Easing Capacity Planning

ScaleBase improves database capacity planning

ScaleBase can essentially normalize the unpredictable nature of today’s new business applications and business models. While ScaleBase can’t actually forecast demand, it can ease the financial burden of planning for too much or for too little application traffic.

For most companies, database capacity planning continues throughout the company life-cycle as a never ending decision process that defines an overall level of resources needed to respond. Effective database capacity planning can have a significant impact on business operations as inadequacy can lead to the loss of customers.

ScaleBase can drive financial gains from enhancing the capacity planning process to a point of simplicity – in essence reducing the opportunity for error and minimizing the over or under capacity discrepancy.

As seen in the diagram below, there are three main capacity planning strategies used today: lead, lag and match. Only ScaleBase can provide the means for achieving the optimal balance. The three capacity planning strategies are defined as:

1Lead strategy adds capacity in anticipation of an increase in demand. The disadvantage of this strategy is that it usually results in excess capacity, which is costly.

2Lag strategy adds capacity once the organization has achieved full capacity or beyond due to increase in demand. While this may be less costly, it could result in lost business.

3Match strategy adds capacity in relative amounts in response to changing market demands. ScaleBase completely supports this balanced strategy.

Capacity planning strategies

ScaleBase enables next generation applications to respond to database capacity planning challenges with the best strategy available – scale-out.  This match capacity management strategy is made available by virtualizing the overall database infrastructure and meeting demand when it arrives.