Exponental Learning and Mumbai

January 11th, 2011

Many of my endeavors have been accelerated tremendously by networks of friends and acquaintances I have. One group of acquaintances and friends is the members of the Oaktable who have from time to time accelerated my projects by their answers, advice and feedback. For example, back when I wrote a program to directly read Oracle’s SGA memory, many people added bits and pieces that kept me on track. I orignally was just dumping memory and looking at the contents when someone pointed me to James Morles work in the area and James pointed me to Jonathan Lewis’s discovery of an offset table etc etc.

Such accelerated learning has been outlined in the book the “Power of Pull” by John Hagel III , John Seely Brown and Lang Davison.

An individual or even a fixed team will have at in general linear output when things are going well, but when different  groups  and far flung individuals work together in tight feedback loops, output, learning and creation can accellerate.

The acceleration is happening more and more with the communication and collaboration that is enables and facilitated by the web.

This collaborative tight feedback loop is what I want to see happen in the database performance tuning arena  and graphical monitoring and what I think I see the beginnings of in  Marcus Mönnig’s Mumbai tool. Marcus creates his own Oracle database tuning tool but also pulls in the work of Tanel Poder’s Snapper package and Egor Starostin Orasrp.


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