Operations | Monitoring | ITSM | DevOps | Cloud

Many IT teams underestimate the true cost of managing infrastructure themselves. At first glance, DIY tools may seem like a cost-effective and flexible solution — but the workflows you build and manage with in-house tooling reveal a host of hidden expenses, inefficiencies, and risks as your IT scales. While it’s not a new problem, it’s one that’s revealing itself more and more clearly as time goes on.

Let’s face it: managing global data infrastructure isn’t just hard, it’s “I-just-deployed-the-wrong-config-to-prod-again” hard. If you’re a Cribl Admin or Operator working across clouds, continents, and compliance regimes, your to-do list probably reads like a series of increasingly desperate Post-it notes. Sources. Destinations. Pipelines. TLS settings. Proxies. Dev, staging, prod. Repeat. Forever. But what if we told you there’s a better way?

We’re excited to share that Icinga now offers an improved way to view dependencies. With the releases of Icinga DB Web 1.2.0, Icinga DB 1.4.0, and Icinga 2.15.0 today, any dependencies you’ve set up in Icinga will now be visually represented. Additionally, we’re introducing a new enterprise feature called Icinga Dependency Views, available through an Icinga subscription. This component expands Icinga DB Web with even more powerful capabilities.

On May 15th, 2025, Honeycomb hosted Observability Day (or O11yDay) in the London financial district. The skies were clear and the weather was wonderful and we had a huge turnout, from our networking breakfast to the happy hour at the end of the day.

I use Slack daily. It works perfectly fine. Outages rarely happen. Even if they happen, they are resolved quickly. And this is the same for many other tools. But how are they all doing it—Keeping services running and resolving issues quickly? The secret: On-Call Schedules. On-call schedules make sure someone is always available to handle emergencies, so your systems stay reliable.

We ran real-world load tests across seven different infrastructure plans—from Grid to Dedicated Split—using realistic conversion rates, bot traffic blends, and ERP-driven API imports. The findings were clear: performance scales predictably with resources, but only if your code, cache, and configuration keep up. This blog post walks through key results, why API load is disproportionately expensive, and what metrics matter most. How well does Shopware actually perform under load?

The conversations around artificial intelligence (AI) typically revolve around its vast potential: writing applications, automating tasks, or transforming entire industries. However, despite the excitement around AI’s potential, the more pressing issue for many organizations is how to manage the risks of deploying it at scale across the enterprise. This is where AI Security Posture Management (AI-SPM) comes into play.

Innovative brands are gradually shifting toward playable ads to capture audience attention and drive meaningful engagement. A notable example is Toyota's campaign for the 2024 Grand Highlander, which seamlessly integrated interactive content into Uber's platforms. Within the Uber app, users encountered the 'Cargo-Cram' game, an engaging challenge that allowed them to fill the SUV's trunk with various items virtually, effectively showcasing its spacious cargo capacity.

We are excited to announce that Netdata has officially implemented the Model Context Protocol (MCP), joining the forefront of AI-powered infrastructure monitoring.

High-availability (HA) systems form the backbone of modern enterprise applications. In today's always-on world, Java applications are expected to deliver consistent performance with minimal downtime. However, achieving this critical objective is impossible without a well-defined and executed monitoring strategy. A robust Java monitoring approach is essential to ensure resilience, uptime, and peak performance.