Google Professional Cloud Architect Study Guide

Chapter 4. Design Principles: Business Use Cases and Trade-Offs

I was asked one time to help an organization troubleshoot cost overruns with BigQuery. BigQuery is a very successful tool in the Google Cloud space, and it does its job, running SQL queries over big tables of information, really well. The company asking for help was thrilled with the performance they were seeing, so BigQuery was meeting all their goals there, but it was doing so at a higher cost point than my client would have preferred.

When I came in, my first move was to get access to the billing information. I was curious about where my client’s BigQuery dollars were going. It didn’t take me long before I saw a major suspect. The company was spending $5,000+ a month on streaming data inserts.

The next day, I had a sit-down with the client, and I said, “I see you’re doing a lot of streaming inserts into BigQuery.”

“Oh yeah, our old system was so slow getting in new data. It always took days before we had anything useful.”

“What’s the business use case for the data?” Lots of staring and blinking. “What business problem is being solved with the data you are streaming into this table?” More blinking and staring. “How about this: who decided the data needed to be streamed in real time into BigQuery?”

“Oh, yeah, that was the cloud architect?”

“Could I speak to them?”

I’ll save you the rest of my tracking the answer down, but suffice it to say, the cloud architect was told by the business analytics team that the data, ...