Recently I was at a community session talking to a bunch of computer science students about databases and the type of work I have been doing lately in consulting. I wanted to talk about Performance tuning and why it is critical to understand the basics. Some of the fundamental concepts I have learnt in my college days are still helping me solve some of the complex problems I do at consulting. With that in mind, I started my talk about some of the recent assignments and how I have been troubleshooting performance for both SQL Server on a VM and even SQL Server as a service on Azure. It was about 10 mins into the talk that I realized something was totally wrong, I could see blank faces just like when a professor teaches a complex topic. I have been there and could see the reaction. I said I need a glass of water and paused. I asked one of the students to what was going on – He said, “You mentioned the word ‘Azure’ close to 4-5 times now in the past 3 minutes. Can you tell us what Azure is? Is this a new Database in the industry?”
The cloud phenomenon is no more a dream for many, but a reality for several customers I have been working with. Many of my customers are looking for guidance and from time to time I get an opportunity to have some deep constructive discussions. These discussions can range from should I be going to cloud or not, is this app cloud ready, can we do a lift-shift of this application directly to some cloud player etc. Though each of these discussions lead from one point to another, there is a lot of profiling I do with customers. In this blog, I want to talk about a conversation I had with one of my customers who was evaluating cloud for one of his applications. Let us see a Cloud Consulting Pre-Engagement Questionnaire.
Many application workloads are characterized by resource use that varies over time. Usage peaks can vary depending on the time of the day, week, or month, and outside events. Even a big sport game or an online sale can bring usage spikes. With traditional, on-premises technologies, IT departments typically provisioned enough capacity to manage worst-case scenarios. This approach to scalability can leave a significant amount of underutilized resources in the data centers, most of the time—and inefficiency that can impact overall costs. Cloud computing promises answers to such inefficiencies. In the cloud, you can balance costs and performance by deploying new resources when needed and shrinking them during slack periods. This elastic approach matches demand and capacity.
In yesterday’s blog post we learned the importance of the NewSQL. In this article we will understand the role of Cloud Computing in Big Data Story