Operations | Monitoring | ITSM | DevOps | Cloud

Why SRE agents need orchestration, not just more tools

Single agents are a useful starting point for SRE workflows. They are not where the architecture should end. The first version is simple enough: connect an LLM to a few tools, give it a system prompt, and point it at your infrastructure. It can summarize an alert, pull logs, answer questions, and draft a useful next step. Then the workflow gets real. You add GitHub for runbooks, Kubernetes for cluster state, PagerDuty for incident context, Prometheus for metrics, and Mezmo for telemetry.

When your agents hallucinate at 2 am, it is not a model problem

The first time an AI assistant suggests "restart the service" during a live incident and nobody on the bridge can tell whether that suggestion came from a current runbook, a stale wiki page, or thin air, you stop caring about model benchmarks. You start caring about what the agent actually knew, where that knowledge came from, and whether you can trust the chain of reasoning behind it.

Builder in the loop: Henry Andrews on building AURA like production software

An interview series with the people building Mezmo’s open-source agentic harness for production operations. Builder in the loop is a Mezmo interview series focused on the engineers, product leaders, and operators shaping AURA, our open-source, MCP-native agentic harness for production operations. The goal is to get past the polished product layer and talk through the decisions that matter when AI starts interacting with real systems. What should agents be allowed to do?

AURA in Practice: Mezmo's SRE bot, demo walkthrough

A walkthrough of the Slack-based SRE bot Mezmo's engineering team built on AURA, the open-source agent harness, running against Mezmo's own production tooling. Adrian Furlong shows the bot answering questions in a DM with tool calls visible inline, then in a shared channel where it reads the conversation before responding. He opens a fresh PagerDuty incident on camera. The webhook fires AURA, and within seconds, the agent posts a triage note back on the incident and a structured analysis in the dedicated incident channel.

The Journey to Production AI: Five Steps for SRE and Platform Teams

In a recent webinar, The Journey to Production AI, Andre Elizondo walked through what separates a working agent demo from an agent worth trusting on a 2 a.m. page. Live polls during the session put numbers behind a pattern most platform teams already feel. ‍ ‍ Most teams are early. The ones who are further along did not get there by shipping a flashier demo. They got there by treating production AI as a platform problem.

LiveTail: Real-Time Visibility for Active Telemetry

See how Mezmo LiveTail helps teams move from passive log search to active, real-time investigation. In this demo, you'll watch live telemetry stream across services and environments, identify emerging issues as they happen, and use real-time context to troubleshoot faster before signals are delayed, buried, or lost in the noise. LiveTail is part of Mezmo's Active Telemetry platform — built for platform engineers and SREs who need immediate visibility into what's happening across their stack right now, not after the fact.

How Mezmo Uses Active Telemetry for Faster AI Root Cause Analysis

AI-powered root cause analysis only works when the data going into the model is clean, relevant, and structured. In this demo, we show how Mezmo's Active Telemetry approach helps engineers and SREs move from noisy application errors to immediate clarity. Using a restaurant ordering application running in Kubernetes, we trigger a database connection pool exhaustion issue and walk through two ways to investigate it with Mezmo.

See how Mezmo's AI Assistant instantly pinpoints root causes

This video shows how Mezmo's AI Assistant turns noisy telemetry into clear answers when errors spike. By preprocessing data and surfacing only the most relevant patterns, Mezmo quickly identifies issues like database connection failures or resource shortages and delivers actionable recommendations. Watch how AI-powered root cause analysis helps teams troubleshoot faster and with confidence. Mezmo's AI Assistant is built for platform engineers and SREs who need fast, reliable root cause analysis across high-volume telemetry pipelines — without manually sifting through noise.

Meet AURA: The Open-Source Agent Harness for Production AI : Autonomous Incident Response Demo

Watch AURA autonomously respond to a production incident in real time—from building its reasoning context and querying PagerDuty and ClickHouse, to triggering a human-in-the-loop approval with the on-call SRE, to removing the stuck pod and validating remediation. Every behavior is defined in a simple config. AURA is Mezmo's AI-powered incident response agent built for platform engineers and SREs managing high-volume telemetry pipelines.

The Runbook Problem: How AURA Documents What Teams Don't Have Time to Write

Runbooks are rarely missing because teams don't value them. They're usually missing because incident response, follow-up, and platform work compete for the same limited time. By the time an issue is resolved, the knowledge is fresh, but the window to document it is already closing. That gap creates familiar failure modes: over-reliance on senior engineers, slower handoffs, and less confidence for whoever is on call next.