Singapore’s cloud success at risk because it lacks visibility

cloud visibility Singapore
Cloud technology and cloud computing concept with digital white cloud illustration on human shoulders

The pandemic has demonstrated that moving to the cloud is critical to business resilience – supporting customers, partners, and employees in every industry. However, this level of cloud adoption makes monitoring difficult and creates visibility issues that impact user experiences and cause security risks.

Globally – and across Asia Pacific (APAC) – organisations have turned to observability tools to get ahead, gain visibility, and protect the future of their cloud investments.

Singapore, however, according to our research, is lagging behind.

Observability refers to the capability to monitor and troubleshoot across infrastructure, applications, and user interfaces, in real-time and at scale, to deliver reliable services and great customer experiences. It plays a great role in the modern digital enterprise.

Organisations with the right tools in place and are comfortable using those tools are 2.1 times more likely to detect problems in internally developed applications. They also report a 69% better mean time to resolution (MTTR) for unplanned downtime or performance degradation. Needless to say, a strong observability practice gives organisations a sizable advantage over the competition.

Globally, 35% of organisations have adopted observability tools and are working towards gaining a degree of comfort and maturity with them. In Singapore, however, just 15% of organisations seem to be investing in observability tools and building their observability practice.

This is surprising, especially with local organisations expressing less confidence in their ability to meet application availability and performance SLAs. According to the report, just 29% of organisations in Singapore were completely confident versus a 49% global average.

Observability cuts downtime costs by 89.5% annually

We surveyed 1,250 industry professionals globally, who agreed that those who have adopted observability tools are reaping great benefits today. Adoption has helped businesses significantly cut their downtime costs from US$23.5 million to US$2.5 million – depending on the stage of observability maturity at each organisation.

The observability maturity visualisation below, however, makes it clear that there’s still plenty of room for improvement across different maturity levels and factors.

The statistics tell an interesting story. For example, twice as many organisations as last year have begun their journey to embrace observability (beginner-level experience is at 24% in 2022 up from 12% in 2021). Being new to observability, this group is naturally working with a number of vendor-led tools instead of adopting a platform approach, with vendor rationalisation at 35% for beginners in 2022 versus 25% in 2021.

On the other hand, both data correlation (which signifies how much data can be correlated across IT systems and observability tools) and AI/ML adoption (which shows the use of AI/ML within observability tools) saw adoption rise as businesses realised that data & AI/ML are critical to delivering efficiency at scale.

These numbers reveal one global story. More organisations are beginning to invest in observability. They have been piloting various tools to see what can help stitch their organisation’s data and IT systems together, along with powerful AI/ML insights.

Organisations in countries like France and Japan seem to have embraced observability and are thus enjoying great results. They reported that their investments in AIOps technologies have helped them achieve lower MTTR (58% and 68% respectively, versus 43% averaged across other countries). Their achievement sets a benchmark for peers around the globe, such as Singapore where there is room for improvement.

Why is Singapore falling behind and what’s the solution?

Observability brings significant value to organisations, but it is also a field that’s new. As a result, it requires a shift in mindset. In Singapore, this shift in mindset is a challenge, and it partly stems from the fact that the country’s journey to the cloud is on a slower trajectory than the rest of the globe due to legacy infrastructure and systems.

On top of that, moving to the cloud would also mean having to face cloud complexity. Quite a few of the republic’s applications are archaic and need to be rearchitected to thrive on the cloud. A simple lift and shift won’t do, because they need to be refactored to leverage a microservices architecture – an environment where observability delivers the most value.

Singapore also seems slower to adopt DevOps and CI/CD best practices which adds to its challenges when migrating applications to the cloud. This – as a first step – needs to change.

By establishing DevOps and CI/CD best practices, mission-critical applications can be prioritised and modernised. When that happens, it’s bound to do two things. First, it’ll release sufficient financial and manpower resources to explore observability. Second, it’ll create an opportunity to experiment with observability and build use cases that can be championed internally.

Organisations in Singapore that want to accelerate this shift to the cloud, and observability, quickly also need to empower their engineering teams. We see that the purchase process for observability tools looks different in Singapore versus other countries: Respondents in Singapore were less likely to report that IT operations teams have influence (60% versus 73% across other countries).

Observability linked to attracting & retaining top IT talent

With a bigger share of voice, engineering teams can invest in the right tools and build the platforms their organisations need. In enabling this – and accelerating the path to observability – business leaders are able to attract and retain top IT talent.

Our report highlights that 65% of APAC organisations shared that observability tools help to modernise operations with an eye towards better recruitment and retention of top-tier development/operations talent.

According to engineering leaders, since their teams get measured by metrics and SLAs that track their productivity, performance, and impact, the lack of voting power when it comes to choosing the tools they use every day is frustrating. With observability quickly becoming a powerful tool group in their arsenal, leaders need to focus on how they invest in this new-age capability.

For traditional entities like banks and government agencies, the willingness to adopt observability tools with AI/ML capabilities are often a strong indicator to next-generation talent that such organisations are forward-thinking and are a good place to grow their career in the digital world.

By Dhiraj Goklani, Vice President, Observability, Splunk APAC

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