The need for more efficient payments infrastructure
Across the payments industry, organizations feel pressure to reduce costs. Evolving messaging standards, the growing need to support real-time processing, and accelerating transactional volumes only exacerbate an already difficult situation to contain costs. Existing technology is not helping either. Consequently, many payment organizations are reevaluating their current payments infrastructure to reduce both the complexity and cost of processing payments. They also want to gain the scalability and performance required to adapt to a world that is increasingly digital.
Excess infrastructure and cost
Virtualized infrastructure has made provisioning compute, storage, and network resources much easier. However, uncertainty over transaction volumes often drives teams to configure virtualized environments for projected peak volumes. While erring on the side of overprovisioning resources eliminates the risk of running out of capacity during an unexpected spike in demand, it can lead to unused capacity and high cost for nominal usage. In many instances, payment processors also run their messaging infrastructure in a hot/warm configuration because of challenges with distributed data replication. As a result, a significant portion of resources may sit idle during parts of the year, resulting in higher operating costs than what actual payment volumes necessitate.
Complex maintenance and upgrades
Many organizations have deployed traditional message brokers on top of virtualized infrastructure. They have also invested in some degree of automation to ease the setup and configuration of the messaging infrastructure, which typically includes a database for persisting messages and a cache to improve overall messaging throughput. Unfortunately, you still need to adjust and test the automation scripts associated with it, which tends to create a messaging infrastructure that is costly to operate and makes regular upgrades a painful process.
Cannot quickly adjust to changing volumes
Even deploying a small configuration based on one of the more popular message-oriented middleware packages makes it possible to achieve performance of approximately 20,000 messages per second. The performance interplay between the database, the broker, and the caching components make vertical scaling the typical choice. However, this approach also increases the cost and effort to configure additional virtualized infrastructure, which ultimately makes it difficult to adjust quickly as transaction volumes fluctuate.