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Pinterest on AWS

Pinterest is a visual discovery engine that hosts billions of images for over 450 million users to explore, save, and share as “Pins” to personalized digital inspiration boards. Born in the Amazon Web Services (AWS) Cloud, Pinterest can scale processing, storage, and analysis of its rapidly increasing data, all while reducing infrastructure management and focusing on innovation. Using compute solutions from AWS, Pinterest migrated its iOS continuous integration and continuous delivery (CI/CD) pipeline from on-premises to reduce build failures by over 80 percent. Pinterest also uses machine learning (ML) to power its visual search tool Pinterest Lens that can recognize over 2.5 billion objects and match them to products. Today, Pinterest’s exabyte data platform runs entirely on AWS, scaling log search and analytics to over 1.7TB while reducing operations costs by 30%.

Pinterest's Cloud Journey on AWS

Pinterest's Cloud Journey on AWS
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Storage

Using reliable, scalable, secure storage to accelerate innovation

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Data Solutions

Keeping data secure and unlocking its value at scale

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Machine Learning

Innovating faster with comprehensive AI and ML services

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Migration

Building efficiencies in the cloud after migration

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Cost Optimization

Taking control of costs and continuously optimizing spend

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Security

Building secure and compliant cloud-based solutions

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Sustainability

Advancing sustainability goals

  • Storage
  • 2022

    Build With Me – Pinterest and AWS

    Learn how Ambud Sharma, tech lead and engineering manager at Pinterest, discovered his passion for tech and how his research in distributor systems eventually led him toward building them from scratch. Ambud also explains how Amazon Simple Storage Service (Amazon S3) has been foundational for some of Pinterest's work, describing it as a game changer for its on-going work.

    2022

    How Pinterest Uses AWS to Create a System to Speed Up Development Times

    Looking to enable its users while deploying analytic tools, Pinterest identified that those users should have permission in order to access the data. Pinterest used Amazon S3 and AWS Identity and Access Management (IAM) to create a fine grain access control system to ensure the correct user permissions were in place which, in return, improved development time for the internal users.

    Read the Pinterest case study »

    2021

    How Pinterest Worked with AWS to Create a New Way to Manage Data Access

    With thousands of engineers and developers working on its platform, Pinterest needed to restrict data access to specific users and processes, turning to AWS for help building a solution. Learn about the collaboration between Pinterest and AWS to develop the scalable and secure Fine Grain Access Control (FGAC) system for Pinterest’s data on Amazon S3 and how FGAC helps Pinterest amplify underrepresented creators.

    Read the data access blog »

    2021

    How Pinterest Uses Amazon S3 Glacier Deep Archive to Manage Storage for its Visual Discovery Engine

    As a large-scale user of Amazon S3, Pinterest stores billions of objects and nearly an exabyte of data across multiple AWS Regions. Learn how Pinterest uses Amazon S3 Lifecycle to assign data to optimal Amazon S3 storage class assignments, helping meet large-scale cost goals and maximize storage efficiency.

    Read the Amazon S3 blog »

    2021

    Tips for Effective Innovation Collaboration from Pinterest and AWS

    Keith Regier, Pinterest engineering manager, and Doug Youd, AWS senior solutions architect, share six collaboration tips gleaned from their experience working together to build Pinterest’s FGAC system. Discover actionable insights, including how to clearly define a problem, why even “bad” ideas can be useful, and what AWS can do to help customers like Pinterest develop solutions to tough technical challenges.

    Read the innovation tips blog »


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    As a visually driven platform, Pinterest relies heavily on the speed and quality of images. But, the text behind those images is just as important as it provides context and makes Pins actionable for our 200 million active 'Pinners.' By working with the Amazon Rekognition Text in Image feature, we can better extract the rich text captured in images at scale and with low latency for the millions of Pins stored in Amazon S3."

    Vanja Josifovski
    Chief Technology Officer, Pinterest

  • Data Solutions
  • 2022

    How Pinterest Engaged with AWS Proserve to Ensure Pinners have Always-On Access to Its Platform

    Growing rapidly with large amounts of data, Pinterest identified the need to establish a disaster recovery plan. With existing solutions already on AWS, Pinterest engaged with AWS Professional Services to build on top of those solutions and take its nearly exabyte of data, version it, and distribute it regionally.

    Read the AWS Proserve case study »

  • Machine Learning
  • 2022

    Pinterest Lens Helps Users Find and Buy the Perfect Item

    Pinterest builds on AWS storage and compute solutions to power the ML engines behind the Lens camera feature on its app, which is used to conduct hundreds of millions of visual searches each month. Learn how Lens can be used as a digital shopping concierge to help users source and purchase items in minutes.

    Read the Lens blog »


    kr_quotemark

    Pinterest is continuously developing machine learning systems to detect objects for visual search and moderation use cases. To accomplish this, we need to label millions of images to generate the required training datasets. Pinterest has an existing labeling platform that has integrated Amazon services like Amazon Mechanical Turk. We were excited to explore using SageMaker Ground Truth to extend this platform to support bounding box labeling tasks. We found SageMaker Ground Truth provides a simple, streamlined interface to kick off labeling jobs."

    Veronica Mapes
    Technical Program Manager, Pinterest


    2022

    AWS is How: Baby Sister

    When there is a new baby on the way, you can expect a lot of changes. Luckily thanks to companies using AWS as their cloud platform those changes only make things better.

    2018

    Deep Dive on Amazon Rekognition, featuring Pinterest

    Learn how Pinterest can easily add intelligent image and video analysis to applications using Amazon Rekognition in order to automate manual workflows, enhance creativity, and provide more personalized customer experiences.

  • Migration
  • 2021

    Pinterest Improves iOS Build Pipeline Reliability by 80.5% Using Amazon EC2 Mac Instances

    In this case study, learn how Pinterest migrated its continuous integration and continuous delivery (CI/CD) pipeline for iOS applications from on-premises computers to Amazon Elastic Compute Cloud (Amazon EC2) Mac Instances. On AWS, Pinterest developers can now seamlessly provision access to macOS compute environments in the cloud, reducing machine-related build failures by 80.5 percent and improving development speeds by 18.4 percent.

    Read the Amazon EC2 case study »

  • Cost Optimization
  • 2020

    Pinterest Scales Daily Log Search and Analytics from 500 GB to 1.7 TB, Reduces Costs by 30% on Amazon OpenSearch Service

    Read how Pinterest migrated its log and search analytics workloads from self-managed and third-party Elasticsearch tools to Amazon OpenSearch Service. Following the migration, Pinterest scaled its daily data-ingestion capabilities from 500 GB to 1.7 TB in only 1 year while reducing operational costs by 30 percent, improving data security, and increasing engineer productivity.

    Read the cost optimization case study »

  • Security
  • 2022

    Scalable Access Control with STS Token Vending

    In this video, Keith Regier, engineering manager at Pinterest, talks about the scalable access control solution for clusters of Amazon EC2 instances that need access to data in Amazon S3. Learn how Pinterest built a token vending service using AWS Secure Token Service (STS) that helps to bridge its internal concept of users and authentication to managed policies and AWS Identity and Access Management (IAM).


    kr_quotemark

    At Pinterest we use Amazon Elastic Container Registry (Amazon ECR) for managing our Docker container images. We use Amazon ECR’s image scanning feature to help us improve security of our container images. Amazon ECR scans images for a broad range of operating system vulnerabilities and lets us build tools to act on the results.”

    Cedric Staub
    Engineering Manager, Pinterest

  • Sustainability
  • 2022

    Sustainability and AWS Silicon

    Learn how sustainability is integrated into Pinterest’s AWS architecture decisions and how AWS continues to innovate on chip design as the organization works toward Amazon’s goal of achieving net-zero carbon by 2040.

About Pinterest

Pinterest is a visual-discovery platform and social commerce network with a mission to inspire. Building on AWS storage and compute solutions, Pinterest uses sophisticated machine learning engines to deliver personalized content to its users.