As businesses across industries embrace digital transformation, the need for real-time observability has never been more critical. Whether it’s the fast-paced food delivery platforms or large-scale AI-driven enterprises, companies are realizing that speed, performance, and reliability are key to maintaining a competitive edge.
In this exclusive interview with SmartStateIndia, Nic Benders, Chief Technology Strategist at New Relic, shares insights into the evolution of observability in India, how AI-driven innovations are enhancing system performance, and why disruptor companies—not just in e-commerce but also in finance, SaaS, and even government sectors—are leading the way in intelligent observability adoption. From reducing MTTR by 90% to leveraging AI for proactive monitoring, Nic discusses how New Relic is helping companies detect issues before they escalate, optimize performance, and control costs—all while fostering innovation from India itself.
How does New Relic define intelligent observability, and what role does AI play in shaping this vision?
Nic Benders: Intelligent observability has evolved through distinct phases. Initially, in the Instrumentation Era, companies competed to monitor more systems, and New Relic pioneered instrumentation across various languages and platforms. As software began embedding its own monitoring, we entered the Data Era, where the challenge shifted to efficiently storing, querying, and analyzing massive telemetry streams.
Now, we’re in the Intelligence Era, where simply collecting and displaying data is no longer enough. Modern IT environments, with thousands of microservices and multi-cloud deployments, are too complex for static dashboards and manual alerts. Intelligent observability means automating insights, helping engineers focus on what truly matters instead of sifting through endless telemetry.
At New Relic, our approach combines AI-driven automation with context-aware intelligence—integrating system architecture, team workflows, RCA documentation, and change records. While AI plays a crucial role, intelligent observability is about guiding users toward the right questions, enabling faster, more effective issue resolution.
With enterprises increasingly relying on AI-driven solutions, how is New Relic adapting to this shift in observability?
Nic Benders: In the past, diagnosing issues was straightforward when software ran on physical servers—you could directly inspect the hardware. But with microservices and cloud environments, visibility became more challenging as applications grew more distributed. Now, AI is taking this evolution further by enabling autonomous decision-making within enterprise systems.
AI adoption is following a similar trajectory to cloud computing. Initially, enterprises treated the cloud as just another data center, moving existing workloads without major architectural changes. Over time, they recognized the real value lay in re-architecting applications to fully leverage the cloud. AI is undergoing the same shift—right now, it’s being applied to existing problems, but its true potential will unfold as organizations design entirely new solutions around AI’s capabilities.
How can intelligent observability help businesses adopt a more pre-emptive and proactive approach rather than relying on traditional logging systems? How is New Relic helping in this regard?
Nic Benders: As organizations mature, their challenges evolve. Instead of managing multi-hour outages, they focus on disruptions that last minutes or even seconds. Take Swiggy or BigBasket in India—when operating on 15-minute delivery windows, a 45-minute performance issue is unacceptable. These companies shift from reactive troubleshooting to proactive prevention, asking: How do we stop issues before they even happen?
Intelligent observability enables this shift by detecting early warning signs before failures occur. By aggregating data across the tech stack and applying AI-driven insights, businesses can identify anomalies that haven’t yet triggered alerts but signal potential risks—helping prevent outages before they impact operations.
What role does AI-driven intelligence play in making observability more proactive?
Nic Benders: AI-driven observability goes beyond traditional monitoring by identifying patterns and deviations before they escalate into major disruptions. It’s not just about logging incidents—it’s about detecting when systems aren’t behaving as expected and taking action before failures occur.
At New Relic, we apply this principle internally, using AI, cloud-native technologies, Kubernetes, and microservices—just like our customers. What sets successful teams apart is their ability to compare expectations with reality, leveraging machine learning and statistical analysis to spot anomalies early.
Proactive observability isn’t just about complex neural networks—it’s about intelligent data correlation that links technical performance with business impact. The best observability platforms don’t just assist during incidents; they empower teams to prevent issues before they happen.
My advice to businesses: Whether using New Relic or another observability solution, focus on three key areas:
- Centralize your data—bring all relevant metrics into a unified system.
- Incorporate business context—understand how system performance affects customer experience.
- Encourage proactive monitoring—analyze data continuously, not just during incidents.
Companies that embrace AI-driven observability will transform it from a troubleshooting tool into a competitive advantage.
How do you see the observability space evolving in India? Beyond Swiggy, can you share other examples of industries where New Relic is driving positive outcomes? Additionally, how are AI-led observability solutions being adopted by Indian companies?
Nic Benders: The observability space in India is evolving rapidly, driven not just by global players but by homegrown tech companies building world-class solutions for Indian consumers. Unlike the past, where much of India’s tech talent worked on outsourced projects, we’re now seeing Indian businesses leveraging cutting-edge technology to solve local challenges—similar to the early days of Silicon Valley.
When identifying businesses that benefit most from New Relic’s observability solutions, two key factors stand out:
- Time-Sensitive Businesses
- Companies like Swiggy and BigBasket rely on ultra-responsive observability because even minor downtime impacts customer experience and revenue.
- In India’s highly competitive market, users have alternatives—if an app underperforms, they switch immediately.
- Cost-Conscious, High-Growth Companies
- HealthifyMe, a leading health-tech firm, partnered with New Relic to optimize reliability while reducing infrastructure costs.
- Their focus wasn’t just on performance; they leveraged intelligent observability to balance cost-efficiency with rapid innovation.
AI-led observability plays a crucial role in both scenarios—enhancing customer experience while helping companies manage costs and scale efficiently. As Indian businesses continue to embrace AI-powered monitoring, observability is becoming a strategic advantage rather than just a troubleshooting tool.
Can you talk about New Relic’s role in advancing AI-driven observability solutions in India?
Nic Benders: Absolutely. India is not just a key customer base for us—it’s also an innovation hub for New Relic. We’ve built a strong presence here, and some of our most exciting AI advancements are coming from our teams in Bangalore.
For instance, I’ve been meeting with our New Relic AI team in India, who are working on our next-gen Agentic AI platform. This platform enables automated troubleshooting, handling complex rollbacks, root cause analysis, and scaling optimizations—tasks that traditionally required extensive human intervention.
Beyond that, I’m also engaging with our teams here who are developing next-gen application monitoring and infrastructure observability tools. This underlines how India is not just adopting AI-led observability solutions but is also creating them.
For us, India represents the future of innovation—both from the customer side and from the engineering and R&D perspective. The rapid digital transformation happening here is a glimpse into what the future of global observability solutions could look like.
