Australia & New Zealand top Asia-Pacific in IT stability

New Relic has published its 2026 Observability Forecast for Asia-Pacific, finding that organisations in Australia and New Zealand run the region's most stable IT operations.

The Australia and New Zealand results also highlight a gap between how quickly companies detect major outages and how slowly they resolve them, as broader use of AI-generated code adds to system complexity.

The survey found that 18% of respondents in Australia and New Zealand keep downtime costs below USD $1 million an hour, the highest share in Asia-Pacific. Engineering teams in the market spend a median 23% of their time addressing disruptions, compared with 30% globally and 50% in India.

That lower burden is reflected in outage frequency. Some 39% of organisations in Australia and New Zealand experience a high-impact outage once a month or less, while 31% of organisations in India face multiple outages each day.

The research also found that local organisations use fewer observability tools than their regional peers. Respondents in Australia and New Zealand reported a median of four tools, compared with a regional median of six.

Detection gap

Even so, fast detection does not translate into fast recovery. Around 36% of respondents said they detected high-impact outages in under 30 minutes, and the mean time to detect was 29 minutes, better than the global average of 35 minutes.

Only 17% said they resolved those outages within 30 minutes, which the report described as the widest resolution lag in Asia-Pacific.

One reason may be fragmented monitoring data. Just 41% of organisations in Australia and New Zealand said they had unified telemetry in a single platform, below the global figure of 55%.

Use of other monitoring practices also trailed global levels. The survey found that 32% had deployed distributed tracing, compared with 38% globally, while 24% said they used Kubernetes monitoring.

The figures suggest teams often know when something has broken but lack enough information across systems to quickly pinpoint the source. Demand for a single consolidated platform rose to 37% from 24% over the past year, indicating that buyers want fewer disconnected tools.

AI pressure

The report links some of that pressure to the rise of AI software development. In Australia and New Zealand, 42% of respondents said adoption of AI applications was a primary driver of observability demand, up from 32% a year earlier.

Use of AI coding assistants was also notable, with 47% of organisations using GitHub Copilot and 37% using OpenAI Codex.

Half of respondents said the growth of AI-generated code makes robust observability critical. That points to concerns about code quality, system behaviour and the difficulty of tracing faults across increasingly complex technology estates.

Cost focus

Budget pressure is shaping buying decisions. Cost was named the most important observability purchasing criterion by 41% of respondents in Australia and New Zealand, up from 18% in 2024.

New Relic called that the sharpest rise in cost sensitivity recorded in any Asia-Pacific market covered by the study. At the same time, 28% cited lack of budget as a barrier to achieving full-stack observability, while 32% pointed to complex technology stacks.

Rather than adding more software, many organisations appear to be trying to get more from what they already use. Nearly half, or 49%, said they were prioritising staff training on existing tools.

The study was conducted with Enterprise Technology Research and surveyed 2,575 IT and engineering leaders and practitioners across 24 countries and 12 industries. The Australia and New Zealand findings were based on 150 respondents in executive, management and practitioner roles.

Rob Newell, Senior Vice President and General Manager for APJ at New Relic, said the survey showed a market that has maintained disciplined operations but may now need deeper visibility across its systems. "Australia and New Zealand lead the Asia-Pacific region in operational discipline and running exceptionally lean software environments," Newell said.

"However, a cautious approach to technology investment means that teams are struggling to see into the critical layers of their digital stacks. To overcome this risk-averse mindset and prepare for the complexities of AI-generated code and agentic AI, leaders should transition from a defensive posture of cost containment to a proactive strategy of platform consolidation," he said.