Learn about how reverse debugging happens at Facebook scale, how Doordash calculates our food delivery ETA for long tail events, how compliance audit can be made easier using tools & ongoing processes, how building trust became an important factor for Yelp in post COVID world, and finally how Walmart scaled their homegrown AB testing tool in mist of 10x traffic.

Welcome to the 9th issue of engineering brew. 

#Debugging #Scale #Facebook

Teams working at companies with crazy scale usually encounter problems that a lot of us will never encounter, or if we do, it will be with different constraints or scale. This post talks about reverse debugging at Facebook. This is how the post starts (spoiler - you will get hooked)


#PredictiveModels #FoodETA #Doordash 

Who knew when the Doordash ETA was calculated, longtail events had so much importance. They can be responsible for churn, and are super hard to predict. In this post authors discuss the problem, why it is important and hard, and how Doordash approaches the solution. 


#Compliance #AWS #Tools

If you have ever been involved or will be involved with the company's annual compliance audit, this is a post for you. Author talks about tools and patterns that they used for building a continuous compliance stack for AWS. 


#Trust #COVID #Yelp

This post talks about how small businesses went on to building trust with their local communities on the Yelp platform. Yelp's engineering team stepped up in solving the problem and also to make sure that the platform users were safe. Read how they came up with standard levels of trust and a way to calculate it with new parameters.  


#Ecommerce #Scale #Walmart

The author talks about how traffic is 10x’ed since COVID and how they scaled and moved the inhouse AB testing platform. The post gets into the weeds of different problems and their solutions around Kafka & KairosDB (a wrapper around Cassandra). 


Thank you for reading.

Happy Friday!