Peter Marelas, Field CTO, APJ, New Relic.

Why does the Indian automotive industry need full-stack observability?

The modern automotive ecosystem is far more complex than what’s visible on the showroom floor. Beneath the surface, a sprawling web of connected technologies underpins everything from manufacturing lines and supply chains to logistics, dealership management systems, and aftermarket service platforms. As India’s automotive sector aligns with global trends—adopting electric vehicles, embracing sustainable manufacturing, and responding to the connected-car revolution—having end-to-end visibility into these layered IT environments becomes critical.

Full-stack observability provides a unified lens across all facets of the automotive ecosystem—cloud-based platforms that power vehicle connectivity services, digital supply chain networks that can anticipate parts shortages, advanced analytics engines that guide manufacturing robotics, and customer-facing applications that handle maintenance scheduling or service diagnostics. Without holistic visibility and proactive intervention, a hidden software bug in a back-end logistics application could halt production lines, an unmonitored performance bottleneck could degrade infotainment updates being pushed over-the-air, and an undetected cybersecurity issue could lead to data leaks impacting both business continuity and brand trust.

By implementing intelligent observability, the Indian automotive industry can maintain resilience amid growing complexities, ensuring production targets are met, supply chains run smoothly, and customer-facing services deliver reliable, high-quality experiences. For example, leading car manufacturer Toyota has used observability to improve the quality of software projects not just within its research and development department, but also the broader company. To support the development of applications related to mobility and digital transformation, the company uses observability to improve the experiences of its users, which supports the functional operations of a multi-cloud environment.

What are the risks of downtime in automotive manufacturing?

In automotive manufacturing, downtime can be costly to finances, operations, and reputation. Modern production lines depend on a seamless interplay of machines, software, supply chains, and data-driven decision-making. Even a short, unplanned outage can halt production, disrupt just-in-time deliveries, and erode trust with dealers and consumers expecting on-schedule deliveries. The State of Observability for Industrials, Materials, and Manufacturing report found that more than a quarter of those surveyed had critical business application outages cost at least $500,000 per hour. This underscores the magnitude of the risk: without full-stack observability, automakers may lose significant revenue, struggle with recovery times, and face escalating expenses as operational issues cascade through the production and supply ecosystems.

How customer experience is adversely affected when businesses in the automotive industry experience downtime?

When automotive brands experience IT disruptions—be it delays in spare parts distribution, failures in remote diagnostic systems, or service appointment booking errors—customers feel a direct impact. Modern Indian car buyers expect services that are not only cost-effective and sustainable, but also reliable and connected. Whether scheduling a maintenance check via a mobile app or receiving timely over-the-air updates to their EV’s battery management system, customers link their loyalty to consistent, smooth interactions. Observability ensures that back-end IT issues are caught and resolved before they ever affect these touchpoints, safeguarding both brand reputation and customer trust.

How observability can reduce downtime in automotive manufacturing?

Observability tools integrate data from operational technology (OT) on the factory floor—sensors, programmable logic controllers, and robotic systems—with the IT systems that manage inventory, workforce assignments, and production schedules. By analysing data holistically, engineers and IT teams can spot early warning signs of machine wear, predict supply chain bottlenecks, and fine-tune quality control processes. This data-driven approach reduces unplanned downtime, supports proactive maintenance, and keeps production lines humming at peak efficiency.

How different is the Indian automotive market and customer expectations vis-a-vis the global market?

India’s automotive consumer is evolving. While price sensitivity remains a factor, there’s also a rapidly growing appetite for environmentally responsible products and robust after-sales support. EVs, for instance, require seamless integrations across charging infrastructure, dealership service readiness, and software-driven diagnostic capabilities. Full-stack observability helps ensure these evolving ecosystems perform reliably—from the apps that guide EV drivers to charging stations, to the logistics systems ensuring spare parts and certified technicians are always available. By leveraging observability, Indian automotive brands can meet their customers’ expectations head-on, reinforcing their commitment to quality, sustainability, and innovation in a competitive global marketplace. 

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