Riskified Technology

Using random data generation to improve your testing methodologies

A lot of data is priceless for data scientists but may create noise, so to clean it up, look for answers in the system’s architecture.

Automatic type class derivation can help you reduce code complexity and increase productivity. Learn how to do it correctly and cleanly

The process of transitioning from monolith to microservices and how it’s affects the R&D organization structure

How to tackle fraudsters and how R packages help gradually transition from analyses to production-ready code

Stream Processing & Probabilistic Data Structures are a match made in heaven — learn why with a step-by-step tutorial

Listen to Drorit on the transition from Batch to Stream processing, and which of the two approaches is most suitable for your organization

Listen to Oded on the advantages of Kubernetes, how to implement it correctly, and how it serves us in our R&D organization’s growth

Listen to Karin on how it’s like to manage a growing R&D organization and create a technological culture.

How did our Dev team manage to handle the growth of our main codebase by setting domain boundaries

How we build our new Machine Learning platform in order to hand massive amounts of data, and shorten the way to production

What is our responsibility when hostile organizations are taking advantage of vulnerable communities?

The changes we made to our clusters to gain the needed elasticity, control cost and provide a safe and available environment to run on.

Why we decided to transform our Spark applications to run over Kubernetes by using the spark-on-k8s-operator, the pros, cons and…