ScaleBase: The Cloud Native Database Scalability

scalebase-logo_mdI’ve been working in the cloud industry for nearly the past decade, and can say, without a doubt, that Database as a Service is one of the most interesting and challenging domains I’ve encountered.
In 2005, I ran a software developers team that provided LAMP Software as a Service for enterprises; therefore, I became very familiar with the challenges of carrying out MySQL work for large scale demand. These challenges are further augmented when dealing with web applications that have exponential transaction rates and concurrent user growth.

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Consumption, Utilization and Elasticity: Cloud Basics

newvem cloud utilization heatmap
Cloud Utilization Heatmap by Newvem

Lets start with a basic scenario where there is a sudden peak in the demand for an application service as the amount of clients’ requests increase. This event leads to a direct and immediate impact on the load placed on the web servers that host the service. In the traditional world, the number of servers is fixed, therefore an overload adversely affects the application performance and the service may slow down or even be terminated. The IT team would want to restore the environment functionality and bring the service up as soon as possible. The immediate impact  of such an event on the business can be devastating. Starting with this simple understanding, we can move into the world of cloud computing use including resources consumption, while relating to the key differences between the traditional data center and today’s cloud technologies.

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Scale IT and Make Your Cloud Capacity Meets Demand

Capacity vs demandThe practice of shaping demand to fit the available resources can be found for example in transportation businesses, where airlines charges more for their service when demand is high and charge less to encourage more demand. In the real-time and interactive on-line world,  the challenge is to ensure that capacity meets demand.
The following diagram shows 3 cases of over capacity, under capacity and on demand capacity, which the latter can be achieved only by taking an advantage of the cloud elasticity.
IT systems or applications have capacity limitations. Sometimes a new SaaS web application works well in its first phase on the air as it serves from tens up to a maximum of several hundreds of users. In this stage, there will be no need to worry about a scalable hosting environment and paying a flat fee for the fixed computing resources makes sense. Over time as the SaaS product matures, the amount of users increases and the overall usage goes up. The SaaS vendor will have to deal with these scalability challenges and hopefully without the service suffering from poor performance. So what are the options to maintain the application’s availability with the new demands? Or in other word how do we scale it?

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