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Lightbend > Case Studies > Sharethrough Chooses Scala to Build Industry’s First Native Ad Management System

Sharethrough Chooses Scala to Build Industry’s First Native Ad Management System

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Customer Company Size
Mid-size Company
Region
  • America
Country
  • United States
Product
  • Typesafe Platform
  • Twitter's Finagle
  • Typesafe's Play Framework
  • Akka Framework
Tech Stack
  • Scala
  • JRuby
  • Java
  • Sinatra
  • Heroku
Implementation Scale
  • Enterprise-wide Deployment
Impact Metrics
  • Innovation Output
  • Productivity Improvements
Technology Category
  • Application Infrastructure & Middleware - API Integration & Management
  • Platform as a Service (PaaS) - Connectivity Platforms
  • Analytics & Modeling - Predictive Analytics
Applicable Functions
  • Business Operation
  • Product Research & Development
Use Cases
  • Digital Thread
  • Edge Computing & Edge Intelligence
Services
  • Software Design & Engineering Services
  • System Integration
About The Customer
Sharethrough is a technology platform that powers in-feed 'native' ad placements, enabling publishers to manage and sell native ads on web and mobile. The company believes the future of advertising will be about thoughtfully integrating brand content on sites people love to visit, rather than using traditional display advertising formats like cookie-cutter boxes, banners, or auto-playing videos. Founded in the heart of Silicon Valley at Stanford University, Sharethrough has expanded across the United States with offices in San Francisco, New York, and Chicago. The team is composed of professionals with deep experience across the advertising, technology, media, and creative industries. Sharethrough's mission is to replace underperforming traditional display advertising with non-interruptive, seamlessly integrated advertising formats.
The Challenge
Prior to 2012, Sharethrough's advertising platform relied on an integration between their end-to-end campaign trafficking and analytics platform and a third-party ad server. To realize their vision of powering native advertising across the open web, they needed to build their own ad server as no existing solution supported the targeting, templating, and analytics capabilities they required. Sharethrough started small, focusing on building early pieces of the core templating and targeting technology as a simple, horizontally scalable trafficking tool in Sinatra, deployed on Heroku. As the platform quickly gained traction, they realized that a move from Sinatra (and Heroku) was going to happen sooner than originally planned. Given the significant performance requirements and the critical portion of their infrastructure being in the service layer, Sharethrough decided to examine other languages and frameworks.
The Solution
In 2012, Sharethrough began evaluating languages and architectures for their next-generation service stack. They set objectives around performance, stability, and extensibility, aiming for 99% of transactions to return in under 50ms. Sharethrough needed efficient algorithms that scaled linearly with the content quantity, facilitating low latency and reducing infrastructure costs. They decided to build the next-generation architecture on the JVM, considering JRuby, Scala, and Java. Scala was chosen due to its support for both functional and object-oriented paradigms, expressiveness, and lack of boilerplate code. Sharethrough's architecture focused on extracting small, single-concern services using Twitter's Finagle and Typesafe's Play and Akka Frameworks. The front-end ad server was built using Finagle, while backend services used a combination of Finagle and Play. Akka was used for background processes, such as the automated creative optimizer.
Operational Impact
  • Sharethrough successfully built a native advertising platform that integrates brand content seamlessly on websites.
  • The platform supports efficient algorithms that scale linearly with content quantity, facilitating low latency.
  • The architecture allows for rapid deployment of new algorithms, capturing learnings quickly.
  • The service-oriented architecture isolates each unit of work, allowing parallel efforts and reducing the need for a dedicated QA team.
Quantitative Benefit
  • 99th percentile latency of less than 50ms.

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