Operations | Monitoring | ITSM | DevOps | Cloud

AI inference and training are terms you'd run into if you have been around software engineering or even just scrolled through the news. Both are integral to delivering the AI-powered experiences we have come to expect from many of the applications we use daily. According to McKinsey, by 2030 inference will overtake training as the dominant workload in AI data centers, making up more than half of all AI compute and roughly 30-40% of total data center demand.

Internet Performance Monitoring (IPM) provides end-to-end visibility into what happens between your infrastructure and your users, across networks and services you don’t own or control. The internet is your network now. Your apps live in the cloud, your users are everywhere, and the systems that deliver your applications and services to them use hundreds of providers, ISPs, and networks beyond your control. In practice, that means infrastructure monitoring is the foundation.

In the modern development landscape, we are seeing a shift in how work is managed. The rise of AI-assisted development and highly distributed teams means that work is moving faster than ever before. However, this increased velocity often comes with a hidden tax: complexity. We are seeing more parallel work streams, more intricate dependencies, and a constant stream of shifting priorities. In this environment, simply moving fast is not enough to guarantee success.

For network operations and security teams, maintaining compliance across device hardware and operating systems is a complex and time-consuming task. At any given moment, your network contains thousands of devices from dozens of different vendors. To keep this infrastructure secure, you must constantly know which devices are approaching end-of-life (EOL) milestones, and which platforms are vulnerable to active common vulnerabilities and exposures (CVEs).

At Bindplane, we iterate fast. One of the most important tools we've adopted across our organization is Claude Code. It helps every team here build solutions to complex problems with both speed and precision. But speed without visibility is a liability. We needed a reliable way to monitor and audit how Claude Code was being used across our team. Luckily, we build the best platform on the market for data in motion.

Built as a globally distributed storage platform integrated directly into the Megaport backbone and co-located with Latitude.sh compute infrastructure, Megaport Storage simplifies how organizations store, move, and access data across distributed environments with a unified infrastructure experience spanning compute, network, and storage. For years, enterprise infrastructure has moved toward abstraction. Compute became elastic. Networks became software-defined.

Modern businesses need infrastructure that can scale as quickly as their demands change. Yet many organizations still struggle with infrastructure that is costly to maintain, difficult to expand, and slow to adapt to new requirements. As applications, users, and data continue to grow, managing resources efficiently becomes increasingly challenging. Cloud infrastructure provides a more flexible approach.