Thursday, 12 December 2013

IT's Day of Reckoning Draws Near

Bob Colwell, Intel's former chief architect, recently delivered a keynote speech proclaiming that Moore’s law will be dead within a decade.  Of course, there has to come an end to every technological revolution - and we've certainly noted the stablization of processor clock speeds over recent years, in conjunction with an increasing density of cores per chip.

Moore's Law has been so dominant over the years, it has influenced every major hardware investment and every strategic data center decision.  Over the last 40 years, we have seen a consistent increase in processing capacity - reflected in both the increase in processor speeds and the increased density of transistors per chip.  In recent years, whilst processor clock speed has reached a plateau - the density of cores per chip has increased capacity (though not performance) markedly.

The ramifications of Moore's Law were felt acutely by IT operations, in two ways.

  1. It was often better for CIOs to defer a sizable procurement by six or twelve months, to get more processing power for your money.  
  2. Conversely, the argument had a second edge - that it was not worthwhile carrying out any Capacity Management, because the price of hardware was cheap - and getting cheaper all the time.

So, let us speculate what happens to IT operations when Moore's Law no longer holds:

  1. IT Hardware does not get cheaper over time.  Indeed, we can speculate that costs may increase due to costs of energy, logistics etc.  Advancements will continue to be made to capability and performance, though not at the same marked rate charted above.
  2. The rate of hardware refresh slows due to the energy and space savings available in the next generation kit.  Hardware will stay in support longer, and the costs of support will increase.
  3. Converged architectures will gain more traction as the flexibility and increased intra-unit communication rates drive performance and efficiency.
  4. You can't buy your way out of poor Capacity Management in the future.  Therefore the function of sizing, managing and forecasting capacity becomes more strategic.

Since capacity management equates very closely to cost management, we can also speculate that these two functions will continue to evolve closely.  This ties in neatly, though perhaps coincidentally, with the maturing of the cloud model into a truly dichotomous entity - being that a supplier and a provider will have two differing views of the same infrastructure.  As the cloud models mature in this way, it becomes easier to compare the market for alternative providers on the basis of cost and quality.

Those organisations with a well-established Capacity Management function are well placed to navigate effectively as these twin forces play out over the next few years, provided they:

  1. Understand that their primary function is to manage the risk margin in business services, ensuring sufficient headroom is aligned to current and future demands
  2. Provide true insight into the marketplace in terms of the alternative cost / quality options (whether hardware or cloudsourced)
  3. Develop effective interfaces within the enterprise to allow them to proactively address the impacts of forthcoming IT projects and business initiatives.

So - the day of reckoning draws near - and IT operations will adapt, as it always does.  Life will go on - but perhaps with a little bit more careful capacity planning....

Tuesday, 3 December 2013

The dichotomy of Capacity Management in a private cloud

The Pushmi-Pullyou - an analogy for the dichotomy of private cloud

The Fable

The two great heads of IT sat and stared at each other across a meeting room table.  It was late in the day, and thankfully their services had all been restored.  Now was the time for recriminations.  The CIO had been called into firefighting meetings with the board all day.  They knew he was going to be royally pissed off, but who was going to get the blame?

The beginning

The story began when service performance nose-dived.  It was always a busy period, the lead-up to Christmas, but this season had been marked by some hugely successful promotional campaigns, and their online services had been humming with traffic.  Nobody quite knew what caused it, but suddenly alarms started sounding.  Throughput slowed to a trickle - and response times rocketed through the roof.  Downtime.  At first the infrastructure team, plunged into a triage and diagnostics scenario, did what they always did.  Whilst some were busy pointing fingers, they formed a fire-fighting team, and quickly diagnosed the issue - they'd hit a capacity limit at a critical tier.  As quickly as they could, they provisioned some additional infrastructure and slowly brought the systems back online.

The background

But why had all this happened?  Some months ago, and at the advice of some highly-paid consultants, the CIO had restructured the business into a private cloud model.  The infrastructure team provided a service to the applications team, using state-of-the-art automation systems.  Each and every employee was soon enamoured with this new way of working, using ultra-modern interfaces to request and provision new capacity whenever they needed it.  Crucially, the capacity management function was disbanded - it just seemed irrelevant when you could provision capacity in just a few moments.

The inquisition

But as the heads of IT discussed the situation it seemed there were some crucial gaps they had overlooked. The VP of Applications confessed that there there was very little work being done in profiling service demand, and in collaborating with the application owners to forecast future demands.  He lacked the basic information to be able to determine service headroom - and crucially was unable to act proactively to provision the right amount of capacity.  In an honest exchange, the VP infrastructure also admitted to failings in managing commitment levels of the virtual estate, and in sizing the physical infrastructure needed to keep on top of demand.  In disbanding the Capacity Management function, they realized that they had fumbled - and in fact needed those skills in both of their teams.

The Conclusion

The ability to act pro-actively on infrastructure requirements distinguishes successful IT organisations from the crowd.  What these heads of IT had realised is that the private cloud model enhances the need for Capacity Management, instead of diminishing it.  The dichotomy of Capacity Management in the private cloud model is that these two functions belong to both sides of the table - to the provider, and to the consumer.  Working independently, they would be able to improve demand forecasts and diminish the risk of performance issues.  Working collaboratively, these twin dichotomies combine in a partnership that allows a most effective way of addressing and sizing capacity requirements to align and optimize cost and service headroom.


  1. As a consumer, ensure you are continually well-informed on service demand and capacity profiles.  Use these profiles to work with your application owners in forecasting different 'what if' scenarios.  Use the results to identify which are the most important metrics, and prepare a plan of action when certain thresholds are reached.
  2. As a provider, ensure you are continually tracking your infrastructure commitment levels and capacity levels.  Use the best sizing tools you can find to identify the right-size infrastructure to provision for future scalability.
  3. Have your capacity management teams work collaboratively to form an effective partnership that ensures cost-efficient infrastructure delivery and most effective headroom management.

Will you wait for your own downtime before acting?