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TeamQuest (now Vityl Capacity Management) provides unintrusive mechanisms for instrumenting applications and analyzing application performance. Neil Gunther describes how to use those mechanisms.
Dissect the psychology of IT managers that prefer to let a project fail as long as it fails on time in this provocative article by Dr. Gunther.
This article explains how correlated or bunched requests can impact capacity planning results.
This is the final online article concerning the concept of application scalability. Here, you will learn how to determine value of the parameters that control scalability.
This is a little quiz to test your understanding of the triplet of numbers that appear in the UNIX® load average (LA) performance metric.
In this online article Dr. Gunther digs down into the UNIX kernel to find out how load averages (the “LA Triplets”) are calculated and how appropriate they are as capacity planning metrics.
This is the second in a two part-series where we explore the use of UNIX load averages in performance analysis and capacity planning.
This is an unexpected Part 3 to the discussion about the UNIX load average metric answering the question of where the weight factor comes from.
This article is about delusions that arise from incorrect interpretation of load test measurements.
This paper discusses avoiding calculation results that are more precise than is justified by precision of corresponding measurement input data.
In this paper we present an introductory analysis of throughput scalability for update intensive workloads (such as measured by the TPC-C or TPC-W benchmarks) and how that scaling is limited by serialization effects in the software-hardware combination that comprises any platform.
Accurately Capacity Plan with What-if Analysis and Accurately capacity plan for consistent service delivery. *Reduce or eliminate over-provisioning by identifying the least expensive way to accommodate service level requirements. * Get unbiased, vendor-neutral guidance that identifies what you really need as opposed to what your vendor says you need. * Accurately provision systems to avoid costly and time-consuming performance bottlenecks. * Guide business decisions with objective information.
Queuing theory is the study of queues, otherwise known as waiting lines. It sounds straightforward. But unless you have an advanced math degree, queuing theory can be difficult to understand. That’s why we’re clarifying queuing theory basics.
As IT infrastructures continue to grow more complex, finding performance bottlenecks gets hard. That’s why it’s absolutely essential that IT teams have the tools, training, and resources necessary to quickly identify causes of poor application performance.
Watch this webinar to learn how to truly understand your systems and server capacity with simple but effective methods. Plan for future growth—even in your virtual environments.