Datadog targets enterprise risk with AI and automation

Observability company Datadog is positioning real-time risk and compliance management as a key growth opportunity in ANZ, as enterprises grapple with increasingly complex technology environments and the rapid adoption of artificial intelligence.

The convergence of observability, security and data is creating an inflection point for enterprises, particularly in some of Australia's heavily regulated industries, said Roz Gregory, Regional VP for ANZ at Datadog.

"The power of what you have today, bringing together data, observability and security, just hasn't been able to be done before," she said.

The combination could help organisations address three increasingly important priorities: the cost of running technology environments, safety and governance of AI, and the ability to manage security and compliance risks.

Australian enterprises face a particularly complex transition, with Gregory arguing that many organisations remain heavily reliant on traditional on-premises infrastructure while simultaneously adopting cloud, artificial intelligence and increasingly sophisticated security technologies.

"Over the last few years, it's all been about moving to the cloud," she said. 

"It's increasing complexity in the actual tech stack itself. How many things (companies) have got in there. How much does it cost to keep the lights on?"

That complexity is being compounded by AI, adding another layer of technology and risk to already fragmented environments.

The traditional approach of managing technology through multiple specialised tools is becoming increasingly difficult to sustain, argued Gregory.

"While we remain in a tool-heavy environment, we're never going to be able to solve the problem of AI safety and reducing complexity because the threat surface is so broad," she said.

Datadog has expanded significantly beyond its traditional observability roots in recent years, growing from two products to more than 30, according to Gregory.

The company now spans infrastructure and networking, applications, software development, digital experiences, data, security and AI, allowing it to collect and correlate information across a broader portion of an organisation's technology environment.

There is also an increased focus on autonomous operations, where AI is used within an organisation's technology operations to detect, analyse and potentially resolve problems with less human intervention.

Gregory said Datadog's AI capabilities could allow organisations to use natural language to investigate issues, automate remediation and reduce the volume of routine operational work performed manually by IT teams.

The objective is to move enterprises from reactive responses to technology incidents towards more proactive and automated operations.

However, Gregory acknowledged that Australian organisations would not simply abandon their existing technology stacks and immediately adopt autonomous operations.

The cost and risk associated with major technology changes remain significant barriers, while many large enterprises also have substantial outsourcing arrangements that need to be incorporated into transformation programs.

Datadog delivering results for varying customer journeys

Australian retailer Winning Group, parent company of Winning Appliances and Appliances Online, uses Datadog's observability platform to improve website performance, speed up incident investigations and support continued growth across its retail operations.

The company adopted Datadog in part to give employees outside its engineering teams easier access to data and insights about how its digital platforms are performing.

Speaking at Datadog Live in Sydney, Technical Manager at Winning Group, Nick Rivett, said it was looking for a platform that could make technical information more accessible across the company.

"We were looking for a platform that would be easy for a lot of our users to join and have quick access to," Rivett said.

The ability to share dashboards and information quickly with non-developers was a key factor, allowing teams to gain visibility into new features, pricing and other changes without relying solely on engineers to interpret the data.

Observability has become more important for Winning Group as the company continues to grow and handles an increasing volume of customer interactions.

It needs visibility not only into whether its systems are functioning, but also how well they are performing.

"We want to know not just that everything is working okay now, but how quick things are working, and what performance are we giving our customers?" Rivett said.

That is particularly important for Appliances Online, whose website acts as the primary face of the business, with no traditional brick and mortar presence like competitors JB Hi-Fi, The Good Guys and Harvey Norman.

"The face for the brand for Appliances Online is our website," Rivett said, "so we need to make sure that everything there is perfect for our customers."

The retailer is currently focusing on website performance and speed, using Datadog to monitor its digital environment from multiple perspectives, including its servers, synthetic monitoring and customer experience.

Winning Group is also beginning to utilise artificial intelligence within the Datadog platform.

It uses the Bits AI and MCP capabilities, with the AI assistant recently helping identify the cause of an incident that had taken human teams hours to investigate, Rivett explained.

"Bits connected all the dots very quickly, and told us exactly what happened," he said.

"Bits was able to do it in about 10 minutes, which was phenomenal."

Australian surf-technology company Flowstate is using Datadog to automate software monitoring, identify performance bottlenecks and accelerate development as it scales its real-time video platform.

It captures and processes video of surfers, allowing customers to receive clips of their sessions almost immediately after riding. The company relies on real-time processing, making system performance and uptime critical to its operations.

Flowstate Cofounder and CTO, Chris Hausler, said they adopted Datadog from its inception to provide visibility into how its services were performing.

"It just works. It's easy to use," Hausler said.

"You can see exactly what's going on."

Hausler said the ability to detect problems quickly was particularly important because an outage can result in video footage of customers' sessions being missed.

"Any amount of downtime for us is moments not captured," he said.

"If our cameras are down for 10 minutes, maybe you miss four of my waves. Maybe it's my best wave."

AI is utilised to help optimise the performance of its video-processing infrastructure, Hausler explained.

Flowstate has increased the quality and frame rate of the video it captures, moving from 4K at 30 frames per second to 4K at 60fps and then 6K at 60fps.

The resulting increase in data means the company needs to continually identify and eliminate performance bottlenecks.

"Being able to get to the bottom of, 'Could we do this bit faster? What about that? Where are we losing the most time? What's the lowest-hanging fruit?' is really critical for us," he said.