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Engineering
Embracing a Docs-as-Code approach
Read to find out how Grab is using the Docs-as-Code approach to improve technical documentation. -
Engineering · Security
Graph Networks - Striking fraud syndicates in the dark
As fraudulent entities evolve and get smarter, Grab needs to continuously enhance our defences to protect our consumers. Read to find out how Graph Networks help the Integrity team advance fraud detection at Grab. -
Engineering
How we reduced our CI YAML files from 1800 lines to 50 lines
GitLab and its tooling are are an integral part of the machine learning platform team stack, for continuous delivery of machine learning. One of our core products is MerLin Pipelines. We were reaching certain limitations of GitLab for large repositories by way of includes and nested gitlab-ci YAML files. -
Engineering
How Kafka Connect helps move data seamlessly
Grab’s real-time data platform team (Coban) covers the importance of moving data in and out of Kafka easily and how Kafka Connect helps with that. -
Engineering
Supporting large campaigns at scale
Running batch jobs targeting a large user base is a challenge. Find out how we designed our system to tackle the challenge at scale. -
Engineering · Data Science
How telematics helps Grab to improve safety
Coupled with data science, telematics can help to detect traffic events such as harsh braking and unsafe lane changes so we can provide a safer experience for our users. Read on to find out more about the challenges faced and how we addressed them with telematics. -
Engineering · Data Science
Real-time data ingestion in Grab
When it comes to data ingestion, there are several prevailing issues that come to mind: data inconsistency, integrity and maintenance. Find out how the Caspian team leveraged real-time data ingestion to help address these pain points. -
Engineering
Abacus - Issuing points for multiple sources
Learn about the challenges of points rewarding and how GrabRewards Points are rewarded for different Grab offerings.