The Current Landscape
Today’s banking status quo is no longer confined to the four walls of physical institutions.
With the help of cloud, microservices, distributed systems, and application programming interface (API)-led design, banking services such as customer onboarding, instant or bulk payments, mobile payments, investment, lending, and cash withdrawals have become ubiquitous. Amid these changes, if there is one thing that every bank prioritizes and wants to provide to its customers, it is a stable and secure digital banking experience.
However, service disruptions often affect customers despite their increasing reliance on digital banking. Such service disruptions lead to reputational impact and financial losses. For banks, the focus lies in developing and maintaining digitally mature, agile, and dependable services. To that end, banks must embrace DevOps practices that deliver modern business solutions and personalized designs. Banks benefit when these practices are embedded with microservices and a container-based approach with the high scalability that platformization and the cloud offer.
Prevention is better than cure
Regardless of comprehensive testing procedures, there is no way to ascertain if a piece of code or system is immune to degradation or failure.
This is especially true in modern-day digital banking, where the chances of service disruptions are higher. Banks cannot forecast all user activities, sudden hike in traffic due to external events such as a discount on an e-commerce portal, internal interface lag among different services, or real user experience after a new version release. To counter unplanned outages, it is important for banks to have zero ambiguity, maximum visibility, precise insights, and high agility to design, deliver, and maintain a stable and secure user experience.
New-age banking: Think beyond monitoring
Global financial services firms are exploring state-of-the-art technologies to build customized experiences around the end user.
To deliver a secure and stable experience, banks have been using a traditional monitoring approach for long. But the traditional method evaluates the statistics of known metrics, which is ideal for monolithic designs, where alerts for known threshold breaches are sufficient. To illustrate, consider a user complaining about the failure of an online payment. In diverse, highly scalable, and distributed designs, the issue is addressed through the collective action of multiple underlying services: the user logs in from the front end using a service, which then calls for subsequent services based on user actions. The request travels across multiple services like initiating, mid-processing, fraud check, and clearing, to complete the online payment action.
In this example, the traditional monitoring approach will trigger an alert only against the failure of pre-defined monitored metrics in the payment flow. However, it is incapable of understanding the reason for the failure, thus leading to bigger impacts, more investigation time, and a higher mean time to resolution (MTTR). Now, banks need a solution which can also detect the unseen cause of the failure.
This is where observability solutions can help banks. Such solutions aggregate all IT stacks, such as user actions, code execution records, resource utilization, networks, service interfaces, application performance management (APM), browser response, security, and other important system behaviors. Observability and monitoring complement each other, where monitoring is a part of observability, and observability cannot be achieved without monitoring
Observability solutions help banks identify the hidden cause of a disruption or failure by collecting system insights. The concept originates from the control theory of engineering systems, where the output is used to control the internal states of the system.
Observability can be achieved by efficient, correlative, and collective instrumentation and visualization of metrics, traces, and logs—deemed the three observability pillars.
A best-fit observability solution can show the intelligent correlation on the collected insights of infrastructure, APM, back-end, code, security, browser-mobile real user response, synthetic checks, and API calls.
To illustrate, let’s go back to the online payments failure example mentioned above. Equipped with an observability and monitoring solution, the bank’s IT support team can proactively identify the online payment failure. By utilizing the three observability pillars, they can conclude which service was affected while performing what action. It provides proactive detection, reduces impact, and eliminates unplanned downtime.
In a nutshell, monitoring updates the bank’s support staff on the system failures (knowing the knowns), while observability informs why the system has failed (seeing the unseen). The solution can be further integrated with IT service management (ITSM) tools, artificial intelligence, bots, or processes to trigger self-heal actions.
The way forward
The future of innovative banking is not restricted to just investing in state-of-the-art technologies.
Over the next few years, a bank’s reliance on cutting-edge technologies will grow further, to convert its vision and customers’ expectations to reality and action. This will lead to faster software release with new features, but these releases cannot come at the cost of performance or reliability. This is where the right observability and monitoring tool plays a key role, where developers can focus on innovation and quick resolutions with minimal disruption, while customers receive the highest degree of reliability. Banks can partner with experts to help them identify the best-fit observability and monitoring solution that can answer the ‘what and why’ of a system degrade against the key performance indicators – availability, capacity, and performance.