Success vs. Scalability: Why your biggest success might also be your biggest disaster

There is a scenario I have seen again and again. A company has developed a nice piece of software which many clients are running with happily. Then along comes a new client, the biggest client to date by far. Celebrations abound, plans are made to expand the business and the execs are wringing their hands with glee at the anticipated new revenue.

But then soon after go-live things start to go wrong. The application just doesn’t cope well with what are unprecedented loads. The database is under strain and even throwing more power at at – where that is an option – isn’t helping as much as would be hoped.

This is often where I get called in. Scalability of database applications is a real issue. Without proactive performance tuning and optimization, most systems will reach a tipping point once a certain load, or size of data is reached.

On the application side it’s often easy, you can scale-out and simply add more application servers. On the database end however, you often have no choice to rely on a single database instance. This is often a point that is used to criticize traditional OLTP databases and people will say you should use NoSQL or rely on things such sharding and eventual consistency. There is definitely a place for those things, but at the same time, speaking mainly from my experience working with SQL Server, there is no realistic load it can’t take as long as the application is designed well, and the database and server are properly tuned.

So how do you identify if you’re going to have a problem before you end up in the middle of a client emergency?

Load testing is one answer. I’ve worked with product teams in this exact circumstance, testing to see if the application and database will scale to the requirements of a new customer. It is hard though. It’s hard to accurately simulate a profile of usage that anticipates how a given client – or all clients – may use your system, and it’s a lot of effort.

The good news though is that you can identify most potential issues within database applications before they become critical ones. Often it’s clearcut; a query is not going to scale well unless it has better indexing to support it, a particular piece of code is going to create a lot of locking as data sizes grow, parallelism settings are not optimal and won’t support optimum performance at scale, the list goes on.

Even when it’s not clear, there’s usually enough information to raise suspicion. Then you can at least target load testing to those specific functions and see how they cope under strain.

This scenario isn’t just limited to new customers. Existing customers can grow over time and usually their databases certainly do. Unless you’re pro-active in identifying those potential issues early then you will reach performance tipping points where clients end up raising Sev 1 issues.

It’s often said that the best DBAs go un-noticed because this is their approach. They’ve identified and solved issues ahead of time before anyone else was even aware of them. The best performance tuning activities are invisible in terms of negative impact, and it’s always great to be able to tell clients you’ve made things better without being asked.

So, have you got a big new client just around the corner, or are your existing clients (or their databases) growing, and you haven’t done any tuning recently (or at all)?

Get in touch and I can perform a Comprehensive SQL Server Healthcheck for you. We’ll identify these sorts of issues, as well as any other hidden dangers that might be lurking around the corner ready to bite. We’ll discuss solutions and I’ll work with your team so they understand the issues in detail. Or if you’re have a need for any other SQL Server consultancy then check out my services page or give me a yell.

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