New Relic has released its 2025 Observability Forecast, revealing the high costs of IT outages in Southeast Asia and the growing role of AI in addressing them. The study, which surveyed more than 1,700 IT and engineering professionals across 23 countries, highlights the financial and operational impact of outages, as well as the increased demand for AI-driven observability tools.
Rising cost of high-impact outages
The report found that high-impact outages globally cost a median of US$2 million per hour, or about US$33,333 per minute. In Southeast Asia, covering Singapore, Thailand, Malaysia, and Indonesia, these outages are even more costly, ranging from US$1 million to US$3 million per hour. On an annual basis, the median cost of such outages reached US$165.5 million in the region—more than double the global median of US$76 million.
The research also showed that outages are widespread, with 46% of organisations in the region experiencing high-impact outages weekly. A small percentage (1%) reported facing them multiple times a day. Beyond financial losses, these disruptions divert engineers from innovation, with global respondents indicating that 33% of their time is spent dealing with system failures rather than building new solutions.
AI adoption driving observability demand
The survey revealed that the rapid adoption of AI is a key driver for observability investments. In ASEAN, the use of AI monitoring capabilities has more than doubled in a year, climbing from 39% in 2024 to 83% in 2025. This surge reflects the rollout of AI use cases across the region, particularly large language model-powered and agentic AI applications, which introduce new visibility challenges that traditional monitoring cannot address.
Many organisations are now using AI to monitor AI systems, applying observability platforms in real time to track how models interact with pipelines, APIs, and downstream applications. Observability is increasingly viewed as essential for AI readiness, with 69% of ASEAN respondents stating it helps prepare for and manage AI application development. The figure is even higher in Indonesia (73%) and Thailand (71%).
Challenges and opportunities ahead
Despite the progress, organisations continue to face hurdles. In ASEAN, 39% cited a lack of strategy as their biggest challenge, followed by 36% pointing to complex technology stacks. Tool sprawl remains another issue, with 27% reporting too many tools or siloed data. Data sprawl is particularly prevalent, with 24% of organisations using six or more telemetry data stores—the highest proportion in Asia Pacific.
Rob Newell, Senior Vice President and General Manager Asia Pacific at New Relic, said, “With the role of AI taking centre stage and outages proving to be exceptionally costly, the importance of a robust, intelligent observability strategy has never been more vital for Southeast Asian organisations. While the broad adoption of key observability capabilities like AI monitoring is encouraging, it’s clear that a lack of strategy, data and tool sprawl, and tech complexity are continuing to present significant challenges. Organisations that don’t embrace intelligent observability will find themselves at a severe and costly disadvantage.”
The report also noted strong returns from observability investments. Half of executives and managers in ASEAN said their organisations saw a three- to five-fold return on investment from observability platforms. Top benefits included AI readiness (69%), improved data integration (61%), and stronger collaboration and decision-making (49%).
Technology trends driving observability demand in the region include AI monitoring (61%), integration of business applications into workflows (35%), and adoption of IoT technologies (32%). Plans for greater data integration are also advancing quickly, with 85% of ASEAN respondents intending to integrate operations data in 2025, compared to 50% in 2024. In Singapore, this figure rose to 92%.
The findings underline that observability is no longer optional but a critical enabler for both digital resilience and AI adoption across Southeast Asia.
