Operations | Monitoring | ITSM | DevOps | Cloud

9 Best Log Management Tools and What They Cost

Most log management tools bill you on log ingestion, the volume of data you send them. That works until your log volume doubles, and the invoice doubles with it. The best log management tools let you control what gets indexed and kept, so growth stops being a budget problem. In this blog, you will see: By the end you will know which fits your volume. Log management is the full lifecycle of your log data, from the moment it is collected to the moment it is deleted.

Custom labels in Grafana Cloud Synthetic Monitoring: New updates for consistency and ease-of-use

Labels are a powerful way to organize telemetry and define policies across Grafana Cloud, helping to streamline alerting, attribution, access control, and more. But traditionally, custom labels in Synthetic Monitoring have worked a little differently: they only lived on a single sm_check_info metric, and Grafana Cloud prefixed each one with label_.

How to right-size the handoff between two agents

model-right-sizer-schema is a Claude Code skill that designs the typed contract between one agent and the controller that dispatches it. Point it at an agent plus its controller and it returns a JSON prescription with typed in/out fields, an exclusion list that keeps raw logs out of the reply, a before/after size delta, then writes the contract into the agent's own file. It picks from nine portable output-shape families, or your repo's own.

Your patch window just went from 30 days to hours

Thanks to AI, vulnerability disclosures are exploding. In mid 2026, we're seeing 130+ a day and climbing, with roughly a quarter already being exploited in the wild before they're even disclosed. The result: security teams that used to have 30 days to respond now feel pressure to issue patches in a few days or hours. This video covers why "are we safe?" isn't a question you get to answer once: That last drill is what separates teams that panic when a real incident hits from teams that already know the answer.

Megaport Collaborates With NVIDIA to Boost AI in Australia

Australia’s home-grown global automated infrastructure platform is part of a cohort of companies with Australian operations that will provide regional businesses and institutions access to NVIDIA accelerated computing and NVIDIA Nemotron open models. It’s a point of pride for all of us at Megaport that we’ve built a global automated infrastructure platform while maintaining our deep Australian roots.

How to Manage Shadow IT in 2026: Detection, Policy And Control

Shadow IT is any hardware, software or IT resource running inside your organization that the IT department never approved, never configured and, in most cases, does not know exists. It covers the file sharing account someone opened with a departmental card, the personal laptop plugged into the office network, and the AI assistant installed on a work machine last Tuesday. None of it is necessarily malicious, and all of it sits outside every control you have.

How Global Businesses are Adapting to an Increasingly Connected Economy

In recent years, advances in technology and digital commerce have made it easier than ever for businesses of all sizes to operate internationally. In an increasingly connected global economy, there are both new opportunities and challenges to be aware of. This post will explore how global businesses are adapting to an increasingly connected economy in 2026. Read on to find out more.

Nvidia Forecasts 70% Revenue Growth as AI Spending Heads Toward $1.3 Trillion

Nvidia has decided to break with its usual practice of providing guidance only for the upcoming quarter and, for the first time, has given investors an outlook for the next fiscal year. The company expects to increase revenue by approximately 70% to $673 billion, which would further cement its position in the Dow Jones index and make it the secondlargest U.S. technology company by revenue, after Amazon. This projection substantially surpasses market expectations based on growth of about 44% and is effectively an attempt to convince the market that the AI boom is far from over. Against this backdrop, Nvidia stock moved higher.

What an "Agent Harness" Actually Is - and Why Raw Model Calls Don't Survive Production

There's a demo that convinces every engineering team that agents are ready: someone gives a model a goal, it calls a couple of tools, and it produces a result that would have taken a person an hour. The gap between that demo and a system real users depend on is enormous, and most of that gap is not the model. It's everything around the model - the layer that decides what to do next, calls tools safely, remembers what happened, asks for help when it should, and records the whole run so you can debug it. That layer has a name: the agent harness.