Observability drives digital trust by uniting resilience, security, and insight.
Author: Abhijit Chakravarty, Executive Vice President – Networks & Cyber Security, Kotak Mahindra Bank.
At Kotak Mahindra Bank, we operate in a high-stakes, high-frequency environment where resilience is non-negotiable and latency is unforgiving. In such an environment, observability is not a post-incident diagnostic—it is a first principle of digital trust. It shapes how we design, secure, and operate every layer of our digital stack, from network infrastructure and application workloads to transaction flows and cyber-defense systems.
One of the persistent challenges is that observability is still treated as a back-office function—owned by a few engineers, understood mostly at the technical layer, and invoked only when something breaks. That model no longer works. For us, observability has evolved into a strategic discipline, as fundamental to reliability as it is to security.
We are building observability into the system at design time. It’s not about monitoring endpoints or tracking latency in isolation. It’s about stitching together real-time, contextual telemetry across infrastructure, APIs, application logic, and user behavior—so we don’t just detect anomalies, we understand them in the context of business workflows.
This becomes especially critical in hybrid environments like ours. We run systems on-premise, in private cloud, across SaaS, and through mobile and web channels. If a payment fails, we want immediate clarity: Was it a network flap, an API timeout, a rate-limit event, or a malicious action? And we want that insight in real time—with enough context to act, not guess.
Security is integral to this fabric. Observability feeds our cybersecurity posture not merely as log data for forensic analysis, but as continuous signals for threat correlation, anomaly detection, and policy enforcement. If a high-risk user suddenly triggers an unusual transaction pattern, it must appear not only as a SOC alert but also as an anomaly in our service-health view. System degradation and security events often masquerade as each other, and observability bridges that gap.
We are also driving tighter integration between technology operations and business observability. It’s no longer sufficient to know that CPU usage spiked—we need to know which customer journey was disrupted, what revenue impact it created, and whether it introduced regulatory exposure. Achieving this requires more than tools; it requires a mindset shift across teams.
Of course, scaling observability brings its own complexities. Telemetry volumes are massive, and we constantly calibrate what we collect, how we store it, and who gets access. We strive to avoid alert fatigue without risking silent failures, and we need systems that can intelligently filter noise while remaining sensitive to real risk. Ultimately, our goal is to make observability not just the eyes and ears of the enterprise, but its central nervous system. In a world where systems are too complex to watch manually and too critical to fail quietly, we need observability that is intelligent, secure, and aligned with how the business thinks.