Moniepoint provides financial solutions like payment, credit, business management, banking services for Nigeria’s SMBs. The company has now scaled to support over two million businesses since its founding in 2015 using Confluent Cloud. Moniepoint has scaled from processing hundreds of thousands of requests to millions of requests using this solution. Successful integration of Confluent Cloud has been instrumental in ensuring the platform’s reliability, scalability, adaptability.
In Nigeria, small and medium-sized businesses, SMBs make up 48% of the national GDP. Moniepoint provides financial solutions to power the aspirations of these SMBs from payment, credit, business management to banking services. The company has now scaled to support over two million businesses since its founding in 2015.
During its initial growth stages, Moniepoint’s infrastructure grappled with handling increasing transaction loads. It required manual effort to access and fix data, delaying customer access to their transactions. Felix Ike, CTO and co-founder, Moniepoint identified three main issues with Moniepoint’s legacy data storage solution that Confluent’s data streaming solution helped to solve.
Elimination of replication lags
Originally, each financial solution had a single database, which used read replicas. This initially helped with database management, but the duplicate copies of the database used for reading data became an issue. As transactions increased, read replicas fell behind, causing replication delays of up to eight or twelve hours.
The lags in replicating the data meant it became increasingly difficult to support the workload using a single database. The read replicas became practically unusable. For example, how do you tell your customers that I cannot display transactions because they are lagging?
Moniepoint eventually adopted a horizontal scaling solution with Confluent. It eliminated the manual effort to address and eliminate individual replication lags. Moniepoint could now capture changes in transaction data efficiently, ensuring near real-time data in read replicas.
The outperformance of an open-source environment not only resolved scalability challenges, but also provided a scalable, reliable foundation for handling growing transaction volumes.
Real-time migration to reporting
Moniepoint also had to seamlessly migrate its transaction data to a reporting data store for analytical purposes. Its legacy infrastructure could not support real-time transfers of data without adding costs. With Confluent Cloud, Moniepoint found a managed solution to copy data from the master server to a reporting server.
Unlike the complexities of building custom solutions to copy data from master databases to reporting servers, Confluent’s managed platform ensures efficient and real-time data replication, eliminating the need for additional infrastructure costs.
Decoupling services, enhancing scalability
Before the company’s use of Confluent, certain products relied on database-level transactions that triggered important decisions for the product. The activation of these products was only possible with the development of a specialised layer.
The solution was to log the transactions on Confluent’s managed streaming layer. After which, Felix said his scaling needs were resolved. The implementation of Confluent Cloud was so efficient that you had near real time data in the read replicas.
Moniepoint leveraged topics to expose events, empowering each financial solution to consume the data immediately and independently for decision-making, making reporting more efficient.
Breaking department monoliths
While Confluent helped Moniepoint scale, without the discipline of an intermediary service, the microservices evolved to become monoliths. The tightly coupled architecture could not separate the company’s four financial products into microservices, without affecting each other’s database.
For example, the payment and settlement services could not be scaled because they were single components. A reactive solution would be to break up the service databases.
The Moniepoint team discovered Confluent as an intermediary solution, by plugging in Confluent between the two services, which solved the problem elegantly. Once a transaction happens and the payment is successful, you log the event and then you move on.
Redesigning the system architecture with Confluent Cloud at its core, Moniepoint revolutionised its transaction status management. It could finally consolidate disparate processes across its financial solutions without a large infrastructure team to manually make the changes.
The centralised approach not only optimised performance but also facilitated easy scaling. Moniepoint swiftly adapted to growing transaction volumes across its diverse financial offerings.
Felix referenced that with loan processing, Confluent allowed for seamless tracking of transaction stages. This prevented bottlenecks and ensured timely customer updates. Similarly, for payment transactions, Confluent unified the status-check mechanism, simplifying the entire process and allowing for real-time adjustments.
“This allowed us to scale, from processing, say hundreds of thousands of requests to millions of requests,” says Felix.
Handling of transactions
Before the implementation of a managed solution with Confluent, Moniepoint had to create a small, specialised system to manage transactions and notification. The initial use of Apache Kafka via a relational database functioned seamlessly under lighter traffic conditions. Eventually, a non-managed solution could not keep up with the company’s scaling.
“The initial implementation of this particular microservice was terrible,” says Felix. “We built it on a relational database, and the simplicity was good because we could just have three tables. We were happy with the results until business blew up, and then everybody was on fire,” explains Felix.
Moniepoint saw issues with database locks, low throughput and scalability from the escalating transaction load. The meticulous process of maintaining a finite set of records led to unexpected database hang-ups. For Felix’s team to build on top of Confluent, they were able to scale their infrastructure.
Felix shared that since Confluent deployment this year, “We have never had any form of downtime with respect,” to processing millions of requests from its customers.
The impact extended beyond immediate problem-solving. Confluent offered a future-ready solution for Moniepoint’s expanding user base. The ability to decouple critical services, coupled with reliable scaling, positioned Moniepoint as a leader in the Nigerian ecosystem, serving over 2 million businesses and aiming for further expansion across African markets.
The successful integration of Confluent Cloud became instrumental in ensuring the platform’s reliability, scalability, and adaptability to experience financial happiness.
How Confluent works
The confluent data streaming platform reimagines your data architecture by building upon the heritage of Apache Kafka and Apache Flink to enable enterprise-wide adoption of data products.
With Confluent, your data architecture is no longer a complicated, expensive, and risky mess. The platform untangles data problems, breaking down data barriers and silos across your enterprise. It delivers universal data products that connect teams, systems, and applications, ensuring a consistent view of the most up-to-date data.
With the pillars describe below, Confluent’s Data Streaming Platform transforms data mess into reusable, high quality data products. These data products remove the need for brittle point-to-point integrations, and can be leveraged by every team, in any organization, for operational, analytical, and never-before possible use cases.
Stream
Confluent reimagines data streaming through the award winning Kora engine, which removes the need to manage Apache Kafka. With Kora, you have the scale, elasticity, resiliency, availability, and security required for mission-critical workloads across hybrid and multi-cloud environments. Kora improves ROI by reducing TCO through pay-as-you-go storage.
Connect
Data streaming requires connections to be built, deployed, and managed for each data source. Confluent provides 120+ pre-built connectors that allow your teams to instantly connect data. Your teams are free from writing generic integration code and managing connectors.
Process
Confluent lets you join, enrich, and curate data at the source while removing the operational complexity and burden of running Apache Flink. Regardless of whether the data comes from the operational or analytical estate, it is presented in a consistent format that seamlessly works across both.
Govern
Confluent provides a suite of governance capabilities that enable your teams to maintain data contracts, classify and organize data into a neat catalogue, track data lineage and securely find and consume trustworthy data products through a self-service portal, while ensuring observability, compliance and confidentiality of data that is on the move.
