How can we as developers, do everything in their power to protect the users of their applications from experiencing ANRs? Let’s find out.
Check out these 7 questions Taboola gathered to better define problems.
Most products don’t have the luxury of retaining users beyond the first session solely on their solid reputations, and in order to do so, we need to optimize for the best user experience possible.
Have you recently launched a cool new feature you spent so much time on? What data do you use to determine the impact of the feature? Take a look at this blog, this may be just for you!
Ted Lasso has some real-life lessons we can all take in. How is this possible? Take a look!
Why is it important to remove underperforming features to improve the product’s key metrics? Find out here.
Is there a way to lower Cost Per Action or increase Conversion Rate? There is! Taboola created the Attentive Audience program, learn more about it here.
We wanted to see if there was a way we could sync our Kubernetes NetworkPolicies dynamically with tools we already use, like Consul and Calico.
Read this article to learn more about what conversions are, how Taboola handle billions of daily events at scale, and how it all presents meaningful data to customers.
Something strange happened while I worked with Kafka. While adding a new consumer from Kafka to one of our services, the service stopped consuming from ALL other existing consumers. As part of my job at Taboola as a team leader on a production team in the Infrastructure group, we’re supposed to remove bottlenecks, not create them. This post will describe how I investigated the issue, explain what I discovered, and share my insights into the whole situation. Some background Before I get into the rest of the story, here’s some background on how we use Kafka at Taboola’s events handling pipeline and why it’s critical to our infrastructure. Taboola’s recommendations appear on tens of thousands of web pages and mobile apps every second. As users engage with the content, multiple events are fired to signal that recommendations are rendered, opened, clicked, and so on. Each event triggers one or more Kafka messages, […]