Reading Time: 6 minutes
Or: How to kill off the if branch.
Everli has changed a lot in the past years! Not only by growth in raw numbers, but structurally.
- From just Italy into multiple countries.
- New kinds of business partnerships and customer relationships.
- New types of retailers.
(And that’s not even mentioning external changes like new government regulations)
Feature Creep Can’t Be Stopped
So imagine you’ve got some code. It’s readable, it met all the requirements, very elegant!
Continue reading “A Strategy for Scalable Business Logic”
”Okay code, now meet the real world.”
Reading Time: 5 minutes
Here we go again.
This is the third episode of our series on how we are ingesting retailers’ data for our beloved customers.
If you did not read our previous post about this topic, consider spending a few minutes catching up on it.
In the following paragraphs, we will show you how our new process to update the assortment of our stores works and our journey to get there.
From the previous episode
In the previous episode, we showed you how we reached coordination in our price update flow. We achieved it by the mean of a semaphore stored on Redis: each time it gets accessed, we decrease its value. Once it reaches 0, the next stage of our pipeline begins.
We also covered our Conversion Optimizer, a machine learning algorithm.
As soon as prices are updated, the next step of our pipeline can start.
Continue reading “A Brief History of Price Updates (Part 3)”