A Brief History of Price Update (Part 2)

Reading Time: 7 minutes

Here we go again.
This is the second episode of our docuseries about how we are managing retailers’ data for our beloved customers.
If you did not read our previous post about this topic, you should spend a few minutes catching up on it.
With this part, we would like to introduce the hidden aspect of our product and I promise, it is not a buzzword: Machine Learning.
In the following paragraphs, we are going to show new technical improvements and the analytics aspects under the hood.

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Accelerate, the science of DevOps

Reading Time: 4 minutes
DISCLAIMER: this article is the transcription of an internal talk.
You can find the presentation here.
In Everli we have recurring internal moments that we use for sharing knowledge.
We are going to integrate the key points of the book we’re reviewing as we move forward and then we’ll share our learnings and outcomes.

Today I’d like to talk about one of the most interesting and educational books that I’ve recently read.

This book is Accelerate, the Science of Dev Ops and I liked it a lot for mainly three reasons:

  • it investigates the connection between software performance and business performance, a topic I always found very interesting and I consider crucial
  • it is highly practical and not too much philosophical: there’s a bunch of concrete actions and suggestions to implement
  • there’s a lot of science behind it: the rigorous mathematical approach has been one of the most appreciated aspects by the community

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A Brief History of Price Update.

Reading Time: 6 minutes

Hold onto your seats; I am going to guide you around our brief history of the price updating process.
Prices must be updated every day, following our Retailers procedures to provide the best experience to our customers.
If you think it should be a simple procedure, consisting of just updating the right record and go on with the next one, I totally agree with you!

When we were in the start-up phase back in the days it was that simple, but soon we had to forget about doing it this easily when we had to scale it up from a few thousand updates to millions.
In the next paragraphs, I will show you the evolutions of this process during the years.

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How we handled the spike of more than 4k% new users in a week.

Reading Time: 7 minutes

Covid-19 changed and is changing everything.
From customer behaviour to customer spend, no one could have expected this.
Our servers neither.
This post would like to be a simple overview of what we did to maintain our website and apps reliable during this time.
And yes, you have read properly, how we kept the infrastructure responsive while serving more than 4000% new users (and of course the previous one) plus a few DoS attacks.

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