Quantifying Production Workloads

In any production environment, a minimum six sets of workload parameters affect the capacity requirements of a system and hence its costs:

1. Numbers of active users

2. Volumes of data generated and used by applications

3. Type, size, and volume of transactions

4. Type, size, and volume of database queries

5. Type, size, and number of documents generated and printed

6. Batch workloads, including data consolidations, backup operations, and production printing

These parameters can vary widely within a company, as well as between different types and sizes of businesses in different industries. As a result, use of standardized, generic measurements for quantifying system performance is one of the most common causes of cost underestimates.

Because there is no such thing as a generic business, any valid computing cost comparisons must be specific to the needs of an individual business organization.

Most standardized measurement techniques have little relevance to the performance that will actually be experienced by users in any given production environment.

For example, much of the industry debate about millions of instructions per second (MIPS) is based on a fundamental error. Instruction sets, as well as the complexity and size of instructions, and the system processes that are instructed vary widely between systems. MIPS has no validity in a cross-architecture comparison. In addition, MIPS represents only a measure of CPU performance. In any real production environment, the performance actually experienced by users is influenced by hundreds of different parameters.

Measurements of transaction performance, such as TPC/A, TPC/B, or TPC/C, are based on stylized suites of software and workloads. These rarely correspond to the applications portfolios, transaction volumes, or workload characteristics of a specific business. Variations between different types of transactions have a major effect on capacity requirements, and hence on costs.

The use of any single benchmark is inherently misleading because few production systems handle a single type of workload. Transactions and queries may vary widely from application to application, and the overall processing mix is likely to include batch as well as other types of system operations.

Thus, any cost comparison between different systems should be based on quantified workloads that correspond to the current and future requirements of the business.

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