Case Study


A Story Of Online Dating


    Online Dating


    Refactoring of application to adopt Microservices and migration to GCP.

    Google Cloud, Kubernetes, , Microservices, , OCI, Oracle, Terraform

Problem Description:

In early 2017, had become the largest online dating platform reporting over 35 Million users, with the only competitor eHarmony far from catching up with only 17.5 Million. The advent of this new romantic age that leveraged online technologies in the quest for love, brought with it a whole new category of challenges for the platform operators. The number of requests to their servers were no longer in the thousands but in the Trillions. Yet these new types of challenges facing Match, were perfectly suited to be addressed by leveraging the scale and performance benefits of cloud solutions and integrating these with traditional day-to-day IT operations.

One of the first challenges faced by the company was to modernize any remaining monolithic architecture for increased performance and agility. Previously within their software system, functionally distinguishable aspects of their applications, such as data I/O, processing, error handling and user interfaces, were interwoven rather than being isolated into separate architectural components. Other bottlenecks and issues included the elastic demand capabilities of their web servers, and the high capital expenses of provisioning new resources for the on premise data centers.

Solutions Highlights:

In order to facilitate performance improvements and greater agility we conceptualized and implemented a full service end-to-end cloud migration and adoption strategy based around the cloud services offered by Google (GCP) and Oracle (OCI). First, we helped them re-architect their existing infrastructure and applications into a suite of independently deployable, modular microservices. As such each application runs a unique process and communicates through a well-defined, lightweight mechanism. With the help of Docker Containers we helped them migrate these from their on premise locations to the Google Cloud Platform (GCP). Initially, our team used the ExtraHop platform for a continuous auto-discovery of application dependencies and to identify and map architectural requirements necessary to run these applications on GCP. This allowed us to configure and provision Match’s new cloud-based VM environment in a way that would optimally serve the needs of their applications.

Furthermore, we used HashiCorp’s cloud configuration and orchestration tool Terraform to spin up a highly elastic farm of Apache Web Servers in the Google Cloud, to meet the unpredictable and volatile number of requests coming from the online dating platform. This enabled Match to scale flexibly to meet demands and provided significant cost-savings by scaling down when demands were low and stable. Finally, after this initial cloud solution, commissioned us to help them migrate their database as well. Subsequently we migrated their Oracle DB from on premise to the Oracle Cloud AZ in Phoenix. This is done with the aim of maintaining and improving performance further through the utilization of Oracle’s Baremetal infrastructure. Simultaneously, we are facilitating significant Oracle licensing cost savings through the provision of dynamically scalable instances (elastic CPU scalability) and automation.