Operations | Monitoring | ITSM | DevOps | Cloud

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.

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 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.

We rebuilt our post-mortems from the ground up. In this video, Pete and the engineering team talk through how they built it: the decisions they made, the problems they were solving, and what it took to ship AI-native post-mortems.

Most “application issues” don’t start in the code. They start somewhere deeper in the delivery system. If you can’t see beyond the trace, you’re only seeing half the story.

Bitbucket Pipelines lets you build reusable pipelines and share them across repositories. These reusable, shared pipelines need a way to share artifacts. Otherwise, we’ll have to repeat expensive steps such as downloading and installing dependencies and building the application code. You can now specify an artifacts section for child pipelines, with upload and download keywords. Artifacts listed under upload will be moved from the parent pipeline into the child pipeline, where they can be used and potentially modified.

This on‑demand product demo shows how N‑zo supports MSPs looking to simplify operations and scale more efficiently. Watch to see how N‑zo brings key workflows together, reduces operational friction, and helps teams gain better insight into their business. The demo highlights practical scenarios designed to support growth, consistency, and operational clarity without added complexity. Ideal for MSP leaders and operations teams who want a clearer, more streamlined way to manage their business.