Operations | Monitoring | ITSM | DevOps | Cloud

With all the rapid advancements in machine learning and AI, it can feel like we’re constantly playing catch-up. Over the last two Civo Navigate conferences, Berlin 2024 and San Francisco 2025, Civo brought together leading experts to discuss the future of AI, machine learning, and the growing challenges and opportunities for developers and businesses.

Lately, there has been a growing buzz around the concept of “Vibe Working,” where teams are leveraging AI to dynamically share, develop, test, and transform “fuzzy” ideas into something useful in real-time. I view this approach as one of the next significant evolutions in our professional and technological landscape. Reflecting on my own journey in technology, I’ve observed how the pace of innovation and collaboration continually reshapes our daily workflows.

AI spending continues to accelerate. In 2025, experts project that companies will collectively spend about $644 billion on generative AI alone — a whopping 76.4% increase from 2024. This puts it a mere $79 billion behind the public cloud as a whole, signaling the most seismic interval of new infrastructure investment since the dawn of the public cloud.

Most databases were built for a slower world, one where data waited, systems pulled, and answers came later. But today, data flows. It triggers real-time decisions, powers models in motion, and spans every cloud layer. This shift demands a different kind of database—one built to execute, not just store. Microsoft has answered that call with SQL Server 2025.

Data is the lifeblood of businesses the world over, from the smallest startup to the largest enterprise. Making sure that it’s available when you need it, secured for authorized use, and recoverable from faults is vital to operating data platforms, no matter where your business is on its cloud journey. This can only be achieved by putting the right data into the hands of the right people, in a timely way, to make the right decisions about how to manage that platform effectively.

AI to streamline software development workflows, from idea to operations.

We’re entering a new era at CloudZero, and we’re coming in hot. This week, we’re not just launching a new feature. We’re taking a major step forward in our mission to make cloud cost efficiency a seamless, engineer-first, business-aligned reality. My team and I are thrilled to introduce CloudZero Optimize, our smartest, most action-oriented optimization solution yet.

When requests slow down across your microservices, tracing helps you understand where time is spent. Jaeger and Zipkin are two popular tools for distributed tracing, built to answer a simple question: where did the request go? If you're choosing between them or just exploring options, this guide breaks down the differences and when each one might be a better fit.

Everything looks fine—dashboards are green, logs are quiet. But users start reporting slow response times. No errors, no traffic spikes. Just a general slowdown. It’s a common situation. Not all problems show up as crashes or clear failures. Sometimes, performance degrades quietly, and standard metrics don’t catch it early. But that's where Prometheus alerting can help, if you're monitoring the right signals.

Last week, hundreds of engineering leaders, SREs, platform teams, and developers joined us for Summer Scoop 2025, our biggest launch event yet. The way that we think about our product development at Cortex revolves around all the different types of users who are in our product every day.