Compaq ProLiant 6000 Performance of Microsoft Exchange Server 5.0 on Compaq Pr - Page 5

LoadSim

Page 5 highlights

ECG052.0897 WHITE PAPER (cont.) 5... For example, in any system there will be bursts of activity due to coincidence, when more users than usual initiate actions at nearly the same time. These bursts can be random in nature or a consequence of scheduled events that affect many users on the same server, such as when a large meeting adjourns. Additionally, the near-real-time notification mechanisms built into Microsoft Exchange Server may contribute to the quantum effect. Users on the same server are notified that a new message has arrived at essentially the same time. If the message was sent to a large number of users, a burst of activity may occur as many of those users read the message immediately upon receipt. Fortunately, the quantum effect becomes less and less significant as the number of users hosted per server increases. Because of the large number of users Microsoft Exchange Server can typically host, even on small servers, only the largest variations in user activity are typically noticeable by the server. From the user's perspective, however, the quantum effect is still noticeable if the server is under load. The sudden increase in server load affects the delay between the initiation of an action by the user and the server's response to it. LoadSim The main tool used in generating the performance data contained in this paper was the Microsoft Exchange Server User Load Simulation utility called LoadSim. As its name implies, LoadSim is a tool for simulating a client user load on an Exchange Server. Its purpose is to enable a single Windows NT machine-called a LoadSim client-to simulate multiple Microsoft Exchange client users. The current version of LoadSim not only provides simulation of MAPI protocol clients but also provides support for POP3, NNTP, LDAP, and HTTP client protocols. The operation of LoadSim users is governed by a LoadSim profile. This profile controls factors such as how long a LoadSim 'day' is, how many email messages to send in a day's time, how many times to open and read existing email, whether to use distribution lists, whether to use public folders, etc. LoadSim is a simulator and therefore not a perfect image of real-world activity. Because of the nature of the product and the quantum effect discussed previously, it is impossible to fully emulate a client. Thus there are two points to remember when considering this data: First, the LoadSim results do not properly address users' logging on and off. When a test is run, all users log on sequentially. Once this process is complete, users begin their tasks. If users typically log on and off multiple times during the day, the NT logon can have an impact on server and network rates of utilization, especially when many users log on simultaneously. Based on your organization's implementation, these factors could pose important considerations in addition to those presented in this paper. The second point to remember is that the response numbers generated by LoadSim are based on server response to clients and do not account for strictly client-side actions such as rendering rich text once a message is received. LoadSim, despite possible shortcomings, creates a highly accurate simulation of reality. It mimics the full Microsoft Exchange Client in many respects. First, it uses .MSG files, the same format used by the Exchange Client. This guarantees that messages generated by LoadSim have the same properties as those sent by real users of the Exchange Client. Second, LoadSim uses the same remote procedure call (RPC) semantics as those used by the Client. Third, LoadSim registers MAPI change notifications in the same manner as they are registered by the Client. Finally, LoadSim even emulates the Microsoft Exchange Client list-box cache, which the Client uses for folder and message panes in the viewer when a user browses and selects messages on the server.

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For example, in any system there will be bursts of activity due to coincidence, when more users
than usual initiate actions at nearly the same time. These bursts can be random in nature or a
consequence of scheduled events that affect many users on the same server, such as when a large
meeting adjourns. Additionally, the near-real-time notification mechanisms built into Microsoft
Exchange Server may contribute to the quantum effect. Users on the same server are notified that
a new message has arrived at essentially the same time. If the message was sent to a large number
of users, a burst of activity may occur as many of those users read the message immediately upon
receipt.
Fortunately, the quantum effect becomes less and less significant as the number of users hosted
per server increases. Because of the large number of users Microsoft Exchange Server can
typically host, even on small servers, only the largest variations in user activity are typically
noticeable by the server. From the user’s perspective, however, the quantum effect is still
noticeable if the server is under load. The sudden increase in server load affects the delay between
the initiation of an action by the user and the server’s response to it.
LoadSim
The main tool used in generating the performance data contained in this paper was the Microsoft
Exchange Server User Load Simulation utility called LoadSim. As its name implies, LoadSim is a
tool for simulating a client user load on an Exchange Server. Its purpose is to enable a single
Windows NT machine—called a LoadSim client—to simulate multiple Microsoft Exchange client
users. The current version of LoadSim not only provides simulation of MAPI protocol clients but
also provides support for POP3, NNTP, LDAP, and HTTP client protocols.
The operation of LoadSim users is governed by a LoadSim profile. This profile controls factors
such as how long a LoadSim ‘day’ is, how many email messages to send in a day’s time, how
many times to open and read existing email, whether to use distribution lists, whether to use
public folders, etc.
LoadSim is a simulator and therefore not a perfect image of real-world activity. Because of the
nature of the product and the quantum effect discussed previously, it is impossible to fully emulate
a client. Thus there are two points to remember when considering this data: First, the LoadSim
results do not properly address users’ logging on and off. When a test is run, all users log on
sequentially. Once this process is complete, users begin their tasks. If users typically log on and
off multiple times during the day, the NT logon can have an impact on server and network rates
of utilization, especially when many users log on simultaneously. Based on your organization’s
implementation, these factors could pose important considerations in addition to those presented
in this paper. The second point to remember is that the response numbers generated by LoadSim
are based on server response to clients and do not account for strictly client-side actions such as
rendering rich text once a message is received.
LoadSim, despite possible shortcomings, creates a highly accurate simulation of reality. It mimics
the full Microsoft Exchange Client in many respects. First, it uses .MSG files, the same format
used by the Exchange Client. This guarantees that messages generated by LoadSim have the same
properties as those sent by real users of the Exchange Client. Second, LoadSim uses the same
remote procedure call (RPC) semantics as those used by the Client. Third, LoadSim registers
MAPI change notifications in the same manner as they are registered by the Client. Finally,
LoadSim even emulates the Microsoft Exchange Client list-box cache, which the Client uses for
folder and message panes in the viewer when a user browses and selects messages on the server.