> For example, a recruiter I know will ask a tech candidate "what is 20% of 20,000?" A significant percentage cannot answer the question. Some even cry. It's shocking.
During our interview, we ask candidates to design a history system. The key is to realize that our database is only 8Gb, and storing a year of updates is only 160Gb, so $2pm in AWS. Once there, a simple DB table suits, no need to set up Amazon S3.
So we ask them for the multiplication. First we give them the data, and if they don’t do the calculation, we nudge them, then we ask them, then we write the multipliers for them, then we take the calculator out and write the result for them.
Those are Masters degrees. They can’t even do calculations, let alone getting it right, because 500MB x 200 days a year = a few petabytes apparently. And after that, they’re exhausted, it’s impossible to ask them the rest of the questions like “So is it worth worrying about a Rube Goldberg machine when you’re in for $2 of AWS costs?”.
Honestly, after ~13y in this, I only know a handful of items from the famous latency table, notably those I've used a lot (mutexes cost 25ns, is only 1/4th of main memory reference tho, then disk seek is x100K of that). I'm "DevOps" (and titular variants thereof) in most of my resume.
That said, I'm not above your bar as each cloud provider have their own pricing model. I'm not even above your bar for AWS---which I've used the past six years---just for the sheer diversity of their offerings, not to mention regional variations. I know how EC2 servers are priced relative to each other but when we include ECS, DynamoDB, Lambda, etc., I'm gonna need a cheat sheet.
Out of curiosity what do you find wrong in the s3 solution? This is a data volume that rdbms can manage, but are you looking specifically for the engineer to say something like “I’ll maintain a Write Ahead Log in the database”
It’s just that it’s easier to pull if it’s in the same db as everything else. The S3 solution is perfectly ok and 10x cheaper (.20$ pm instead of 2$), but the difficulty is, now you need to do a REST call to S3, and if you want the history per user or per day or per object, then you need to design all sorts of metadata to be able to fetch the right objects.
During our interview, we ask candidates to design a history system. The key is to realize that our database is only 8Gb, and storing a year of updates is only 160Gb, so $2pm in AWS. Once there, a simple DB table suits, no need to set up Amazon S3.
So we ask them for the multiplication. First we give them the data, and if they don’t do the calculation, we nudge them, then we ask them, then we write the multipliers for them, then we take the calculator out and write the result for them.
Those are Masters degrees. They can’t even do calculations, let alone getting it right, because 500MB x 200 days a year = a few petabytes apparently. And after that, they’re exhausted, it’s impossible to ask them the rest of the questions like “So is it worth worrying about a Rube Goldberg machine when you’re in for $2 of AWS costs?”.