Operations | Monitoring | ITSM | DevOps | Cloud

In 2025, the average enterprise juggles over 150 SaaS applications, hybrid cloud infrastructures, and a workforce that expects seamless digital experiences—yet most CIOs still rely on monitoring strategies built for the data center era. The result? A $1.5 trillion annual hit to global GDP from downtime and performance lags, according to recent industry estimates. The problem isn’t the tools—it’s the thinking behind them.

AI agents are everywhere in the headlines—and yet no one seems to agree on what they actually are. Ask five companies what it means, and you’ll get five different answers: So yeah—no wonder people are confused. At the highest level, everyone agrees on this: AI agents are systems designed to act on behalf of a user. But that’s where the agreement ends. The big differences come down to how independent they are, how intelligent they really seem, and what kind of work they can do.

Let’s start with a blatant truth: If we tell you that AlertBot offers “superior customer support,” then you are perfectly within your rights to respond with a tepid “meh,” or perhaps an irritated “so what?” Why? Because EVERY COMPANY in this industry claims to offer amazing customer support. Of course, many of them provide mediocre customer service, and a few of them deliver awful customer service.

Cybersecurity threats don’t exclusively come from external attackers—insider threats must also be considered and mitigated. Insider threats come from employees, contractors or business partners who have legitimate access to IT systems to fulfill business functions. They have access to data and systems that are valuable to cyberattackers or would cause reputational damage if disclosed outside the organization. For example, an insider could leak private company information.

Kubernetes, by default, adopts a permissive networking model where all pods can freely communicate unless explicitly restricted using network policies. While this simplifies application deployment, it introduces significant security risks. Unrestricted network traffic allows workloads to interact with unauthorized destinations, increasing the potential for cyberattacks such as Remote Code Execution (RCE), DNS spoofing, and privilege escalation.

Signals is FireHydrant’s modern on-call product that is a replacement for legacy tools such as PagerDuty or Opsgenie. When we began planning Signals, we not only wanted to build a kickass on-call alternative, but also to reset the standard on how much on-call should cost.

Over the past decade, businesses have realized that relying solely on their data centers has limitations. That’s why 38% of organizations turned to private clouds in 2024 to control their data. However, as the need for more flexibility and scalability grew, they started integrating public cloud services. In this article, we’ll explore hybrid cloud computing, what it is, how it works, and why it’s a hot future trend for businesses.

CI/CD pipelines don’t wait. When traffic surges and your artifact platform can’t keep up, it’s not just a few slow requests: builds fail, deploys become backlogged, and engineers lose confidence. We’ve seen it all: 502s from overloaded VMs, minutes-long pulls, and pipelines grinding to a halt. That’s why we built Cloudsmith to scale by default; no one should have to firefight with their registry at 2 a.m.

In our increasingly serverless world, observability isn’t just a “nice to have”—it’s essential. Serverless functions such as AWS Lambda bring incredible benefits, but they also introduce complexities, especially around monitoring and debugging. In a previous article, I provided a quick, practical guide for sending AWS Lambda traces to Grafana Cloud using OpenTelemetry.

Developed by Microsoft in the 1980s, SQL Server is a relational database management system designed to help store, retrieve, and manage data. SQL Server’s strong data processing capabilities, robust security, and high scalability make it an excellent option for enterprise environments that need to process high volumes of advanced analytics, transactions, and more. Data availability is vital for businesses of all sizes, so organizations strive for high availability (HA).