Operations | Monitoring | ITSM | DevOps | Cloud

Builder in the loop is a Mezmo interview series with the engineers, product leaders, and operators shaping AURA. Each installment looks past the product layer to explore the decisions, tradeoffs, and lessons involved in building agents for real production work. This installment features Mike Shearer, the engineer who built AURA and, until recently, its only developer. AI agents are easy to believe in when the task is small.

Coralogix Real User Monitoring has spent years collecting full-fidelity user sessions: every session and event processed in stream, without sampling and without prior indexing, at rest in cloud object storage you own. Today that data does a second job. Product Analytics brings heatmaps, funnels, and pathways to the RUM sessions you already send, with no second SDK to install. One dataset now answers what your users did and why it happened.

Deployment is not the end of shipping your application. From time to time, you will get errors that you will need to attend to. Without a good method of catching errors or logs in general, you could end up with uncaught issues that might cost you valuable customers in the process. In this article, you will learn how to catch logs for an application deployed on Fly.io. You will learn how Fly.io logging works, then learn ways to handle logs natively on the platform.

AI agents are only as effective as the context they can access. The problem is that most of that context lives outside your observability platform.

By the time an IoT device shows up in an incident review, it has usually already done its damage. Not the dashboard-gap kind. These devices are load bearing. They sit in the control path of substations, haul trucks, pump stations and cold rooms, so when they go blind the blast radius gets measured in tripped relays, spoiled stock, and unplanned outages rather than in missing datapoints.