The solution was developed to replicate data from key sources into a central database platform:

• Automatic vehicle location (AVL) data, provided by bus operators and ticketing providers, tracks a public transport vehicle’s location
• The Open Data Platform provides timetables, fares and disruptions data.

A challenge included engaging with the data producers, mainly due to a lack of visibility on how data was being used. To get them onboard, we explained the benefits of the open-source model and how this would support better two-way feedback going forward.

As a black box system, while we knew the inputs and outputs, the internal workings were unknown and required us to reverse engineer the solution. A proof of concept was developed to demonstrate viability.

We built a cloud native solution using GDS practices:

• Modern, serverless cloud services were selected for security, performance and cost efficiency benefits, as well as supporting the existing skill sets and tools in place
• The tech stack supports scalability and future demand, allows new features to be added effectively, and supports quicker development and fixing of issues
• AWS was selected for data screening and to allow data to be ingested with minimal lag.

Implementation of best practice included setting up monitoring and alerting dashboards, and breaking tickets into smaller pieces of work to maintain momentum during sprints. Adding automated ways of working and CI/CD pipelines drove efficiencies in the development process.