Operations | Monitoring | ITSM | DevOps | Cloud

Engineering teams constantly balance the need for speed and standardization, but achieving both goals at the same time often feels impossible. Developers’ dependence on platform engineers for support with infrastructure and tooling can create bottlenecks for routine operational tasks such as provisioning environments, troubleshooting incidents, and managing deployments.

We’re excited to share that Honeycomb has completed our first-ever acquisition: we’re joining forces with Grit, bringing on board not only a strong team, but also compelling technology that supercharges our ability to deliver on our mission: to bring observability to every software engineer. This is a strategic move that will help us deepen the value we deliver to customers and accelerate our vision for what modern observability can and should be.

Intellyx BrainBlog by Jason English for Mezmo ‍ “Bubble bubble, toil and trouble” describes the mysterious process of mixing together log data and metrics from multiple sources as they enter an observability data pipeline. ‍ Customers demand high performance, functionality-rich digital experiences with near-instantaneous response times.

In recent years, we’ve seen many organizations migrate from legacy incident response tools to Grafana Cloud IRM — our unified incident response and on-call management application hosted on Grafana Cloud — as they look to improve reliability, reduce costs, and consolidate their tooling. To help guide those efforts, we offer several IRM migration tools that allow you to more seamlessly migrate away from those legacy solutions and start using Grafana Cloud IRM.

In a world of managed services, details can often be skipped, overlooked, ignored, or just plain avoided. And in many cases, that's fine. But if you're here, reading this, then I will take it for granted that these things interest you, and I welcome you to join me on this journey of exploration, looking under the hood of two prominent container orchestration platforms on the market: Cycle and Kubernetes.

It started with promise: deploy a chatbot, cut service desk costs, and deliver instant support to employees anytime, anywhere. And many large organizations bought in. But several years into this so-called “chatbot revolution,” the results tell a different story—one of inflated expectations and underwhelming outcomes. It’s time to face a hard truth: AI that only talks is no longer enough.