If you are impressed with work experience, then read on as I’ve spent the last 25 years teaching performance fundamentals, capacity planning, modeling, and performance testing of websites. In performance monitoring you need to know three things: the incoming workload, the resource consumption and what is normal.
You need to know the incoming workload (what the users are asking your system to do) because all computers run just fine under no load.
The data you collect can also be used to predict the future with the other three tools in your bag: Capacity Planning, Load Testing, and Modeling.
Capacity planning is the simple science of scaling the observed system so you can see if you have enough resources to handle the projected peak load, but it only works for resources you know about. Load testing is the art of creating artificially generated work that mimics the real work generated by the real users.
Load testing can also help you find where subsystems break, and isolate the effect of one transaction type.
Load testing can tell you many interesting things, but it can only give you data on the computing infrastructure you have now.

This chapter shows you how to gain confidence you will make it smoothly though a projected future peak load by scaling up your current observed load. This spectrum of tools allows one to pare down the number of virtual compounds using a combination of synthetic complexity and interaction scores to hundreds and thousands of virtual ligands employing SPROUT (and or TOPOMAX) with confidence that the complexity triage is indeed linked to the `ease of synthesis’. I spent about 15 of those years also doing performance work on live systems and critical applications for customers around the world. Assuming you know how many guests will show up and have a reasonable understanding of what they will consume, everything you checked should be fine. For any test you need to know how much work you are sending into the system, the throughput and response time for the completed work, and how the system resources are responding under that load. If circumstances change so much that you lack confidence in that prediction, then try modeling. With it, and some work on your part, you’ll be able to solve performance problems and to walk into the CIO’s office with confidence. One then can then obtain a synthetic accessibility score and complete retrosynthetic pathways to known starting materials for a subset of compounds in a matter of minutes using CAESA batch.

Mostly I’ve learned from other performance wizards, programmers, system administrators and a few generally smart people I’ve known.
If you need more confidence in your plan, or you need to hold the response time down to a reasonable level, or if the future you are planning for includes significant changes to the transaction mix or vital systems, then you need to do either Load Testing or Modeling. I would arrive knowing almost nothing about their business and their problems and leave having given them a clear path to follow. The binding site is determined either based on known binding modes of ligands as found in crystal structures of complexes, or based on an educated hypothesis. You would want to use the one where you had confidence that your top scoring poses were the ones with probable low RMSD to the actual pharmacological pose.

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