This is the second of a three-part blog series. Prior to reading this, be sure to check out Part 1, Benefiting from multi-cluster setups requires familiarity with common variations. In your Kubernetes journey, it's highly likely that you'll encounter the need to manage multiple clusters simultaneously.

DevAlert 2.0, which is now immediately available from Percepio, is a major upgrade to our edge observability platform. The upgrade provides much improved diagnostic capabilities, including core dumps for Arm Cortex-M devices. This allows remote inspection of crashes, errors or security anomalies in full detail, including the function call stack, parameters and variables and with source code display.

We are pleased to share a sneak peek of Query Assistant, our latest innovation that bridges the world of declarative querying with Generative AI. Leveraging our large language models (LLMs), Coralogix’s Query Assistant translates your natural language request for insights into data queries. This delivers deep visibility into all your data for everyone in your organization.

Observability is important to understand what’s happening in production. But carving out the time to add instrumentation to a codebase is daunting, and often treated as a separate task to writing features. This means that we end up instrumenting for observability long after a feature has shipped, usually when there’s a problem with it and we’ve lost all context. What if we instead treated observability similarly to how we treat tests?

We're thrilled to share an exciting update from Logit.io. As part of our ongoing commitment to providing cutting-edge observability solutions to our users, we've integrated OpenSearch 2.10.0 into our platform, bringing a host of advanced features to enhance your experience. Let's dive into what's new and how these changes can benefit your observability workflows.

Ever since we launched Query Assistant last June, we’ve learned a lot about working with—and improving—Large Language Models (LLMs) in production with Honeycomb. Today, we’re sharing those techniques so that you can use them to achieve better outputs from your own LLM applications. The techniques in this blog are a new Honeycomb use case. You can use them today. For free. With Honeycomb.

The single pane of glass is perhaps the most enduring and elusive goal of enterprise IT operations teams. When we polled our customers a couple of years ago, out of 184 respondents, 99% of them rated it as important to their business – with 64% indicating “extremely important”. The shared dream is to have: But unfortunately, the single pane of glass has become a bit of myth.