People Behind the Product: Meet Rahim Daya, Head of International Product & Toronto Lead

Rahim Daya, Toronto-native and Pinployee of nearly 4 years, leads Pinterest’s International Product as well as the Tech team in Toronto. Ahead of our virtual Pinterest Engineering: Meet the Toronto Team event, get to know Rahim and learn more about…

Improving the Quality of Recommended Pins with Lightweight Ranking

The Pinterest corpus is composed of billions of Pins, however, each Pinner only sees a small subset based on their interests when…

A one year PWA retrospective

The idea of building a “Progressive Web App” (PWA) is not new, but its definition has changed with the emergence of key technologies like service workers. Now it’s finally possible to build great experiences in a mobile browser. Being an early adopter can…

Real-time experiment analytics at Pinterest using Apache Flink

At Pinterest, we run thousands of experiments every day, and rely mostly on daily metrics to evaluate performance. The daily pipelines can take 10+ hours to run and sometimes are delayed, which has created some inconvenience in verifying the setup of…

Secret management in multi-tenant environments

Knox, Pinterest’s open-source secret management service, now supports SPIFFE x509 identity documents as an authentication method. This update enables Knox to manage secrets in multi-tenant environments like Kubernetes. Knox is widely used across Pinterest’s infrastructure to provision secrets into production systems. In an…

How We Protect Pinners’ Passwords

Aalaa Satti | Software Engineer Amine Kamel | Head of Production Security At Pinterest, one method by which we ensure account security is through protecting Pinners’ passwords. Passwords can be problematic for a variety of reasons, including the fact that people tend to reuse their…

How switching our domain structure unlocked international growth

More than half of the 200 million monthly active users on Pinterest use our app outside the U.S. As we continue to make Pinterest even better for our global users, we moved our traffic to country code top-level domains (ccTLDs). An example of this…

Shallow Mirror

Henry Cai | Software Engineer, Data Engineering Pinterest uses Kafka as the backbone for data transportation. As a part of our infrastructure, Kafka MirrorMaker v1 is used to replicate traffic among different Kafka clusters spread across multiple regions. Kafka MirrorMaker is a powerful tool to replicate/aggregate data between different Kafka…

Trusting Metrics at Pinterest

Pinterest, like many tech companies, relies heavily on data to help inform decisions and power machine learning. This strategy fundamentally depends on the data being accurate. Over the years we’ve worked to improve the processes behind trusting core decision-making data and ensure metrics remain accurate. How Data Can Go Wrong …

Pinterest + ktlint = ❤

Ha pasado casi un año desde que la base de código Android de Pinterest se convirtió en la prioridad de Kotlin, y aproximadamente dos años desde que adoptamos ktlint para el formato y lint de Kotlin. Hoy, compartimos que Pinterest se…

En Pinterest desarrollamos compilaciones para iOS rápidas y confiables

En Pinterest nos enfocamos en ayudar a las personas a descubrir ideas inspiradoras, desde recetas para una cena, hasta productos de estilo y para el hogar que comprar y lugares a los que viajar. Para ello, es…

Pre-Submit Integration Tests For Ads-Serving

Introduction & Background The ads-serving platform is the highest-scale, highest-complexity, and highest-velocity recommendation service at Pinterest. Our ads business is growing and expanding, and the ads engineering team is iterating quickly to continue to improve the system. Therefore, it is vital to keep the system healthy, in order…

Hybrid Search: Building a textual and visual discovery experience at Pinterest

As a visual discovery engine, Pinterest helps you discover ideas even when you don’t know what you’re looking for, or have the words to describe it. Using a mix of technology (including visual search) and community input (thanks to the 175B+ Pins…

Introducing Pinqueue3.0, Pinterest’s next-gen content moderation platform

In 2016, we reached a milestone of launching Pinqueue2.0, which has since become the go-to content moderation tool for the engineering, community, and data science teams. One of our top priorities at Pinterest is fostering a safe and trustworthy experience for all…

How we built rearranging Pins

Listening to user feedback is essential to building a product Pinners love and use to discover and save ideas every day. Often, their feature requests present interesting technical challenges for our engineers. For example, today we launched the ability to…

Building a dynamic and responsive Pinterest

In 2015, the majority of content on Pinterest was pregenerated for users prior to login. It was stored statically in HBase and served directly upon entering the service. (More details can be found in the blog post Building a smarter home feed.) …

Using graph algorithms to optimize Kafka operations, Part 1

Pinterest uses Kafka across the board for data movement. The Logging Platform team alone manages over 3,000 Kafka brokers transporting trillions of messages per day to help bring more than 320 million monthly active Pinners the inspiration to create a life they love. …

Scaling Kubernetes with Assurance at Pinterest

Introduction It has been more than a year since we shared our Kubernetes Journey at Pinterest. Since then, we have delivered many features to facilitate customer adoption, ensure reliability and scalability, and build up operational experience and best practices. In general, Kubernetes platform users gave…

Pin2Interest: A scalable system for content classification

Content understanding is at the core of any great recommendation system. By knowing what each Pin is about, Pinterest can connect Pinners with the most relevant and inspiring content that best matches their interests. Taxonomy of interests The Interest Taxonomy captures popular concepts that appear within Pinterest…

Bottoms-Up: How the Pinterest growth team decentralizes team structure

On the growth team at Pinterest, we describe our structure as “bottoms-up”, meaning ideas and responsibilities flow throughout the team in a way that provides a lot of autonomy to work on the projects each person wants to tackle, across a variety of roles. The…

Powering inclusive search & recommendations with our new visual skin tone model

To truly bring everyone the inspiration to create a life they love, Pinterest is committed to content diversity and to developing inclusive search and recommendation engines…

Building a Kubernetes platform at Pinterest

Why Kubernetes? Over the years, 300 million Pinners have saved more than 200 billion Pins on Pinterest across more than 4 billion boards. To serve this vast user base and content pool…

Privacy Power-Up: Upgrading Pin Links from HTTP to HTTPS

HTTPS should be everywhere. Your website likely runs over HTTPS, giving your users a secure, encrypted connection, but what about all the outbound links? Can you guarantee that they all use HTTPS? In this post, we describe the steps we took…

Looking inside the technology that powers Pinterest

Pinterest began as a small startup, and has grown to a company that serves +175B Pins to +250M people. While we have one of the largest datasets online, we have 600+ engineers, and so technology needs to be accessible for each person to play their part in…

Building interactive email with AMP

AMP (Accelerated Mobile Pages) is an open source technology created by Google to support fast mobile web pages. Over the years, we’ve partnered with Google and adopted AMP technology in our mobile web pages to deliver a faster, more efficient user experience. Most…