
DoorDash Engineering Blog
551 FOLLOWERS
The official blog of the DoorDash Engineering team. Learn about high impact projects that power our velocity, reliability, and innovation. DoorDash is a technology company that connects people with the best of their neighborhoods. By building the last-mile logistics infrastructure for local commerce, we're fulfilling our mission to grow and empower local economies.
DoorDash Engineering Blog
2M ago
Welcome to WordPress! This is your first post. Edit or delete it to take the first step in your blogging journey ..read more
DoorDash Engineering Blog
6M ago
We’ve traditionally relied on A/B testing at DoorDash to guide our decisions. However, when precision and speed are crucial, this method often falls short. The limited sensitivity of A/B tests—their ability to detect real differences between groups—can result in users being exposed to suboptimal changes for extended periods. For example, in our search and ranking ...
The post How DoorDash is pushing experimentation boundaries with interleaving designs appeared first on DoorDash Engineering Blog ..read more
DoorDash Engineering Blog
6M ago
DoorDash is supporting an increasingly diverse array of infrastructure use cases as the company matures. To maintain our development velocity and meet growing demands, we are transitioning toward making our stateful storage offerings more self-serve. This journey began with Kafka, one of our most critical and widely used infrastructure components. Kafka is a distributed event ...
The post DoorDash Empowers Engineers with Kafka Self-Serve appeared first on DoorDash Engineering Blog ..read more
DoorDash Engineering Blog
7M ago
As part of our ongoing efforts to enhance product development while safeguarding app health and the consumer experience, we are introducing metric-aware rollouts for experiments. Metric-aware rollouts refer to established decision rules to flag issues with automated checks on standardized app quality metrics during the new feature rollout process.
Every action DoorDash takes focuses on enhancing the consumer experience. Through deploying metric-aware rollouts, we aim to prevent performance degradation and other problems for our customers when we add new elements or products. This new fea ..read more
DoorDash Engineering Blog
8M ago
DoorDash has redefined the way users explore local cuisine. Our highly interactive notification system has been an integral part of this experience by not only keeping users updated about deliveries but also by acting as a pathway to personalized restaurant recommendations.
Our notifications are meticulously designed to be an essential line of communication that keeps both utility and personalization in mind. Because we believe each meal should be an exploration and an opportunity to discover new culinary delights, we leverage personalized notifications to open unexplored avenues of cuisine fo ..read more
DoorDash Engineering Blog
9M ago
When it comes to reducing variance in experiments, the spotlight often falls on sophisticated methods like CUPED (Controlled Experiments Using Pre-Experiment Data). But sometimes, the simplest solutions are the most powerful and most overlooked – like reducing or eliminating dilution. This unglamorous yet effective technique is free, easy to implement, and plays nicely with other variance reduction methods.
So what is dilution? Dilution happens when we track users in an experiment who could not possibly have been impacted by the treatment. To illustrate, imagine you’re testing a feature to imp ..read more
DoorDash Engineering Blog
10M ago
DoorDash’s retail catalog is a centralized dataset of essential product information for all products sold by new verticals merchants – merchants operating a business other than a restaurant, such as a grocery, a convenience store, or a liquor store. Within the retail catalog, each SKU, or stock keeping unit, is represented by a list of product attributes. Figure 1 shows an example SKU and some of its attributes as it is stored in the retail catalog.
Figure 1: An example SKU and some of its attributes in the retail catalog
Having high-quality, complete, and accurate product attributes for each ..read more
DoorDash Engineering Blog
11M ago
Real-time event processing is a critical component of a distributed system’s scalability. At DoorDash, we rely on message queue systems based on Kafka to handle billions of real-time events. One of the challenges we face, however, is how to properly validate the system before going live.
Traditionally, an isolated environment such as staging is used to validate new features. But setting up a different data traffic pipeline in a staging environment to mimic billions of real-time events is difficult and inefficient, while requiring ongoing maintenance to keep data up-to-date. To address this cha ..read more
DoorDash Engineering Blog
1y ago
The DoorDash ETA team is committed to providing an accurate and reliable estimated time of arrival (ETA) as a cornerstone DoorDash consumer experience. We want to ensure that every customer can trust our ETAs, ensuring a high-quality experience in which their food arrives on time every time.
With more than 2 billion orders annually, our dynamic engineering challenge is to improve and maintain accuracy at scale while managing a variety of conditions within diverse delivery and merchant scenarios. Here we delve into three critical focus areas aimed at accomplishing this:
Extending o ..read more
DoorDash Engineering Blog
1y ago
We reviewed the architecture of our global search at DoorDash in early 2022 and concluded that our rapid growth meant within three years we wouldn’t be able to scale the system efficiently, particularly as global search shifted from store-only to a hybrid item-and-store search experience.
Our analysis identified Elasticsearch as our architecture’s primary bottleneck. Two primary aspects of that search engine were causing the trouble: its document-replication mechanism and its lack of support for complex document relationships. In addition, Elasticsearch does not provide internal capabilities f ..read more