Observability must translate tech metrics into meaningful business context and value.
In a customer-facing business like ours, where financial services and capital markets move in real time, the experience we deliver to users isn’t just about convenience. It’s about credibility. Every glitch, every delay, every broken journey affects not just the transaction, but trust. And once trust erodes, rebuilding it is far harder than preventing the issue in the first place.
I believe that we need a mind shift that observability isn’t an IT initiative, it’s a business enabler. We can’t treat digital experience as something that gets measured after deployment or only when something goes wrong. It has to be part of the strategy, part of the design, and part of how we operate every day.
For that to happen, observability needs to speak the language of the business. It’s not just about CPU utilization or error rates. It’s about whether onboarding journeys are completing, whether customers are dropping off during KYC, or whether an advisory dashboard is rendering the right insights fast enough for our relationship managers. These are not “technical issues”, they are business blockers, and they need to be treated that way.
Observability must speak the language of the business. Only then can it become a true enabler of digital experience.
What I often see is that while organizations have invested in various tools like APM, analytics, infrastructure monitoring, they still struggle to derive insights that are usable across functions. The signal-to-noise ratio is poor. Everyone has dashboards with tons of data, but few can tell a clear story about what’s actually affecting users or revenue, which we call ‘insight’. That’s where the real opportunity lies: in intelligent observability that prioritizes what matters most.
Another challenge is the over-indexing on incident response, rather than preventive operations. Most environments still function with a “wait for alert, then fix” approach. But in a hyper-competitive, always-on world, that’s too slow. We need to shift left, not just in DevOps pipelines, but in experience assurance overall. Can we identify the leading indicators of friction? Can we predict drop-offs or failures before they escalate? That’s where AI and automation come in and not to replace human judgment, but to amplify it.
Security and compliance are also core to experience. A customer who feels their data isn’t safe won’t stick around, no matter how slick the interface is. We’ve built guardrails that align with regulatory expectations, but more importantly, we’re trying to make those guardrails invisible to the user, so security doesn’t create friction, but quietly reinforces trust.
For me, the ultimate goal is real-time, business-aware observability, where we can correlate what’s happening in the system to what it means for the user and for the business. That’s the gap we’re working to close. And as we do, we’re moving from firefighting to foresight and building experiences that not only function well, but feel effortless.
–Authored by Harsh Jha, Group Head of Technology, Nuvama