Performance Design Process Principles

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- J.D. Meier, Srinath Vasireddy, Ashish Babbar, Rico Mariani, and Alex Mackman


Contents

Set objective goals

Avoid ambiguous or incomplete goals that cannot be measured such as "the application must run fast" or "the application must load quickly." You need to know the performance and scalability goals of your application so that you can (a) design to meet them, and (b) plan your tests around them. Make sure that your goals are measurable and verifiable.

Requirements to consider for your performance objectives include response times, throughput, resource utilization, and workload. For example, how long should a particular request take? How many users does your application need to support? What is the peak load the application must handle? How many transactions per second must it support?

You must also consider resource utilization thresholds. How much CPU, memory, network I/O, and disk I/O is it acceptable for your application to consume?


Validate your architecture and design early.

Identify, prototype, and validate your key design choices up front. Beginning with the end in mind, your goal is to evaluate whether your application architecture can support your performance goals. Some of the important decisions to validate up front include deployment topology, load balancing, network bandwidth, authentication and authorization strategies, exception management, instrumentation, database design, data access strategies, state management, and caching. Be prepared to cut features and functionality or rework areas that do not meet your performance goals. Know the cost of specific design choices and features.


Cut the deadwood.

Often the greatest gains come from finding whole sections of work that can be removed because they are unnecessary. This often occurs when (well-tuned) functions are composed to perform some greater operation. It is often the case that many interim results from the first function in your system do not end up getting used if they are destined for the second and subsequent functions. Elimination of these "waste" paths can yield tremendous end-to-end improvements.


Tune end-to-end performance.

Optimizing a single feature could take away resources from another feature and hinder overall performance. Likewise, a single bottleneck in a subsystem within your application can affect overall application performance regardless of how well the other subsystems are tuned. You obtain the most benefit from performance testing when you tune end-to-end, rather than spending considerable time and money on tuning one particular subsystem. Identify bottlenecks, and then tune specific parts of your application. Often performance work moves from one bottleneck to the next bottleneck.


Measure throughout the life cycle.

You need to know whether your application's performance is moving toward or away from your performance objectives. Performance tuning is an iterative process of continuous improvement with hopefully steady gains, punctuated by unplanned losses, until you meet your objectives. Measure your application's performance against your performance objectives throughout the development life cycle and make sure that performance is a core component of that life cycle. Unit test the performance of specific pieces of code and verify that the code meets the defined performance objectives before moving on to integrated performance testing.

When your application is in production, continue to measure its performance. Factors such as the number of users, usage patterns, and data volumes change over time. New applications may start to compete for shared resources.


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