Category: Engineering

To build customer support bots, internal knowledge graphs, or Q&A systems, customers often use Retrieval Augmented Generation (RAG) applications which leverage pre-trained models together with their proprietary data. However, the lack of guardrails for secure credential management and abuse prevention prohibits customers from democratizing access and development of these applications. We recently announced the MLflow […]

Launched in 2019, Segmentation Platform has been Grab’s one-stop platform for user segmentation and audience creation across all business verticals. User segmentation is the process of dividing passengers, driver-partners, or merchant-partners (users) into sub-groups (segments) based on certain attributes. Segmentation Platform empowers Grab’s teams to create segments using attributes available within our data ecosystem and […]

One of the key challenges that organizations face when adopting the open data lakehouse is selecting the optimal format for their data. Among the available options, Linux Foundation Delta Lake, Apache Iceberg, and Apache Hudi are all excellent storage formats that enable data democratization and interoperability. Any of these formats is better than putting your […]

In the world of data engineering, there are operations that have been used since the birth of ETL. You filter. You join. You aggregate. Finally, you write the result. While these data operations have remained the same over time, the range of latency and throughput requirements has changed dramatically. Processing a few events at a […]

The Databricks Container Infra team builds cloud-agnostic infrastructure and tooling for building, storing and distributing container images. Recently, the team worked on scaling Harbor, an open-source container registry. Request loads on Harbor are read-heavy and bursty and it is a critical component of Databricks’ serverless product – anytime new serverless VMs are provisioned, Harbor gets […]

Earlier in this series, we covered the importance of graph networks, graph concepts, graph visualisation, and graph-based fraud detection methods. In this article, we will discuss how to automatically detect new types of fraudulent behaviour and swiftly take action on them. One of the challenges in fraud detection is that fraudsters are incentivised to always […]

Large Language Models (LLMs) unlock a wide spectrum of potential use cases to deliver business value, from analyzing the sentiment of text data stored in a SQL warehouse to deploying real-time chat bots that answer nuanced questions about your products. However, democratizing access to powerful SaaS and open source LLMs for these applications comes with […]

Chief AI Officer Nitzan Mekel-Bobrov and Vice President of Seller Experience Xiaodi Zhang appeared at the VentureBeat Transform conference on Tuesday, July 11th, to discuss generative AI, how eBay has been building AI infrastructure for many years and ways that recent evolutions in the technology can help sellers, buyers and employees. Xiaodi also spoke as […]

On July 10, 2008, Apple opened the doors on a totally new kind of store. In one announcement, Apple enabled an entire ecosystem of apps, allowing for third-party developers to create applications specifically for iOS. As eBay was a launch partner for the historic launch of the App Store, it’s also the fifteenth anniversary of […]

Introduction Coban, Grab’s real-time data streaming platform team, has been building an ecosystem around Kafka, serving all Grab verticals. Along with stability and performance, one of our priorities is also cost efficiency. In this article, we explain how the Coban team has substantially reduced Grab’s annual cost for data streaming by enabling Kafka consumers to […]