One of the frequently asked questions I receive is regarding queuing theory and how it applies to computing infrastructures. I think a good way to explain how computer systems have evolved to address queuing issues is through a burger joint analogy.When I was a kid, there were numerous “mom and pop” burger joints along the roads.  If you wanted a burger, you drove in, went up to the window, placed your order and paid your money.  The people inside cooked up what you requested while you stood there. 

At more popular burger joints, too many people had to wait because it was a one-in, one-out business model.  The busier ones came up with the idea that they would have an “order” window and a “pick-up” window.  This permitted multiple orders to be processed concurrently, reducing the line waiting to be served. The problem was that the order went in quickly, but during busy periods, people queued up at the “pick-up” window instead of the “order” window.

Then large chains used analysis tools (some computer-based) to determine the distribution of orders based on time-of-day and day-of-week.  Based on their analyses, management adjusted manpower schedules and scheduled making up orders in advance. Heat lamps kept the food hot. At peak times, the burger joints could quickly satisfy demand, keeping order and pick-up queues low. Even if there was wasted food, it was acceptable because they were providing faster service and attracting a greater number of customers. The additional volume and associated profits more than offset the rare losses.

Computer technology addressing queuing issues has matured in similar fashion. Old computers using the DOS operating system could only process one job at a time. Then Multiple Virtual operating systems came about. Multiple jobs could be run, however they would vie for the same resources, causing queuing (thus elongated wait times). 

With the advent of cheap memory in data storage (disk) controllers, you could fix data in storage at different points in time so that it was readily available and sped the execution of jobs.  Read-ahead technology was developed at the same time, further reducing job execution times. Current technologies use a wide variety of the above solutions to speed execution of jobs and transactions.  So as you can see, burger joints and computer queuing have a lot in common!

Until the next time

Ron

Thinking of implementing a CMDB?  Maybe you should wait.  According to Gartner, only 3-5% of organizations have a fully operational CMDB. From what I heard, even the vendors are struggling.  No one has a mature, comprehensive offering.  I did learn that there were two components of a CMDB, the database and the dependency mapping tool; and that there were a number of vendors in various positions in the marketplace. 

The Gartner presentation team, Ronni Colville and Patricia Adams, emphasized that you need to understand the business problem you are trying to solve before you even think about building a CMDB. You should have people and processes in place and be operational before you think about buying a tool or tools.

They also stressed that you need to set the correct expectations on implementation as it could take 18 months to two years or more to fully implement. From listening to Ronni and Patricia, it seems to me that CMDB and related tools are in their infancy, that much up-front thought needs to be done and a lot of internal discussions must happen before even thinking about building a CMDB. Considering all that, it might be better to focus on process and delay tool selection until they have matured further.    

At this point most conference attendees are suffering from data overload. I am no exception. It will take me weeks to go back over my notes and think about everything that was said. 

Gartner has out done themselves this year in the quality and applicability of the content. From my perspective, they deserve a standing ovation!

This is my last post of the conference. Hope you have found my posts interesting. For more details regarding these sessions, contact your Gartner representative. 

Thanks for listening! 

Ron