Operations | Monitoring | ITSM | DevOps | Cloud

To succeed in the AI era, customers need fast, easy access to security solutions that can harness the power of agentic AI and deliver business outcomes. They need seamless access to their data for faster threat detection, simpler incident response, and reduced risk. They need technology vendors to work together and not in silos.

The Tier 2 SOC Analyst or the Incident Responder (often hailed as the "Sherlock Holmes of the network") faces an increasingly complex and relentless digital landscape. In a world where analysts are being overwhelmed by alerts, held back by fragmented, manual tooling and inefficient workflows, incident responders are charged with the critical task of identifying, analyzing, and mitigating security threats.

Modern systems don't fail because engineers lack skills; they fail because teams can't see why systems are failing at all or can’t see why they’re failing fast enough. Often, the problem isn't a lack of tools — it's a lack of clear, connected visibility across data, teams, and systems. This is where observability transforms how organizations operate. It's no longer just about keeping systems running.

At.conf25, we took a bold step forward—introducing the concept of MachineGPT, which brings the power of generative AI to one of the most overlooked resources: machine data. MachineGPT speaks the language of machines. Just like ChatGPT learned the grammar of words and sentences to understand questions and respond in human language, MachineGPT can learn the hidden “grammar” of how systems behave through machine data.

The digital landscape has transformed dramatically, and with it, the demands on our systems have grown exponentially. Traditional monitoring tools struggle to provide sufficient insight into complex, distributed, cloud-native environments. Observability is the answer, moving beyond merely knowing "what" is happening to understanding "why" it's happening, and its impact on user experience and business outcomes.

Singapore’s digital economy is growing at a remarkable pace, but with that growth comes a challenge: the nation is on track to need more than a million additional digitally skilled workers by 2026, particularly in cybersecurity, data, and AI. This is not just about filling jobs — it’s about ensuring the country’s long-term digital resilience.

Imagine a future where machines not only perform physical tasks but also learn, adapt, and make intelligent decisions in dynamic environments. This future is rapidly becoming a reality with the advent of smart robots, poised to revolutionize industries from manufacturing to healthcare. In this article, we'll delve into smart robots: what makes these intelligent machines 'smart', how they perform tasks, and how they are reshaping the operational landscape.

In September at.conf25, we announced how Splunk is shaping the future of digital resilience in the age of AI. Agentic AI is rewriting what it takes to build a leading observability practice. As vibe coding gains steam, applications will be built with less human involvement. At the same time, the rise of AI agents demands specialized telemetry to ensure models are performing as intended—aligned to their business purpose and cost.