AI SRE Agent Reads Your Notion Runbooks During an Incident: AURA
One integration token, one config file, no code. AURA routes the question to a runbook-reader worker, queries Notion, and answers from what your team wrote.
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Open Source AI Agent for SRE: Why AURA Is Free
The most common question since we started 31 Days of AURA: how do you plan to make money? The short answer is the control plane, not the agent. Mezmo sells an enterprise-grade control plane for running large numbers of agents across large environments, where coordinating across environments, governance, access control, and the efficiency of preprocessing MCP data start to matter. If a hundred people run AURA and three or four of them need that, the model works. The more people running AI agents in production, the bigger the market for the tooling underneath them.
Free Open Source AI Agent for SRE and More: Why We Give AURA Away
Wondering what the catch is on a free, vendor-backed agent? There is not one in the license. AURA stays Apache 2, fully capable, and free to run. If you are weighing an open source tool with a company behind it, the first question is what the catch is. You have seen the project that turns out to be open core, or that is quietly hindered in one key way. This is Mezmo's answer for AURA.
Install an AI SRE Agent in Kubernetes with AURA and Helm
AURA does not have to live on your laptop. Install it into the cluster with Helm and it is still there the next time something breaks. AURA is a fully open source AI agent built specifically for SRE work. Rather than one general assistant, you configure workers: separate agent roles, each scoped to a job like inspecting the cluster.
Add a human breakpoint to your AI SRE agent workflow before it acts
Reaching a tool and being allowed to use it are two separate lists in the config. Put the mutable Kubernetes tools on the second one and each call pauses.
Install AURA to Debug Incidents Using an Open Source SRE Agent
AURA is a fully open-source agentic harness built for SRE and production operations work. In this walkthrough, Mezmo forward deployed engineer Jeff iinstalls AURA on a local desktop, runs `aura init` to generate the config and connect it to an Anthropic Sonnet model, then wires in a Grafana MCP server pointed at his homelab. He hands AURA a live incident: a set of addressable LED lights that stopped responding to Home Assistant.
5 Things to Know About Context Engineering
Software systems are getting better at understanding themselves. The mix of richer telemetry, smarter pipelines, and agentic AI is shifting observability from a passive record of events into something more active and useful. That shift is what we mean by context engineering. We recently partnered with O’Reilly on a report by David Beale that introduces the discipline. Before you read it, here are five things worth knowing.
We built an SRE bot on AURA. Here's what we learned.
PagerDuty fires. You open the incident. Title, timestamp, nothing else. Whatever context exists is in someone's head, in a Slack thread from two weeks ago, or in a runbook nobody has touched since the last reorg. We got tired of that. So we put an AURA agent behind a Slack bot and pointed it at our own production environment.
Life after SaaS: Enabling the System of Context
By: Tucker Callaway, CEO at Mezmo The market keeps saying “SaaS is dead.” That’s probably true, but it’s also incomplete. What’s actually dying is the idea that value lives inside a vendor-controlled black box. The next era is about utilities: unlimited coding capacity and unlimited analytical capability. And if those two utilities are real, then the vendor model has to change.
An SRE agent for production
AI has changed how software gets built. It hasn't changed how software gets run. Most of the AI money in software has gone into the IDE: code generation, copilots, developer assistants, faster pull requests. That work matters. But writing software is one slice of the lifecycle. The harder problem, and the more expensive one, is running that software in production. Production is where systems fail in ways nobody predicted. Incidents don't stay inside one service.