Bengaluru, November 04, 2026: New Relic, the intelligent observability platform, today released its 2026 Observability Forecast: India Edition, the industry’s most comprehensive report on the state of observability in the AI era. Drawing from a global survey of 2,575 engineering and IT leaders, this regional report isolates 500 respondents in India — the single largest country cohort surveyed globally. Notably, the data reveals a stark paradox: despite India leading the world in advanced OpenTelemetry standardisation and AI agent monitoring, Indian enterprises suffer the heaviest operational and financial strain, losing an average of $3 million per high-impact outage.
Advanced AI adoption outpaces operational maturity as developer firefighting doubles
India’s enterprise landscape has rapidly emerged as one of the most AI-forward markets globally, and they are aggressively deploying advanced observability tools to keep pace with hyper-growth digital infrastructure. Local organisations are successfully removing the AI agent blind spots plaguing the rest of the world, with 56% actively monitoring agents in production compared to a 35% global average. This extends across all AI adoption, with India leading in AIOps at 54% compared to 36% globally, and machine learning model monitoring at 57% compared to 38% globally. In spite of this sophisticated approach to tooling, persistent reactive troubleshooting continues to squeeze engineering capacity. Half of Indian developer time is now lost to addressing system disruptions; up from 35% last year and nearly double the global median of 30%. This shows that when rushed into production without operational discipline, new software can cause challenges rather than make engineering lives easier.
Indian enterprises endure the world’s steepest downtime costs
The cost of a single high-business-impact outage in India has climbed to an average of $3 million, driven by an hourly downtime cost of $2.43 million, or $40,500 for each minute systems remain offline. Rather than isolated events, severe outages have become a regular operational disruption, with 61% of Indian organisations experiencing high-impact outages weekly or more, and nearly a third (31%) experiencing them multiple times a day–a tenfold increase from 2025.
Detection and recovery windows widen as complex stacks obscure root causes
As digital environments grow more complex, Indian IT teams are taking longer to spot and repair critical failures, allowing issues to linger and compound financial damage. The average time to detect a high-impact outage has stretched to 55 minutes from 41 minutes last year, while the average mean time to resolve (MTTR) of these severe incidents has risen to over an hour. This recovery lag is closely tied to the vulnerabilities of highly complex systems, where third-party cloud failures, software updates, and network disruptions are the primary outage triggers. Notably, 32% of Indian organisations point to security failures as a frequent cause of downtime, representing the market's widest operational gap and running nine percentage points higher than the global average.
India dominates global OpenTelemetry standardisation but misses the correlation payoff
India dominates global OpenTelemetry standardisation, with 42% of respondents fully standardised — nearly double the 22% global average. However, highly fragmented software stacks are preventing local enterprises from maximising this advantage. With an average of six monitoring tools per organisation, standardised telemetry is trapped in isolated silos. Consequently, just 20% of Indian leaders report that AI-assisted observability has significantly improved their event correlation (trailing the 27% global average). While OTel unifies the data, tool fragmentation prevents AI from effectively analysing it across the stack.
Agentic AI monitoring drives strongest return on investment globally
India leads the world in agentic AI visibility, with 56% of organisations actively monitoring production AI agents (compared to 35% globally). This proactive approach directly drives India's high observability returns, where the share of enterprises realising 3-5x ROI nearly doubled year-over-year (19% to 35%). Globally, teams that monitor production AI agents are more than twice as likely to achieve 3x or more ROI than those running unmonitored systems. The commitment to proactive visibility has significantly decreased wasted tech spend, with the share of Indian enterprises yet to see a financial return or failing to track ROI collapsing from 12% last year to just 6% today. This high return is likely why Indian buyers are not as sensitive to pricing, with Indian CIOs prioritising AI/ML-powered vendor features at 39%, far ahead of cost at 25%. This shows that confidence in the ROI of advanced tooling has made cost a secondary consideration.
"India's digital economy is scaling at an extraordinary pace, but this high growth has outpaced operational discipline, leaving engineering teams to pay a heavy reactive troubleshooting tax," said New Relic Senior Vice President and General Manager for APJ Rob Newell. "While India's proactive stance on monitoring AI agents has positioned it to lead the world in financial returns, tool sprawl is still capping the upside. To expand on the 35% of Indian respondents already capturing a 3 to 5x return on their observability investments, businesses must transition from disconnected point tools to a unified platform. Consolidation is improving developer productivity and unlocking greater agility.”
The 2026 Observability Forecast: India Edition is available today. Read the full report.
Report Methodology
New Relic partnered with Enterprise Technology Research (ETR) to survey 2,575 IT and engineering leaders and practitioners across 24 countries across the Americas, Asia Pacific and Europe and in 12 industries. 500 respondents were from India. Respondents span executive, management, and practitioner roles. The survey was conducted in April and May of 2026.
