Insights and findings from our daily work

 Artificial Intelligence is only as good as the data it’s built on. While AI promises smarter decision-making, automation, and predictive insights, the reality is that without high-quality, well-labelled data, even the most advanced AI models can fail—sometimes spectacularly. It’s a trap that many organisations fall into: investing in cutting-edge AI tools while overlooking the messy, unglamorous work of data management. 

AI is reshaping industries, promising new efficiencies and insights that can drive competitive advantage. But as businesses race to adopt AI tools, too many overlook a critical ingredient: governance. Without clear frameworks for accountability, transparency, and ethical oversight, AI projects can spiral into costly failures.

Risk is inherent in every business—whether operational, financial, cyber, or strategic. What’s changed in recent years is the way we can anticipate, manage, and even prevent that risk. Artificial Intelligence (AI) is transforming traditional risk management by offering predictive insights, real-time monitoring, and automation at scale. For Australian businesses navigating complex compliance landscapes, fluctuating markets, and cybersecurity threats, AI presents a smarter way to stay ahead of potential issues. 

Software development has come a long way from the rigid, rule-based logic that powered early enterprise applications. Traditional software still has its place—especially when consistency, control, and simplicity are key. But as businesses become more data-driven and demand greater adaptability from their systems, there’s growing interest in machine learning (ML) and its potential to enhance applications.

Artificial Intelligence (AI) is no longer just a buzzword—it’s reshaping industries at an unprecedented pace. According to PwC, AI could contribute up to $15.7 trillion to the global economy by 2030, with Australia alone projected to capture $315 billion of that value. But businesses can't simply 'buy' AI competency—they need to build it thoughtfully if they want a piece of that future growth. 

Kubernetes has become the de facto standard for container orchestration—and for good reason. According to the CNCF (Cloud Native Computing Foundation), 96% of organisations surveyed in 2024 were either using or evaluating Kubernetes. It offers unmatched scalability, flexibility, and resilience. But here’s the reality: Kubernetes isn’t easy. Many businesses rush in thinking Kubernetes will automatically deliver cloud-native utopia—only to end up trapped in a black hole of complexity, spiralling costs, and projects that seem never-ending. 

Kubernetes offers many ways to observe what’s happening in your cluster, but not all tools are created equal. In this post, we compare Grafana’s Kubernetes Pods dashboard to other popular tools like Lens, K9s, and the good old kubectl CLI. If you're new to Kubernetes, this guide will help you understand which tool to use and when. 

Monitoring Kubernetes pods is like checking the health of your application in real time. For developers new to Kubernetes, the Grafana Labs Kubernetes / Views / Pods dashboard offers a visual, easy-to-understand view of what's happening under the hood.  

Microsoft Entra External ID is Microsoft’s next-generation CIAM solution, unifying Azure AD B2C and B2B capabilities into a single, modern platform for managing external users. It offers enhanced security, a streamlined admin experience, and deeper integration with the Microsoft ecosystem.