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Introduction

Data drives every decision we make at Grab. As our operations scale, so does our need for robust, real-time data ingestion and processing frameworks. Enter Hugo: our self-service data platform that has long empowered teams to seamlessly route data into our Data Lake. Today, Hugo is evolving. We have taken previously siloed onboarding workflows and transformed th...


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Introduction

Long integrated development environment (IDE) sync/indexing times can quietly erode developer productivity, making code navigation sluggish, spiking memory usage, and slowing down Jetpack Compose preview updates, turning the IDE into a bottleneck rather than a helpful tool. For Android engineers working in a large monorepo, this was a daily reality. In this post...


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Introduction

Ensuring the reliability of Apache Flink deployments in Grab is crucial for the availability of our business-critical, real-time applications. While all applications are tested in a staging environment before getting promoted to the production environment, there is still a class of issues that can only surface when deploying in the production environment, e.g.:<...


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Introduction

In Part I, we discussed why Grab is investing in a data mesh, referred to as the Signals Marketplace within Grab, as part of our evolving data culture. We also explained how data certification aids teams in reliably reusing data across dif...


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