Failover Plans, Outage Playbooks and Resilience Gaps

How New York Times Engineering fortified our systems ahead of the 2020 presidential election.Illustration by Gizem VuralBy Alexandra Shaheen, Megan Araula and Shawn BowerThis is part two of an ongoing series about how The Times’s is working to improve the resilience of its systems. Read part one here.Over the past few years, New York Times Engineering has been asking ...

Bug Blog: TFT Bugs and Patches

In this article, I’ll be describing how we handle patches across PC and mobile for TFT, and how this relates to quality assurance. Later, I’ll tag in my engineering counterpart, Gavin Jenkins, to give a super techy point of view on patches, and we’ll dive into two use cases that demonstrate different types of patches and how we deploy them. ...

Pinot Real-Time Ingestion with Cloud Segment Storage

Introduction Apache Pinot is an open source data analytics engine (OLAP), which allows users to query data ingested from as recently as a few seconds ago to as old as a few years back. Pinot’s ability to ingest real-time data ... The post Pinot Real-Time Ingestion with Cloud Segment Storage appeared first on Uber Engineering Blog. ...

Surfacing eBay Inventory Across the Web with the eBay Items Widget

The new open-source widget gives developers several layout options for displaying eBay inventory in third-party shopping experiences....

How We Cut GrabFood.com’s Page JavaScript Asset Sizes by 3x

Introduction Every week, GrabFood.com’s cloud infrastructure serves over >1TB network egress and 175 million requests, which increased our costs. To minimise cloud costs, we had to look at optimising (and reducing) GrabFood.com’s bundle size. Any reduction in bundle size helps with: Faster site loads! (especially for locations with lower mobile broadband speed...

Uber’s Fulfillment Platform: Ground-up Re-architecture to Accelerate Uber’s Go/Get Strategy

Introduction to Fulfillment at Uber Uber’s mission is to help our consumers effortlessly go anywhere and get anything in thousands of cities worldwide. At its core, we capture a consumer’s intent and fulfill it by matching it with the right ... The post Uber’s Fulfillment Platform: Ground-up Re-architecture to Accelerate Uber’s Go/Get Strategy appeared first on Uber E...

Search and Filtering Using GraphQL and Dgraph

With GraphQL being a client-centric technology, it allows you to have fine control over how you request your data. Query responses in GraphQL contain the exact data you’ve asked for, no more and no less....

Using Sentiment Score to Assess Customer Service Quality

How AI-based Sentiment Models Complement Net Promoter ScoreBy Shuai Shao, Mia Zhao, Yuanyuan NiNet Promoter Score (NPS) is a well-accepted measurement of customer satisfaction in most customer-facing industries. We leverage NPS at Airbnb to help measure how well we serve our community of guests and hosts through our customer service. But NPS has two major drawbacks: 1...

Data Movement in Netflix Studio via Data Mesh

By Andrew Nguonly, Armando Magalhães, Obi-Ike Nwoke, Shervin Afshar, Sreyashi Das, Tongliang Liu, Wei Liu, Yucheng ZengBackgroundOver the next few years, most content on Netflix will come from Netflix’s own Studio. From the moment a Netflix film or series is pitched and long before it becomes available on Netflix, it goes through many phases. This happens at an unprec...

Protecting Personal Data in Grab's Imagery

Image Collection Using KartaView Starting a few years ago, we realised the strong demand to better understand the streets where our drivers and clients go, with the purpose to better fulfil their needs and also to be able to quickly adapt ourselves to the rapidly changing environment in the Southeast Asia cities. One way to fulfil that demand was to create an image ...