Operations | Monitoring | ITSM | DevOps | Cloud

As much as I enjoy writing firmware, I am, at heart, a hardware engineer. I love hunting for minutia in chip datasheets. I love fiddling with eval boards, tacking on wires, and reworking nets together. I love flipping through The Art of Electronics, finding a new circuit, and piecing through its operation. This is why, when invited to write for Interrupt, I jumped at the chance to write about a hardware-related topic that’s near and dear to my heart: debug tools.

Social media conglomerate Meta is the latest tech company to build an “AI supercomputer” — a high-speed computer designed specifically to train machine learning systems. The company says its new AI Research SuperCluster, or RSC, is already among the fastest machines of its type and, when complete in mid-2022, will be the world’s fastest. “Meta has developed what we believe is the world’s fastest AI supercomputer,” said Meta CEO Mark Zuckerberg in a statement.

If 2021 was the soft launch of the Decade of the Internet of Things (IoT), 2022 is set to accelerate IoT-related technologies and investments, addressing societal and economic issues. The rollout of 5G, maturing of artificial intelligence algorithms for streaming IoT data, increased computing power at the edge and cheaper/better sensor technology is the “convergence” that has supercharged IoT adoption.

The term “Industry 4.0” originated from a committee of German technocrats who wanted to make predictions about where technology was headed next. And certainly, it fits nicely in the storyline of the initial Industrial revolution with the rise of machines powered by steam and water, the second revolution sparked by the use of electricity, and the third revolution of automated production with robots.

The topic of artificial intelligence (AI) is wide-ranging and extensive, providing what seems like limitless possibilities for the world of work. As such, it’s easy for leaders to get lost in the excitement of implementing an AI model for their enterprise.

Observability has gained a lot of momentum in the past year, be it full stack observability or data observability. Modern complex IT systems using clouds, microservices and serverless are easy to develop and deploy but extremely difficult to observe. These systems generate tremendous amounts of data and need an automated way of handling the volume. The next era of delivering customer experience is underpinned by the full stack observability capability.

Over the years, this biweekly letter has provided me with the opportunity to fully and fairly document just how much free time college students can have if they try. My college roommates tried really hard.