For the most part of my career, the technology industry has been obsessed with “Observability”. We have spent billions on tools designed to give us a clearer view of our stacks, more detailed logs, and faster alerts. I look at the current landscape and see a fundamental flaw in this trajectory. We have built systems that are incredibly good at telling us we are in trouble, but they are still entirely dependent on a human being to get us out of it.
In my view, “Identifying” a problem is only half the battle. If our systems stop at discovery, we haven’t actually built a solution; we have just built a more sophisticated alarm clock. The next frontier for the Indian enterprise is not better monitoring, it is Autonomous Remediation. We must close the loop between seeing a failure and fixing it, effectively creating a “living system” that maintains its own health and corrects infrastructure drift before the first support ticket is even raised.
The Problem with the “Identify” Metric
In traditional IT operations, we measure success by Mean Time to Identify (MTTI). We pride ourselves on how quickly a dashboard turns red after a failure. However, from a product and business perspective, MTTI is a vanity metric. The customer does not care how quickly we knew the service was down; they only care about how quickly it is back up.
The real damage happens in the space between spotting a problem and actually fixing it. That’s where our reputation takes a hit, revenue suffers, and the team’s morale dips. This gap exists because of what I call the Human Bottleneck. Alerts might come in lightning fast, but they still have to wait on a human engineer to log in, figure out what’s wrong, and manually patch things up. If we want to stay competitive in 2026, it’s not enough to just notice problems quickly. We need to focus on cutting our Mean Time to Resolve with smart automation. Instead of patting ourselves on the back for finding fires, we need to build systems that don’t catch fire in the first place.
Moving from Correlation to Causation
The technical architecture required for this shift is fundamentally different from traditional AIOps. Most tools today rely on “Correlation”, if two things happen at the same time, they must be related. This leads to thousands of false positives and the dreaded “Alert Fatigue”. If a CPU spike happens at the same time as a database lag, a correlation-based system will scream about both, leaving the human to figure out which is the cause and which is the symptom.
To achieve autonomous remediation, we must move toward Causation. Our systems need to understand the “Why” behind a failure. This is why we have focused our engineering efforts at iStreet on building a “Causation Engine”. When a system understands the root cause, it doesn’t need to ask for permission to act. It can identify an infrastructure drift, perhaps a configuration change that shouldn’t have happened, and automatically revert it to the “Known Good” state before the end-user even feels the impact. This is the difference between a system that records history and one that actively preserves its own future.
Architecture for a “Self-Healing” Enterprise
Building a self-healing system requires three critical pillars that I believe every Product Head should prioritize:
Stateful Awareness: The system should actually get what “healthy” means for your environment, not just follow some generic standard. It needs to recognize the unique rhythm of your business, the way things really tick.
Policy-Driven Execution: Instead of leaning on fragile scripts that break at the slightest change, we think in terms of policy. You don’t write a script for every little error anymore. You define the state you want, and the system takes care of keeping things inside those lines, on its own.
The Feedback Loop: Every autonomous action must be verified. If the system restarts a service to fix a memory leak, it must immediately verify that the leak is gone. If not, it must escalate. This is “Closed-Loop” engineering that removes the guesswork from operations.
The Jurisdictional Advantage
As we build these autonomous capabilities, we cannot ignore the regulatory landscape in India. Under the DPDP Act, the responsibility for data integrity and system availability is non-negotiable. Many of my peers worry that giving a machine the power to act increases their risk profile.
I believe the opposite. Autonomous Remediation is actually a superior compliance strategy. When a system heals itself within a sovereign, private environment, there is no risk of a human error leading to a data breach during a high-pressure outage. By keeping the “Intelligence” and the “Action” within our own jurisdiction, we ensure that our self-healing protocols are fully aligned with Indian law. We are not sending our system’s vulnerabilities to a foreign cloud to be analyzed; we are fixing them in-house, in real-time. This localized autonomy ensures that even during a crisis, our operational integrity remains under our total control.
Our Vision: End the “War Room” & Experience the “Unified ROC”
The ultimate goal of my product philosophy is to make the “IT War Room” a thing of the past. I want to move our engineers away from the “firefighting” mentality that has characterized IT for decades. There is no strategic value in having highly paid, brilliant engineers spending their nights fixing routine disk space issues or restarting crashed containers.
By shifting from Observability to Autonomous Remediation, we are giving our teams their time back. We are allowing them to focus on building new features and driving innovation, rather than spending their nights and weekends responding to routine infrastructure drifts.
At iStreet, it is about creating a system that is inherently resilient. It’s a system that brings AIOOPs, AISecOPs, and Governance, Risk & Compliance (GRC), on a single observable & actionable pane! A system that doesn’t just “observe” its own decline, but has the life-force to mend itself. We are moving toward a future where the infrastructure is no longer a fragile asset that needs constant nursing, but a robust engine that maintains its own uptime.
Conclusion: The Future belongs to the Resilient
The era of passive monitoring is ending. The complexity of modern enterprise stacks has simply outpaced the ability of human teams to manage them manually. We cannot expect humans to keep up with machine-speed failures.
As leaders, we must demand more from our technology. We must move beyond systems that suggest and toward systems that act. The “Self-Healing” enterprise is not a luxury; it is a necessity for anyone who intends to operate at scale in the coming years.
It is time to close the loop. It is time to move from watching our systems fail to ensuring they never do.
