Operations | Monitoring | ITSM | DevOps | Cloud

From the first alert to the root cause, without leaving the page. TL;DR: Investigating an incident is a series of quick questions, each one leading to the next. Until now, Explore made you stop between questions to translate them into syntax, switch modes or rebuild a chart. The new Explore lets you go straight from one question to the next: one workspace, any dataset, any team, any way you like to ask. Here’s what that looks like on a real night on call.

We set out to understand how customers were using Coralogix from outside the web app. Olly answers questions about a system in plain language. Coding agents query logs, examine traces, read metrics and configure the platform through the Coralogix CLI and MCP server. We wanted to see how much of this was becoming part of everyday work. In the week of 20–26 October, 39% of Coralogix sessions included Olly, the CLI or MCP.

AI has made life easier for us developers. Dozens of AI tools are getting more advanced every day, shortening and speeding up the development cycle. Converting an idea into a concrete MVP is faster than ever before. Intelligent models turn your ideas into a working project with just a few prompts. End users or product owners can see the application, use the beta version, and give feedback on the spot.

Having spent significant time working with the Network Observability Deployment Engine (NODE), I can confidently say that modernizing network observability does not have to feel like black magic. NODE simplifies how we deploy, scale, and manage complex network observability environments. Whether you're working with Kubernetes for the first time or streamlining an enterprise monitoring stack, NODE brings structure and clarity to the setup process. At its core, NODE relies on two main building blocks.

How long does it take your service desk to rule the proxy in or out when a user says a site won't load? The proxy carries every outbound web request in most companies, and it still tends to be checked last. So service desks guess, even though the proxy has already logged what happened to that request. For a lot of those companies, the proxy is Squid. It has cached pages and enforced web policy for close to three decades, and it logs every request it touches.

If your Wi-Fi keeps slowing down or dropping connections, checking whether your access points are online won't tell you much. You need to know what's causing the problem, whether it's weak signal strength, overloaded access points, or too many connected devices. Wireless network monitoring tools help you track these issues, monitor access point health, and spot problems before they affect more users.

When we first introduced people to Aiven Runtime, before it even had that name, we kept getting asked: "Can we schedule things?" If you come from a Unix background, that tends to cause a reflexive reach for the cron tool, which provides basic scheduling at fixed intervals. But if you've spent more time with distributed software, you're more likely to think of Apache Airflow, which can do a lot more (although, yes, you can use Airflow to schedule tasks at fixed intervals if you want).

Open the Dashboard Library on a Logs stack that already receives Nginx logs and a few cards come up ticked with a green Data detected badge. Others in the same pack sit there unticked. That isn't random. Before it shows you anything, the Library checks what your stack actually holds and pre-selects only the dashboards it expects to fill.

Q3 was a big quarter for Papertrail. You can now ask questions about your logs in plain English, explore structured logs by field, inspect any single log event in detail, and archive to your own S3 bucket with a setup that keeps you in control of access. We also shipped a round of smaller improvements that make sending logs and searching them faster and smoother. Here is a quick overview. The two Preview features have their own deep-dive articles, linked below.

When evaluating AI models for observability, generating a plausible query or explanation isn't enough. Teams need to know whether an agent's conclusions are supported by telemetry, whether its changes to dashboards actually work, and whether it can deliver reliable results consistently. This is why we built o11y-bench, Grafana Labs' open benchmark for evaluating AI models on observability and SRE tasks. And today, we're excited to share two updates.