Operations | Monitoring | ITSM | DevOps | Cloud

When an AI Agent Goes Rogue, Who's Responsible? | Civo Navigate London

AI agents are taking real actions in production. So when one misbehaves, who's accountable: the model provider or the company running it? David Sullivan explains why a regulated bank can't outsource accountability to an AI lab. James Faure shares how Clairo AI uses hypothesis testing and quality gates before any agent reaches production. Dr Rosemary Francis argues that guardrails which amount to a strongly worded letter won't survive. What agents need are genuine sandboxes and a limited blast radius.

Autonomous Patch Management | Ivanti

New vulnerabilities emerge every day and thousands of endpoints change constantly — it's a continuous race against time. Patching isn't just deployment; it's manual handoffs and incomplete visibility that leave organizations exposed. This video shows how Ivanti Neurons for Patch Management provides immediate, authoritative insights into your IT estate so you can close security gaps faster.

Building an AI Assistant That Actually Understands Your Incidents

When production breaks, the clues are everywhere but the story is scattered. RUM sessions, APM traces, metrics, and logs allow Datadog to tell you part of the story. What’s missing is your service ownership quirks, your team's conventions, or the three-year-old workaround buried in a comment that explains why a certain endpoint behaves the way it does.

Democratizing Incident Response with AI at Riot Games - SRE Track

Senior engineers are the pillars of SRE programs—not only do they have the leadership to manage incidents well, they also have the tribal knowledge to understand the technical causes of tricky issues. But when the know-how is confined to a few individuals, it greatly limits the effectiveness of your SRE team.

Dismantling Datadog's Monolith with Agentic AI - Developer Track

AI can write code, but how does it do with a large, organically built codebase with years of development? Datadog’s monolithic webapp had significant scale and support challenges, so we knew the time had come to break it up. But when the code has been written, revised and tweaked so many times (as we keep adding new features and capabilities), by so many teams, that becomes much harder.

Agentic code is changing how we think about code quality

Discover how Harness Builds combines Test Intelligence, code coverage, and quality signals to help developers and AI agents validate changes faster and improve code quality. AI has changed the speed at which we can write code. Developers can move from an idea to a pull request faster, agents can work through changes autonomously, and the amount of code moving through development pipelines is only going up. But writing the code is only the beginning.

Introducing DojoAI Credits: Flexible, predictable AI pricing built for scale

AI agents are quickly becoming the first responders on the most sophisticated SecOps and DevOps teams, pulling threads on a threat or making sense of a flood of telemetry before a human even logs in. But most AI pricing hasn’t caught up. Token-based models leave you burning through usage with no visibility into what’s driving the cost, while per-seat caps ration access like AI is still a nice-to-have instead of core to how your team operates.

The Root Cause Agent: Bring an agentic approach to observability

For years, engineering teams have faced the same challenge during incidents: the systems generating alerts are becoming more complex, but the investigation that follows is still largely manual. Monitors are good at telling us that something is wrong. The harder question is why. When an alert fires, an engineer still has to work out where to look, which signals matter, what hypothesis to test, and how the evidence across logs and metrics fits together.

AI at scale: are your foundations ready?

What does it take to move from AI experimentation to real-world adoption, and where does sovereign AI fit into the picture? In Episode 2 of Season 2 of Perspectives from the Edge, Andrew Dutton,Enterprise Sales & Marketing Director at SCC, joins Pulsant’s Wendy Shearer to explore the challenges businesses are facing as AI moves from experimentation into production and scale.