The median outage cost for high-business-impact outages in ASEAN is pegged at US$2.5 million per hour, 32% higher than the median $1.9 million per hour outage cost across 16 markets in the Americas, Europe and the Asia-Pacific region.
This is from New Relic’s 2024 Observability Forecast report, which is based on a survey of 1,700 technology professionals. ETR conducted the research in April and May 2024.
Respondents estimated that engineering teams spend an average of 30% of their time addressing disruptions, which is equivalent to 12 hours across a 40-hour work week.
The most common causes of unplanned outages over the last two years were network failure (35%), third-party or cloud provider services failure (29%), and human error (28%).
The report highlights that costly outages are impacting the bottom line of ASEAN companies, and about a third (33%) are experiencing high-business-impact outages once a week or more.
Additionally, 87% in ASEAN estimated that business-critical application outages cost their organisation at least $500,000 per hour of downtime. However, observability can help mitigate these challenges.
In Singapore, 80% of respondents said their mean time to resolve (MTTR) improved to some extent since adopting observability. This was more than any other country surveyed in the report. This figure was 56% for Indonesia.
While observability adoption is growing, tool consolidation is still an issue. More than a quarter of respondents in ASEAN (27%) learned about outages with multiple monitoring tools, and 22% with manual checks, tests, or complaints. Only 18% learned about them with just one observability platform, with respondents in Singapore being the most likely to do so at 30%.
In spite of this, the desire to consolidate tools is growing. While 20% of ASEAN respondents said they had achieved full-stack observability, this figure was 40% in Indonesia—making it the top country in the region for tool consolidation.
Similarly, 65% in Indonesia had deployed 10 or more capabilities, while only 20% in Singapore had reached that level of adoption. Across ASEAN, a complex tech stack (36%) and lack of budget (30%) were the top challenges preventing full-stack observability.
The biggest technology strategy or trend driving the need for observability in ASEAN was the adoption of AI technologies (38%), followed by the integration of business apps, and migrating to a multi-cloud environment (both 34%). Security monitoring was the most deployed capability in ASEAN (55%), followed by infrastructure monitoring (54%).
Globally, security monitoring was the most deployed capability (58%), while AI-related capabilities deployed included AI monitoring (42%), machine learning (ML) model monitoring (29%), and AIOps (24%).
An additional third are expected to deploy artificial intelligence for IT operations (AIOps) capabilities (39%), AI monitoring (36%), and machine learning (ML) model monitoring (34%) in the next year.
Those deploying these capabilities estimated receiving a higher annual total value from observability and had a higher median return on investment (ROI) than average.
Most ASEAN respondents said observability delivered a substantial return on investment (ROI), with 80% saying they spent $1 million or more on observability per year.
In terms of ROI, Malaysia had a median annual ROI of 302%, the highest among ASEAN countries and second-highest in the Asia Pacific region. Thailand followed closely with a median annual ROI of 300%, while Singapore achieved 258%.
Observability has a wide reaching impact on businesses in this region, with 87% of respondents saying that their organisation recorded at least $1 million in total value per year from their observability investment.
More than two-fifths (42%) said observability reduced security risks, and 37% said it improved system uptime and reliability. Those in ASEAN countries were also more likely than respondents from other countries to view observability as a key enabler for achieving core business goals to some extent (62% compared to 50% overall).
Findings also show that full-stack observability adoption rates varied; there is a strong desire for tool consolidation; finding and fixing outages is time consuming; and business observability is on the rise.