatically be generated. FIGURE 5 and FIGURE 6 show drilling down from an alert event sent to Netcool to the statistic in violation on the server under stress.

Figure 5FIGURE 5 MicroMuse/TeamQuest View Integration

Figure 6FIGURE 6 TeamQuest View Report as a Result of the "Start in Context" by MicroMuse

Application Level Resource Reporting

When monitoring, tuning, and predicting capacity of systems, identifying the critical applications (or workloads) of the system is imperative. SLAs are usually created for these critical applications, and thus dictate which workloads must be monitored.

TeamQuest provides a mechanism, through identification of the processes that comprise an application, to track the resource consumption of that group of processes. Through a definitional language, the user builds process groups that are called workloads.

For the IDC Mail and Messaging Architecture, a common set of workload definitions is created and loaded into the TeamQuest performance database on each system.


To enhance the data collection, Solaris OE process accounting was enabled on all of the systems. Thus when a sample was taken, both the running process activity and the completed process activity was merged to provide the best capture ratio.

TeamQuest reduction processing was deactivated so that each and every process captured was recorded into the performance database.

As TeamQuest process-level data was collected, it was compared to the workload definitions and deposited into the appropriate workload container. This allowed the iFRC team to do several very important functions:

  • Monitor (and alert on) the resource consumption by workload.

  • Provide the basic operational entities for the capacity planning exercises described later. In addition to the prestored workload definitions, TeamQuest has the capability to reprocess the raw process data after the fact into workloads, thus allowing for "tuning" and further refinement of the workloads. TABLE 3 lists the workloads and their definitions for the MAIL servers.

TABLE 3 Sample and Workload Definitions

Workload name



Management Services

Processes associated with TeamQuest Performance software or SunMC monitoring agents

command = /tq.*/ or command = esd


Processes associated with Sun Cluster

fullcmd = /.*cluster.*/


Message store maintenance program (deadlock checks, message deletion, and so forth)

command = stored and

login = mailsrv

Post Office Protocol (POP)

Processes that handle POP3 messages to/from MMP servers

command = popd and

login = mailsrv

(Internet Mail Access Protocol (IMAP)

Processes that handle IMAP4 messages to/from MMP servers

command = imapd and

login = mailsrv

Simple Mail Transfer Protocol (SMTP)

Processes that handle the MTA queue for (SMTP) messages

login = mailsrv and

((command = tcp_smtp_server) or (command = ims_master))

Other Message Server (Sun ONE)

Any other processes associated with the Message Server (Sun ONE) application

login = mailsrv


Any processes not explicitly included in the preceding workloads


FIGURE 7 is a screen display of one of the mail servers showing the overall CPU utilization along with the same utilization broken out by course application workloads and finally by a finer granularity set of workloads. It is easy to see how much of the resource each application is consuming and, within the Message Server 5.1 (Sun ONE) application, which specific mail protocol is using the most resources (POP).

Figure 7FIGURE 7 Overall CPU Utilization By Workload

Capacity Planning

As mentioned earlier, TeamQuest Model is the capacity planning tool that was used in this study. TeamQuest Model applies operational analysis principles to measured computer system performance data to build baseline performance models. You can then modify the baseline models to predict system performance when configurations and/or workloads change.

The models are known as queuing network models (QNMs). A QNM consists of a set of resources (CPU, disks, terminals, and so forth) that can be visited by customers from one or more workloads. Workloads can have unique intensities (arrival rates or populations), priorities, and average service demands (visits and service times per visit) at resources. Solving a QNM produces estimates of throughputs, response times, queue lengths, and utilizations for each workload at each resource, as well as estimates of overall workload throughputs and response times.

Results are presented in spreadsheet like displays and charts. For example, components of response time charts allow performance analysts to quickly assess impacts of queuing delays at resources on workload response times.

TeamQuest Model provides two methods to solve QNMs—approximate mean value analysis (MVA) and simulation. Approximate MVA is normally used, since it is much faster than simulation. Approximate MVA iterates solving for response times, throughputs and queue lengths until convergence occurs for all workloads at all resources. Approximate MVA is the method that was used to model the messaging IDC reference architecture systems.

Baseline models of several representative benchmarks were created, including an enterprise model, built by including a representative system from each server class in the messaging system.

Since actual transaction completion rates were not available for the user activity, a synthetic transaction rate was constructed based on the email sender test profile and the number of users. FIGURE 8 shows the throughput of the two major workloads for the enterprise. The throughput rate is the transactions per second based on the synthetic transaction definition discussed previously.

Figure 8FIGURE 8 Major Workload Throughput

The SMTP workload throughput increases as the number of email senders increases. However, the throughput for the POP workload increases steadily only to the 54000/29000 user level and reaches a plateau by the 64000/34000 user level. This indicates that something is constraining the activity of the POP workload.

Further analysis indicates that the constraint occurred in the MMP server. FIGURE 9 shows that the CPU for mmp01 is about 95 percent utilized and is most likely the constraining factor.

Figure 9FIGURE 9 Five Most Active Resources for System mmp01

In the benchmark, the configuration consisted of six MMP servers, which would appear to be able to support about 8000 email readers. The models suggest that to support the 94,000 email reader level would require 12 Netra T1 systems.

Since TeamQuest Model allows you to play "what-if" scenarios both on population growth and on configuration changes, you can see the results of the same workload run on a two-CPU or a four-CPU Netra t1405. (The relative performance characteristics of the CPUs were provided by SunPS).

With the MMP servers upgraded to a two-CPU Netra t1405, the enterprise is able to adequately process the work. FIGURE 10 shows the throughput for both the POP and SMTP workloads steadily increasing as the number of users increases.

Figure 10FIGURE 10 POP and SMTP Throughputs on MMP Servers as Two-CPU Netra t1405 Servers

The active resource utilization for each system indicates that there are not any bottlenecks in any of the systems (MMP – 8 percent, messaging – 39 percent, MTA – 18 percent). However, if we continue our modeling exercise, and double the number of active users, the MMP server becomes saturated. Then, increasing the hardware on the MMP server is necessary. By modeling a number of "what-if" scenarios, we arrive at a four-CPU configuration that adequately supports the doubling of the population. FIGURE 11, FIGURE 12, and FIGURE 13 show the active resource utilization for each system type, supporting up to a 194000/99000 user level.

Figure 11FIGURE 11 mmp01 Active Resource Utilization (4-CPU Netra t1405 Server)

Figure 12FIGURE 12 smtp01 Active Resource Utilization (4-CPU Netra t1405 Server)

Figure 13FIGURE 13 ha01 Active Resource Utilization (12-CPU Sun Fire 6800 Server)

The ha01 system, being one of the message store systems, is handling the mail demands of the increased user population easily.

Through the TeamQuest Performance software, the iFRC team could provide accurate server sizing information based on the various end-user usage requirements.


The Micromuse Netcool product suite is implemented to collect events and information from the other system management tools, consolidate this information, assess the impact on the environment, and produce service level reports and information against the application set. This is accomplished using the following Micromuse products

  • Object Server: The Netcool Object Server is an in-memory database that provides event collection, filter design, and view services. The Object Server provides the foundation upon which the other products in the Netcool suite operate. In the iFRC configuration, redundant object servers are installed in order to provide fault tolerance to the collection system.

  • Internet Service Monitors: The Micromuse Internet Service Monitors (ISM) allow monitoring of 17 different protocols and constructing a simulated transaction. They can be set up in a distributed master/slave relationship, and do not require agents on the remote host that provides the service being monitored. Using the ISMs, you can monitor the Message Server 5.1 (Sun ONE) functionality (LDAP, SMTP, POP, and IMAP) and report their availability for SLA monitoring purposes.

  • Impact: The Micromuse Impact product allows super-imposition of business logic onto the data that has been captured by probes and monitors and is in the Micromuse Object Server. Impact also allows sophisticated event correlation over time, execution of tests to verify events, event consolidation and event enrichment to name a few possibilities.

  • Visionary: The Micromuse Visionary product is an analysis tool that utilizes weighted measurements of various SNMP collected values to assert certain fault conditions exist. It is an attempt to be an engineer in a box. Visionary uses weighted MIB expressions to define the state of something measurable via SNMP (BGP health, Host status, and so forth). You can create your own MIB expressions to be used in the polling and analysis.

  • WebTop: The Micromuse WebTop product is a two-directional Java_ interface into the Netcool Object Server Event List. WebTop can be configured to provide a one-directional (read-only) view to events pertinent to a specific customer.

Netcool Topology

As previously mentioned, the Netcool Object server has been installed on two servers in the IDC Mail and Messaging Reference Architecture implementation in order to provide some level of redundancy to the Netcool system. These Object servers are connected to each other using a bidirectional gateway. With this gateway, a Virtual Object Server is created with the two "real" Object Servers as the participants. Clients need only reference the name of the Virtual Object Server. Object Server operations are performed by one of the two real Object Servers and then synchronized with the other. This scheme provides fault tolerance for the object server.

Monitoring of the Message server 5.1 (Sun ONE) application environment is accomplished using probes provided with the Micromuse suite of products. These probes collect information from the management tools, normalize the information into a standard format, and then inject the resulting record into the database. Probes installed in this environment are:

Syslog: The syslog probe monitors the syslog output of the servers and reports potential problems and failures to the SLA manager and the NOC.

mttrapd: The mmtrapd facility listens for and handles traps. In this implementation, this facility is receiving traps from TeamQuest and normalizing the information. From these traps, the following information is collected:

  • System name that generated alarm

  • User text added to alarm

  • TeamQuest severity

  • Sampled value

  • Normal/Previous/Current threshold values

  • Timestamp of alarm occurrence (from TeamQuest)

  • User text description line 1

  • User text description line 2

  • User text description line 3

  • Current TeamQuest database name and hostname where TeamQuest detected the alarm, main alert bucket, subgroup1, subgroup2, subgroup3, application statistics

SunMC: The SunMC probe connects to the SunMC 3.0 server in order to receive SunMC events and passes filtered and normalized information to the Netcool object server. The contents of the specific record passed back to the Netcool object server are dependent upon the type of alert that was generated by SunMC.

The Netcool components are distributed in the iFRC as follows:

TABLE 4 Netcool Component Distribution





Object Server

Part of virtual object server



Monitors Message Server (Sun ONE) applications



Gets traps from TeamQuest


syslog probe



Process Automation



License Server



Object Server

Part of virtual object server


syslog probe



Bidirectional Gateway

Combines with ncdb to create a virtual object server


Process Automation



SunMC probe



Process Automation

Monitors SunMC probe


License Server

With SunMC probe license

Netcool Console Services

The Netcool implementation provides a NOC view of the environment that is a consolidation of the alerts and information from the other monitoring components. This is a standard feature of Netcool and is provided on the NOC console for Netcool.

In addition to the NOC view, Netcool Impact generates a Service Level Management (SLM) view of the environment. By monitoring the information being generated by the other monitoring tools and the ISMs, Impact can determine how service levels on the application are affected and generate alarms on the SLM view.

In cases where there are performance impacts to the monitored applications, you have the ability to interrogate live TeamQuest graphs and reports directly from the Netcool SLM view. This is accomplished by creating a customized menu tool on the Netcool display and linking that directly to the TeamQuest agent that sent the alarm.

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