The Evolution of Support: From Fixed Phrases to Conversation At Yelp, delivering responsive and accurate customer support is a core priority. For years, our legacy Customer Success (CS) Chatbot provided support by guiding users through a static support experience. Users either navigated a 2-step menu tree or typed a query that was matched against a fixed set of phrases to…
Yelp Engineering
https://engineeringblog.yelp.com/ · 10 posts · history since 2025 · active
27 May
21 May
Introduction In large analytics environments, data teams often struggle to answer deceptively simple questions, like who their stakeholders are and how their data is being used. At Yelp, we address this by visualizing access patterns, plotting time-based partition key values against access event timestamps. These visualizations reveal distinct usage signatures – ad hoc queries, daily batch jobs, and periodic backfills…
20 May
Over the years, Webpack has remained the bundler of choice for many JS projects, including here at Yelp. While it has served us well, its speed has increasingly become a bottleneck as our monorepo continues to grow. Fortunately, a bunch of new build tools (Vite, Parcel, Rspack, etc.) have emerged in recent years. Each of these tools promises different ways…
22 Apr
If you’ve read our earlier post, you already know about CHAOS—the server-driven UI (SDUI) framework we built at Yelp that powers our dynamic views. Until now, we’ve explored its architecture, backend implementation, and component model. In this post, we’ll dive into how we integrated CHAOS with Yelp’s cross-platform design system, Cookbook, and the auto-generated bridge library, Konbini. Introduction to Cookbook…
7 Apr
The Database Reliability Engineering team at Yelp seamlessly upgraded more than a thousand Cassandra nodes with zero downtime. This post takes you behind the scenes of our upgrade strategy, from planning sessions to flawless rollouts. Background Motivation Apache Cassandra is a distributed wide-column NoSQL datastore and is used widely at Yelp for storing both primary and derived data. Yelp orchestrates…
27 Mar
Introduction Users have access to a wealth of information on Yelp business pages – from reviews and photos to structured information, menus, and Ask the Community feature on the business page, a single business page can be an ocean of content. At the same time, user expectations have evolved: people now expect immediate, direct answers. Sifting through dozens of reviews…
2 Feb
Introduction Modern advertising platforms are fast-paced and interconnected: even small adjustments can have ripple effects on how ads are shown, how budgets are spent, and the value advertisers get from their ad spend. At Yelp, Ad Budget Allocation means splitting each campaign’s spend between on‑platform inventory (our website, mobile site, and app) and off‑platform inventory (the Yelp Ad Network). We…
26 Sept 2025
Introduction Yelp heavily relies on Amazon S3 (Simple Storage Service) to store a wide variety of data, from images, logs, database backups, and more. Since data is stored on the cloud, we need to carefully manage how this data is accessed, secured, and eventually deleted—both to control costs and uphold high standards of security and compliance. One of the core…
8 Jul 2025
A little while ago, we published a blog post on CHAOS: Yelp’s Unified Framework for Server-Driven UI. We strongly recommend reading that post first to gain a solid understanding of SDUI and the goals of CHAOS. This post builds on those concepts to delve into the inner workings of the CHAOS backend and how it generates server-driven content. To briefly…
27 May 2025
Background As described in the second blog post of Revenue Automation series, Revenue Data Pipeline processes a large amount of data via complex logic transformations to recognize revenue. Thus, developing a robust production testing and integration strategy was essential to the success of this project phase. The status quo testing process utilized the Redshift Connector for data synchronization once the…