Engineering Blog

TL;DR We simulated several kinds of workloads and measured memory and CPU consumption on five bare metal instances.

Teads is passionate about contributing to the feminization of IT jobs. In 2019, we launched our first Engineering Camp, a two-day training…

A benchmark of available solutions

A practical attempt to estimate CO2 emissions for our software platform. In short, we discovered that it’s a fascinating but complex topic

Breaking changes and expected improvements: a production point of view

A detailed analysis of 3 JavaScript timeout strategies and how they perform in thousands of web contexts.

Building great software requires software craftsmanship skills but successful software companies have something in common on top of that …

Can you trust every browser to generate globally unique identifiers at scale? At Teads, we have tried, and the answer is yes…

3 actionable measures to lower your EMR bills: Spot instances, EMR pricing on bigger EC2 instances and idle cluster detection.

Another real-life use case and methods to consider when optimizing a Spark job, this time using User Defined Aggregation Functions (UDAF).

In this new article, let’s go to our Engineering hub in Bucharest to ask Andreea about her journey to Teads, her team and projects.

In this third article of our interview series, we ask Hugo about his journey to Teads and what he loves about working here.

In this second article of our interview series, we ask Marion about her journey to Teads and what she loves about working here.

In the first article of our new interview series called “Career Takeoff”, we showcase a young talent working at Teads.

This second edition brought together nearly 500 participants (sold-out) to enjoy 50 conferences and workshops over 5 tracks.

Our tormented journey moving from a physical server to a cloud based, highly available and scalable setup

Building a great interview process is quite tricky, there is no magic playbook for that. Here is some feedback on ours.

Spark from the trenches — Part III

How we use and abuse Redshift to serve our data

Troubleshooting tricks and external data source management