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An established asset manager approached us with a research platform challenge. Their application brought together market data with their own research and opinions into one view to create and evaluate their strategies.
Their legacy implementation ran on several servers as a monolithic application, with a hand managed and complex infrastructure. The overall performance was poor, which is unacceptable in a trading research environment where timeliness, speed and accuracy are paramount. In addition, the ongoing cost of this setup was hard to justify.
After reviewing the challenges, Hentsū were able to create an elegant serverless solution in Azure leveraging the huge power and scale of the cloud, which is simply not possible in a private cloud. Where possible we used cloud native services for their low cost, breadth of features available, and ease of management.
Hentsū took the existing legacy application and broke it up into microservices. The code was entirely rewritten into a modern cloud native stack, separating real-time applications from batch processing to be able to handle these appropriately.
The platform has built-in multi-region resiliency across the Azure cloud and is also hugely auto-scalable based on workloads and user demand. Within the application there are health checks and integrated alerts, automated recovery and restarts if any service fails.
Utilising such a cloud native serverless solution allows us to obtain huge processing power when needed, and only pay for what was actually used.
The entire platform has been built as a serverless solution. The batch work now uses Azure Batch; scripts have been turned into Docker containers which are scheduled onto temporary machines used for the smallest amount of time necessary. This allows for simplified management, huge parallelism, and low cost.
The application servers are now hosted with Azure App Service to leverage the reliability and huge number of management tools available. Hentsū built out the data pipelines to move data from the large number of feeds into an Azure Cosmos DB. A managed database was used to take away the headaches of managing a database on a machine, such as patching or disk management, while getting access to features such as georedundant automatic backups and one-button scaling.
Hentsū also developed the API server that allows individual services to get access to the data, as well as a web app that the client interacts with to perform their data analysis.
Bitbucket and Bamboo are used as the CI/CD pipelines, which test and build the application and batch Docker containers and then deploy to the container registry, all automatically when the code is updated. This can be adapted to use any repository and build server products if needed, such as Azure DevOps.
Security is crucial, with all access to the application handled natively within Azure and integrated with Azure AD for a seamless and authentication experience with world-class security.
Everything you need to secure and manage a web app is contained in Azure App Service:
The client was very pleased with the final product, particularly around the much lower cost and ease of administration. Additional iterations of the platform are already being seamlessly deployed, with the underlying infrastructure able to handle any amount of additional data or load from end users.[/et_pb_text][/et_pb_column][/et_pb_row][/et_pb_section]