what is the best stack for your next project
People quite often asking me about technology stack, and where to go with next big project. The answer isn’t simple – it depends. Usually, we have couple components which are critical for the whole system. If we are talking about a web-based solution or any API we have to decide about DATABASE, then we have STORAGE, moving on – some BACKEND service language.
Time-based One-time Password Algorithm (TOTP) is an algorithm that computes a one-time password from a shared secret key and the current time. The most popular implementation of this solution is Google Authenticator.
This application that implements TOTP security tokens . Usually is branded as “ Two-step verification {.mw-redirect}” (or 2-Step Verification). Authenticator provides a six- to eight-digit one-time password which users must provide in addition to their username and password to log into various services or other sites.
Google Cloud storage it’s Google answer to [Amazon S3][1] service. As long one of them is very popular 😉 Second wasn’t so successful amongst developers due to quite complex processes around service. Amazon is super simple, and developer friendly – Google… well not so easy. So the questions – why you may consider using GS instead of well documented, and super easy S3. Not many people realise but Google Cloud Storage is actually cheaper . The other reason to use Google Storage is having different provider as a backup solution. Anyway – let’s show how easy is to use GS with existing S3 libraries.
I’m the guy who like to test. Benchmark is my… middle name. You can find dozens articles about speed one or other solution. I mean MongoDB and MySQL . I tried MongoDB couple times, and each time I wasn’t moved by it speed. Got project coming in, when I have to deal with large amount of concurrent connection. It’s not very big, but bigger then casual MySQL load.
So… how did I test – very dump way. Got 2 tables, one around 11k records, second one close to 200k record. Not much. Fields were indexed in both MySQL and MongoDB. And then i run benchmarks. First one had string fields, second one numeric.
