One of the key elements in the development of robust Database as a Service (DBaaS) is the ability to gauge its successes and failures. After all, if you don’t know what’s working and what’s not, and why, then it becomes impossible to capitalize on strong points and shore up its weaknesses. In this post, I will explore how enterprises are employing Database as a Service metrics today to measure success.

The first step in assessing the efficacy of your new service is to have a thorough understanding of what you want to do with it. You don’t judge an airplane a failure because it can’t fly underwater and you don’t scrap a DBaaS architecture because it doesn’t load balance your servers.

Of course, organizations have all kinds of reasons to deploy DBaaS, from implementing full cloud-based application suites to reducing the prevalence of shadow IT, but it is fair to say that cost reduction is a pretty universal criteria. On one level, it should be relatively easy to gauge the cost differences between DBaaS and traditional software licensing: you simply add up the licensing cost plus hardware, middleware, personnel and related expenses for database support and compare them to the monthly cost of a service-based approach. For kicks, you can even see how those costs are affected by scale, load characteristics, speed and other performance-related measures.

Costs are not the only measure of value, however. Security risk is a key aspect that should not be overlooked, and in fact is one of the primary inhibitors to the adoption of public DBaaS services and infrastructure, particularly at large enterprises. The fact remains, however, that by and large, public resources are no more or less secure than private data centers, and in fact are believed by many experts to be more secure because the provider has a greater incentive (profits) to implement cutting-edge security products than the enterprise, which tends to view all of IT as a cost center.

Then there are issues like data migration, interoperability with legacy and other cloud-based systems, governance and a host of other operational elements that can greatly enhance or inhibit database operations.

Ultimately, however, a successful DBaaS deployment will produce the greatest impact on the user experience. If DBAs, data analysts, Dev/Ops professionals and other stakeholders achieve greater productivity through DBaaS, then it can generally be chalked up as a win. Database as a Service metrics for these kinds of parameters may be a little trickier to master, however. How, exactly, does one directly measure performance? And how should the enterprise weigh the possibility of opening up new market opportunities, and perhaps even entirely new business models, once database and analytics applications are freed from the constraints of legacy data infrastructure?

Naturally, all of this will require the enterprise to undertake a thorough analysis of its own data operations and business processes to determine if the DBaaS platform that has been deployed is hitting on all cylinders. Fortunately, DBaaS users have ready access to a scalable, flexible database service capable of supporting such a high level of analytics.

One of the first tasks assigned to a DBaaS platform, then, should be to prove its own worth to the enterprise. You can also check out the recent State of Database as a Service survey to learn more about what Database as a Service metrics business are using to measure the success of DBaaS projects.

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