3 ms·
While there's arguments on both side for TCO of Cloud, I'll offer one idea - a solution like BigQuery is zero-Ops, lets you scale to thousands of cores in a sec
by vgt 11y ago
While there's arguments on both side for TCO of Cloud, I'll offer one idea - a solution like BigQuery is zero-Ops, lets you scale to thousands of cores in a second, and you pay per-second. This is both cheaper, faster, and easier to use, simply because it breaks many assumptions folks make when doing TCO comparisons:
https://cloud.google.com/blog/big-data/2016/02/understanding-bigquerys-rapid-scaling-and-simple-pricing https://cloud.google.com/blog/big-data/2016/02/understanding...
- api 11y agoFor our app the killer was storage costs. Of course our app is probably different from your app. For us we are doing real-time network testing and diagnostics of a bunch of distributed networks and dumping the data into a series of tables for analysis and diagnostic use. We can also use that data to improve our software in the long term. A lot of data is generated, but if we lose a little bit it won't kill us. The analytics we want to do right now are fairly consistent in terms of load. For this work load the cheapest option by far is to buy a RAID array and warehouse it locally. It can also be backed up very cheaply in Glacier so that if we do lose some we can get it back if we want it. But of course like I said our app is probably not like yours. My point was that you have to do the analysis for your exact specific problem to decide what approach -- cloud or not -- is the best fit.