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…

The top Pinterest Engineering blog posts of 2018

The most-read posts of the year Three-day no-meeting schedule for engineers A one year PWA retrospective Supporting React Native How Pinterest runs Kafka at scale How switching our domain structure unlocked international growth PinSage: A new graph convolutional neural network for web-scale recommender systems Looking inside the technology that powers Pinterest Building a more inclusive way to search Building a real-time user action counting system for ads Goku: Building a scalable and high performant time series database system We’ll be back in 2019 with more updates from the team. Happy New Year!

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…

User state-based notification volume optimization

Notifications play an important role in helping Pinterest’s 335M+ monthly active users discover and engage with inspiring content. It’s crucial to send the right number of notifications with high quality content. If we send too few notifications, Pinners might miss out on great opportunities…

Automating Shop The Look on Pinterest

Every day, people come to Pinterest to discover new ideas — and when they find a product they want to buy, it should be easy to purchase it. In home decor specifically, millions of people come to Pinterest to find inspiration. That’s why in 2017…

How ads indexing works at Pinterest

Introduction Ads indexing is a data processing pipeline that builds servable ad documents for the ads delivering stack at Pinterest, including ads targeting, retrieval, ranking and auction. The pipeline converts ad campaigns in the raw format to the servable format via a heavy computational…

Building Pin stats

A few months back, we started building a way for businesses to create and showcase their latest and favorite content on their profiles. We also wanted to make it easier for businesses to understand how their Pins are performing. If a business can…

Fighting spam with Guardian, a real-time analytics and rules engine

As the Trust & Safety team, one of our major responsibilities is protecting Pinners from spam. Without protections, spam could potentially be all over Pinterest since spammers can script and generate activity at a rate much higher than actual users. One of…

Pinterest + ktlint = ❤

It’s been nearly a year since Pinterest’s Android codebase became Kotlin-first, and about two years since we adopted ktlint for Kotlin linting and formatting. Today, we’re sharing that Pinterest has officially taken ownership over the project. Initially, we chose ktlint because of its…

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…

Building board archiving and sorting

Connor Montgomery | Software engineer, Product Engineering A Pinterest tradition we’ve had since our early days is the Make-a-thon, our twist on a hackathon. Make-a-thons bring together employees from different disciplines to build something new. In the past, we’ve had projects range from scaling hacks to AR prototypes to…

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…

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…

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…

GokuL: Extending time series data storage to serve beyond one day

At Pinterest, developers rely heavily on Statsboard to monitor their systems and get alerted when issues happen. Last year, we introduced our time series database (aka Goku) which stores and serves the most recent one day’s…

Geo-blocking media content on Pinterest

Pinterest engineers are tasked with showing Pinners the best ideas related to their interests, which includes taking into account signals like location. As part of these efforts, we built a video and image platform to enable a…

PinnerSage: Multi-Modal User Embedding Framework for Recommendations at Pinterest

As we build a visual discovery engine that powers 2B+ Pins, it’s crucial to understand user interests and preferences in…

Goku: Building a scalable and high performant time series database system

Co-authored by Jinghan Xu, Jian Wang & Tian-Ying Chang, Engineers At Pinterest, developers rely on Statsboard to monitor their systems and discover issues. A reliable and efficient monitoring system is very important for development velocity. Historically, we’ve used OpenTSDB to ingest and…

How we reduced Pinterest’s iOS app size by 30+% / 50MB

We all know app size (download size[1] and local install size[2]) matters, and there is a correlation between app size and customer engagement. Many times, people make decisions about using software based on size, and even pay for bandwidth by the megabyte. Not…

Setting Up Snowflake Secondary Roles with Tableau

At Pinterest, we heavily utilize Tableau for our enterprise analytics. In an effort to secure access of sensitive data to the appropriate business units, we moved the enterprise data into a Snowflake data warehouse. Using Snowflake as a data platform, we can create and manage…

Optimizing Kafka for the cloud

Takeaways Developing locality aware systems and balancing algorithms can help substantially reduce cost Making Kafka Producer and Consumer rack aware helps efficiently route traffic Data-driven engineering decision making is critical to continuously improve systems One of the fundamental principles when operating in the…

How we increased engagement using automatic personalized copy testing

Think about the last time you visited a website. Was there a word that helped draw you in? Now think about how that might be different if you spoke a different language, were a different age or grew up in a different part of…

The Dead Code Society

On June 1, 2018, engineer Chris Lloyd created the #dead-code-society Slack channel to be “a sombre place for remembering [---]-only diffs.” Messages are prefixed by a :tombstone: and include links to diffs that contain only file or line deletions. The channel averages a little over one message per day, but they frequently come in bursts as part of refactoring projects and clean-up efforts. As Pinterest has grown as a company, our software unpinning has grown with it. We have hundreds of software engineers producing thousands of changes per week. The net result is an upward trend in total lines of code with a significant portion of our software having been (re)written in just the last few years. The #dead-code-society has helped balance that trend by celebrating the retirement of code from active service. Retired code remains in source control history to be remembered and consulted, but it no longer occupies a prominent place in our workspaces, build systems, or cognitive periphery. Less is more. Carpe diem.

Faster Creator Content Distribution at Pinterest

At Pinterest, we are committed to building the best experience for creators to reach and inspire new audiences and for Pinners to easily discover the best ideas for them. We believe more diverse Pin formats and an efficient distribution system that builds a…

Detecting image similarity using Spark, LSH and TensorFlow

As a visual platform, the ability to learn from images to understand our content is important. In order to detect near-duplicate images we use the NearDup system, a Spark- and TensorFlow-based pipeline. At the core of the pipeline is a Spark implementation of batch…