How cloud computing drives scalability for banks and fintechs
Key advantages of scalability
Cloud-based platforms offer banks a range of critical benefits, with scalability crucial among them. Institutions equipped with scalable infrastructure can activate several advantages:
Handle varying workloads
- Resources are dynamically allocated or deallocated to match demand in real time.
- Businesses scale up or down depending on how the workload fluctuates during the day.
- This means that peak periods, like Christmas, Valentine’s Day, or Black Friday, are handled by dynamically allocating more resources.
- On the other hand, during off-peak periods, resources will be downscaled to optimise costs and reduce workload.
Cost efficiency
- Scalability avoids institutions overprovisioning or underprovisioning resources.
- Either scenario results in wasted resources, worker hours, or (in the case of underutilisation) disgruntled customers.
Reliability
- By spreading allocation across peak and off-peak periods, cloud systems offer the possibility of high performance and availability, even during heavy usage.
- Workloads are shared across various servers or data centres, reducing the risk of system failure and improving fault tolerance.
- True scalability enables disaster recovery in rapid time, as resources are quickly allocated to handle sudden spikes.
What are microservices, and how do they power scalability?
The basics of microservices in banking architecture
Microservices are a style of software architecture that structures applications as a collection of coupled services. This methodology means the application is deployed, developed, and scaled as a suite of small, independent services. These communicate with each other through APIs.
Breaking an application into a group of more minor services allows separate teams to maintain, develop, and iterate individual pieces of the puzzle without affecting the whole platform. It will enable rapid, reliable, and frequent deployment of significant, complex software and services.
At Pismo, we have an entire platform comprising microservices designed to meet the modular needs of modern and forward-thinking institutions. We provide flexibility for rapidly expanding new demands in the financial services market.
Strategies for scaling using microservices
Coordinate services
As the number of microservices increases, so does the challenge of handling interactions between them. Creating a service discovery pattern — like mesh frameworks, DNS-based discovery, or P2P — establishes a simple communication method for microservices. Using a reliable communication protocol is also essential to provide a reliable, fault-tolerant, and asynchronous method of inter-service communication.
Maintain data consistency
Data updates should be pushed consistently across their network of services to avoid bottlenecks or single points of failure. One method of establishing consistency is the use of event-driven systems. This involves the passing of asynchronous messages through a broker module. This differs from the traditional remote procedure call (RPC) between APIs. Using a broker ensures others can receive the message sent by one service. These recipients can consume the message at their own pace.
Choose the right infrastructure
Institutions should evaluate their project requirements, as several tools exist to run microservices effectively. Factors to consider are workload characteristics, cost, and long-term performance.
Establish observability
Your developers need visibility of their applications to debug and troubleshoot any issues your architecture may encounter effectively. Implement logging mechanisms to capture data from all microservices and use error-tracking tools to aggregate resultant logs. Select visualisation software that can offer your developers an accessible overview of performance trends and critical events. Furthermore, consider implementing distributed tracing to provide request flow monitoring to identify bottlenecks and latency issues.
Ensure resiliency
As the number of services increases, ensuring resiliency becomes more challenging. The distributed nature of the architecture provides unique speedbumps. These can be minimised by establishing redundancy, fault tolerance, and load-bearing strategies. Should a microservice fail, it’s critical to detect it rapidly, isolate affected services, and recover quickly. Having retry mechanisms in place can mitigate network failures by repeating requests but must also be limited by backoff intervals to avoid responsiveness.
Finally, users should implement a culture of resilience testing to identify weaknesses ahead of time, no matter how small or insignificant they may seem. Pismo utilises chaos engineering tools to root out issues well before they occur in production.
Security and authentication
As the number of microservices expands, so does the potential attack surface. It’s crucial to fortify security measures while scaling. This is achieved in several ways:
- Securing inter-service communication through encryption and authentication protocols such as Transport Layer Security (TLS), Mutual TLS (mTLS), or API Gateways.
- Robust authentication tools. Typical solutions include OAuth 2.0, JSON Web Tokens, and Role-Based Access Control (RBAC).
- Regular patching and updating of software using automated patch management tools
- Conducting security audits and penetration testing
Vertical vs horizontal scalability: differences and benefits
Vertical scaling involves adding resources to a single component to meet increased demands, while horizontal scaling adds additional nodes or machines to distribute the workload. In banking systems, where reliability and performance are paramount, understanding the nuances of each scaling approach is crucial.
What is horizontal scalability?
Horizontal scaling, also known as scaling out, expands infrastructure by adding more nodes or machines. This approach is akin to delegating tasks among several employees, spreading the workload to accommodate increased traffic. However, managing multiple machines can introduce complexity, requiring careful consideration of workload distribution and system compatibility.
The advantages of horizontal scaling include:
- Simpler scaling: adding additional machines rather than new software
- Less downtime: older machines can run simultaneously as new machines are added
- Increased performance: more endpoints means better traffic handling
- Lower cost: pay only for what you use
Horizontal scaling is best used to provide high-quality service and high performance alongside the flexibility to configure machines to meet custom needs. Equally, horizontal scaling can solve challenges around operating in multiple geographies. Companies that use a microservices architecture or containerised applications will naturally achieve greater performance results from distributed systems.
What is vertical scalability?
Vertical scaling, or scaling up, enhances the capabilities of existing machines to handle greater demands. This method involves upgrading resources like CPU, RAM, and storage on a single server. Vertical scaling is less complex in terms of system communication and maintenance since it involves fewer nodes to manage.
However, it’s not without its risks or limitations. Vertical scaling often involves taking down a server for patching or upgrading. This leads to increased downtime and potential outages. Equally, operating from a single node creates a single point of failure. There is also a limit to how much you can scale up a single server or service.
Looking to learn more about distributed systems, and how Pismo utilises its architecture to mitigate outages, reduce downtime, and make developers’ lives easier? We have a whitepaper just for you.
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Sources:
- Miller, Clay, 2024, “Application and Workload Modernization for Banking”, IDC
- GlobalData, 2023, “Cloud Computing”, Thematic Intelligence
