The problem with automated provisioning (I of III)

Referring back to my previous article “The problem with automated provisioning – an introduction” once you get over these too human of issues into the ‘technical’ problem of provisioning then I’d have been much nearer the mark in my initial assessment, because it is indeed an issue of complexity. The risks, costs, and likely success, of setting up and maintaining an automated provisioning capability is integrally linked to that of the complexity of the environment to be provisioned.

There are a number of contributing factors, including, number of devices, virtual instances, etc., location and distribution from the command and control point, but the two main ones in my mind are “Number of Instances” and “Frequency of Change”.

And so ‘Complexity’, in terms of automated provisioning, at a macro level, can be calculated as being “Number of Instances” versus “Frequency of Change”.

No. of Instances x Freq. of Change

By “Number of Instances” I mean number of differing operating systems in use, number of differing infrastctrue applications, number of differing application runtime environments and application frameworks, number of differing code bases, number of content versions being hosted, etc.

By “Frequency of Change” I am drawing attention to patches, code fixes, version iterations, code releases, etc., and how often they are delivered.

The following diagram demonstrates what I frequently call ‘The Problem with Provisioning’; as you can see I’ve delineated against three major architectural “levels”, from the lowest and nearest to the hardware, the OS layer which also contains ‘infrastructure software’, the Application layer, containing the application platform and runtime environment, and the “CCC” layer containing Code, Configuration and Content.


In a major data-centre build-out it is not atypical to see three, four or even more, different operating systems being deployed, each of which is likely to require three or six monthly patches, as well as interim high value patches (bug fixes that effect the functionality of the system and security patches). Furthermore it’s likely the number of ISV applications, COTS products, and application runtime environments will be much higher than the number of OS instances, and that the amount of “CCC” instances will be even higher.

I find it important to separate the system being provisioned into these three groupings because, typically they require differing approaches (and technologies) for the provisioning thereof, something I mentioned in the previous article when organisations mistakenly believe that the provisioning technology that they have procured will scale the entire stack, from just above ‘bare metal’ to “CCC” changes (I’ve seen this issue more than once, even by a Sun team who should of known better, albeit it was around three years ago).

This model brings to the fore the increasing level of complexity, both of components at each layer, and the frequency of changes that then occur, and although the model above is a trifle simplistic, it is useful when describing the issues that one can encounter with implementing automated provisioning systems, especially to those with little knowledge or awareness of the topic.