Operations | Monitoring | ITSM | DevOps | Cloud

Running Graylog on Kubernetes has been possible for a while, but let’s be honest: it usually involved a fair amount of DIY. Custom manifests, duct-taped values files, and more than one late-night kubectl describe pod. That changes today. We’re releasing the first-ever Graylog Helm chart for Kubernetes — now available in beta.

A note from Lauren Nagel, Mezmo's VP of Product: At Mezmo, we believe the best observability tools aren't just built for users, they're built with them. Since the launch of Mezmo's AI SRE agent, we've listened and learned from our customers. The feedback and insights have been invaluable in helping our teams refine and enhance the experience. Today, we're excited to share our latest release, packed with improvements and powerful new capabilities that make our AI SRE even faster and more intuitive.

In today's global enterprises, distributed infrastructure is the norm, not the exception. Organizations operate across continents and are driven by customer proximity and regulatory requirements. For the Elastic Stack, this reality often translates into a multi-cluster deployment model, where data is collected and stored in multiple geographically dispersed Elasticsearch clusters. But, why adopt complexity? The decision to decentralize data storage is generally driven by three critical factors.

This is blog 2 in our New Year, New Resolution Series on OTel migrations. Read the first post, "New Year, New Telemetry: Resolve to Stop Breaking Dashboards", here. Most New Year’s resolutions fail because they require a "big bang" change. If your 2026 mandate is to migrate to OpenTelemetry (OTel), the traditional approach is the definition of friction.

Logs are often the first place dev teams look when they investigate an issue. But logs are often added as an afterthought, and developers struggle with the balance of logging too much or too little. As a seasoned developer, you may remember a time when you were asked to investigate an issue and then handed a 200 MB plaintext log file. Three hours and four Python scripts later, you would realize that the problem was in a different component.

Stack traces are great, but they only tell you what broke. They rarely tell you why. When an exception fires, you get a snapshot of the moment things went sideways, but the context leading up to that moment? Gone. That's where logs come in. A well-placed log can be the difference between hours of head-scratching and a five-minute fix. Let me show you what I mean with a real bug I encountered recently.

Today, we’re excited to announce a new integration between Bindplane and Oodle.ai — combining an AI-driven, OpenTelemetry-native telemetry pipeline with an AI-native observability platform built for extreme scale. With Bindplane acting as the control plane for telemetry and Oodle.ai providing AI-powered analysis across logs, metrics, and traces, you get a single, intelligent, vendor-neutral pipeline from raw telemetry to actionable insight.