Thursday, 24 January 2013

Consumer/Provider : the twin forces in Capacity Management

Those schooled in traditional IT capacity management have long recognised the cause and effect of observed system behaviour.  Few have managed to bridge the gap in quantifying the correlation, however, and for good reason.  Straying too deep into this territory can leave you struggling with data overload, and no way of mapping volumetric and utilization data together. The age of the CMDB and automated discovery and mapping has changed the landscspe in thus regard.  Finally, using configuration mapping to correlate volumetric data against utilization data can be done reliably, consistently and accurately since all feeds are automated.

Correlating service throughput against observed utilization provides intelligence to optimise design, streamline performance, & predict and optimize application scalability.  But in a consumer/provider scenario there are two contexts to consider. Presenting the customer with data about your underlying infrastructure utilisation lays bare the margin or risk levels of your operating model. Equally, the customer's main concern is ensuring their service levels are not jeopardised, and they are not burdened with excessive costs for underutilized environments.

Despite the advantages commonly sought in quantifying the capacity of the physical environment, it is the capacity of the contractual environment that is crucial to the customer. In a cloud context, the provider must diligently ensure the reliability if their operating model. This is crucial to brand equity. But the customer's primary concern will be in managing the flexibility of their service based contract, and ensuring that risks are properly balanced against costs.

Monday, 14 January 2013

To Transform IT - Revisit The Basics

Big Data and the world of business analytics has much in common with Capacity and Demand Management as we know it.  Pertaining to derive competitive advantage by acting on timely business intelligence, business operations analytics requires number crunching on a huge scale.  In the highly competitive world of e-business, the imperative for business agility reaches its peak.  Where aligning appropriate investment with prevailing demand becomes a critical business decision, no less is the importance of that decision to the world of capacity management.  Meaning - business agility depends on Big Data to make sure there are enough sales reps selling hot products, to make sure there are enough of the right sort of product on the shelves, and to commit the right amount of marketing to the products or services delivering the highest profit. The connection with the IT cloud here is clear - aligning IT resources to demand is equally critical to the agile business.  Indeed, such agility is one of the main drivers behind cloud computing.  By transforming IT delivery into a service model, one has the ability to quickly and easily ramp up investment when warranted by demand - or to ramp down.

Nice idea.  But does this happen widely in the field?  Evidence indicates that the transformation to the cloud model in the majority of organisations has hit a glass ceiling.  With the existence of service catalogues, virtual adaptable infrastructures, and increasingly automated processes - IT organisations have put in place the basic ingredients that enable some of the tasks associated with cloud service provision.  However, the vision of agile IT-on-demand has been held back by slow adoption of a business-integrated view more aligned with the balance sheet.  IT resources like many business resources come at a cost.  Not just a cost to purchase, but a cost to provision, a cost to operate, a cost to maintain and a cost to support.  Factoring cost of ownership into resource provisioning requests, and aligning investment appropriately according to demand, are the two pre-requisites for the agile business.

These pre-requisites translate themselves into two management capabilities that are widely missing in IT operations today.  Adding these capabilities to IT management functions will not only provide insight and control over efficient use of IT resources, but will also provide consumer-friendly insight to support optimal alignment of resources.

Firstly, by garnering control of operational costs - IT cloud operations can start to truly drive efficient investments.  A simple cost / utilization correlation is an excellent start to determining efficiency.  For the most accurate approach, this analysis should be carried out by the Capacity Management team to factor in variables like the different sorts of utilisation (meaning virtual, physical, logical - all of which are environmental related), and for what-if scenario analysis to determine the possibilities for optimization.

Secondly, by assessing usage patterns quickly, dynamically and providing short and mid-term trends to the consumer.  The aim here is to ensure the right amount of headroom is maintained in the environment.  A service-aligned view of capacity allocated is essential, such that the service headroom can be correctly calculated according to the weakest link in the chain.    The insight that's needed is to gauge whether the service headroom will be sufficient to meet demands, according to trends, forecasts and other business analytics.  Regression and correlation  between workload and resource usage is another function classically described in Capacity Management.

So - what are we saying here?  That Capacity Management is the missing link between cloud operations and an agile enterprise?  No - not quite.  Capacity Management as it is currently executed and understood is not fit for this purpose.  However, connecting Capacity Management with both the demand cycle - notably from a service not an infrastructure point of view, and also with Financial Management has the ability to disrupt the enterprise cloud, and transform it to become a true partner to the agile business.