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Tracing in Istio environments should be seamless, but too often, teams run into a frustrating problem—traces are broken. Requests jump between services, but instead of a complete flow, Coralogix displays fragmented spans. Tracing should work out of the box in those environments. Istio’s sidecars capture spans automatically, so why are traces incomplete? The issue is almost always context propagation, and fixing it doesn’t have to mean modifying application code.

Your tech stack is growing, and with it, the endless stream of log data from every device, application, and system you manage. It’s a flood—one growing 50 times faster than traditional business data—and hidden within it are the patterns and anomalies that hold the key to the performance of your applications and infrastructure. But here’s the challenge you know well: with every log, the noise grows louder, and manually sifting through it is no longer sustainable.

Are your logs helping you, or are they just creating more work? If you’re sifting through endless data but still missing the important details, you’re not alone. It’s a common challenge—but one that can be solved. For anyone managing infrastructure, logs are essential. They show what’s happening, what’s broken, and sometimes even why. But without the right approach, they can easily turn into clutter instead of clarity.

Do you ever wish you had a personal data guru who could magically sift through all your data, spot patterns before they become problems, summarize everything in a way that actually makes sense and propose recommendations? Well, meet AI Agents—the “digital teammates” who do all that without demanding coffee breaks.

There’s an old cliche about sales and jobs to be done - no one wants to buy a drill, they need a hole… actually, they want a home with pictures on the wall. To get to that beautifully designed home, they will buy a drill, make holes for brackets that can support their various artwork and family photos, and progress toward their dream home experience. Similarly, no one wants to buy observability software. They want their mean time to resolve (MTTR) issues to be zero.

So, you're wrestling with Nginx logs, huh? Been there. In fact, I used to spend way too much time hunting down log files until I finally got smart about it. Let me save you the trouble. Nginx logs are like the black box flight recorder for your web server. When everything crashes and burns (and it will), those logs are often the only evidence left to figure out what happened. But first, you need to know where to find them.

OpenTelemetry (OTel) is supposed to be the great equalizer in observability, giving teams full control over how they collect, process, and store telemetry data. It was built to be open, flexible, and vendor-neutral. Grafana Alloy claims to be OpenTelemetry-compatible, but scratch beneath the surface, and you’ll see that, based on our investigations, it is not a neutral OpenTelemetry Collector.