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Playbook: Staying One Step Ahead of Performance
Predicting demand for your application load, network traffic, and disk or any other system resources is the toughest part of performance planning. Not only do you need to know the intimate details of the underlying technologies, you need to be familiar with the inner workings of your organization's business and to understand how those aspects affect demand.
In your performance analysis, first examine how application logic is distributed across your endpoints and determine the minimum bandwidth and latency requirements for each user session, as well as the expected peak-processing load, for instance. Because these factors vary from application to application, you'll need to scrutinize them on a case-by-case basis. With Web applications, for example, the processing load typically falls on the server, and processing time is more important than network latency. VoIP (voice over IP), meanwhile, relies heavily on the network, since the technology usually is implemented as a peer-to-peer system.
You can learn a lot from tracking your system's usage patterns. Short-term usage patterns, for instance, affect the demands on your system's resources: When a user fires up his or her application, there's usually a flurry of initial traffic as the client authenticates to the system and navigates to its destination. Traffic dies down after login, as does the demand on system resources. You can take advantage of this ebb and flow by off-loading certain tasks. For example, you can run authentication on a dedicated server rather than cramming everything onto one server.
Another trend you can glean from your usage data is peak traffic. With business applications, production workloads usually peak midmorning and midafternoon, while staff-related traffic, such as data entry, typically remains steady around the clock. Of course, if your users are spread across the nation or the world, working hours will vary by time zone. You should design your servers and network to accommodate spikes in usage before and during busy seasons--for example, at holiday time if you're a retailer, or in April if you're an accounting firm.
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