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…

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…

Ad Metrics Quality and Testing on Mobile

Every day at Pinterest, we help our advertising partners reach Pinners through different ad formats, and we provide them with metrics and analytics on how their ads are performing. Maintaining our partners’ trust and delivering value is critical, so the metrics we expose…

Managing Videos on Android

Video launched on the Pinterest Android app in 2016 with the goal of bringing a seamless video experience to the app. This included the ability to support multiple videos per screen, while dynamically controlling their playback state by automatically pausing them when they’ve scrolled…

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…

Building a Label-Based Enforcement Pipeline for Trust & Safety

As Pinterest grows with increasing numbers of users and businesses, providing a safe and trustworthy experience is one of our top priorities. Every day the platform serves billions of Pins and boards to inspire Pinners. With so many Pins and activity, It can…

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…

PinSage: A new graph convolutional neural network for web-scale recommender systems

Deep learning methods have achieved unprecedented performance on a broad range of machine learning and artificial intelligence tasks like visual recognition, speech recognition and machine translation. However, despite amazing progress, deep learning research has mainly focused on data defined on Euclidean domains, such…

Simplifying web deploys

Over the past six months, Pinterest has moved to a CI/CD model for our API and web layers, which has truly improved agility by reducing time between merge and production. Prior to…

Understanding the product cycle of discovery to purchase on Pinterest

Pinners have always used Pinterest for shopping, as they often come in a planning mindset and are exploring products and…

The Fantastic Fixathon

Engineers at Pinterest are always focused on doing what’s best for the product, but working in a codebase that’s clean, well-maintained, and relatively bug-free transforms engineering tasks from being “just work” to enjoyable opportunities to flex our skills. We’re also enriched as engineers, both technically and otherwise, when we take…

Developing fast & reliable iOS builds at Pinterest (Part one)

At Pinterest we’re focused on helping people discover inspiring ideas, from dinner recipes to try, home and style products to buy, to places to travel. Building the best products for mobile is a critical part of that, with 80% of all Pinners…

La evolución de la búsqueda en Pinterest

This blog article was originally posted in English. To read the English version click here. Cuando Pinterest se lanzó por primera vez, ofrecía una nueva forma de recopilar y organizar ideas de toda la web. Sin embargo, lo que comenzó como un lugar…

Automated cluster management and recovery for Rocksplicator

Rocksplicator at Pinterest Rocksplicator (github) was open sourced by Pinterest one and half years ago. It was designed to solve common problems of building large-scale online stateful data systems on commodity hardware, such as RocksDB replication and request routing. Technical details about how Rocksplicator solves…

Growth engineering meetup

Synopsis of the talks Paid growth @ Airbnb Ganesh Venkataraman discusses the various channels and techniques…

Building a more inclusive way to search

Every day, tens of millions of people search for ideas on Pinterest, whether it’s a recipe to cook for dinner that night or a new hairstyle to try over the weekend. According to a Pinterest study, 70 percent of people use Pinterest to…

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…

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…

How we designed our Continuous Integration System to be more than 50% Faster

Earlier this year, the Engineering Productivity team at Pinterest published a blog called How a one line change decreased our clone times by 99%. In that post, we described how a simple Git configuration sped up clone times in one of our…

Multi-task Learning and Calibration for Utility-based Home Feed Ranking

Home feed is one of the most important surfaces at Pinterest that drives a significant portion of engagement from the more than 400+ million people who visit each month. From a…

Building Expanded Targeting for Pinterest Ads

With more than 300 million people coming to Pinterest each month, Pinterest offers unique opportunities for advertisers to get their products in front of people with commercial intent. Similar to other platforms, Pinterest offers a variety of advertising targeting products¹. Advertisers can…

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. …

Real-time User Signal Serving for Feature Engineering

More than 320 million unique visitors come to Pinterest every month to discover inspiring content, which also gives advertisers a unique opportunity to get their products in front of people with commercial intent. Curation…

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…

Calidad y pruebas de las métricas publicitarias en dispositivos móviles

En Pinterest, todos los días ayudamos a nuestros socios de publicidad a llegar a los usuarios a través de diferentes formatos de anuncios y les ofrecemos métricas y análisis sobre el rendimiento de sus anuncios. Mantener la confianza…