Operations | Monitoring | ITSM | DevOps | Cloud

Internet performance monitoring (IPM) gives IT leaders, operations teams, and network engineers visibility into the ISPs, carriers, and SaaS services their business depends on but doesn't control. In this LogicMonitor and Catchpoint webinar, Callum Brown (presales, EMEA, LogicMonitor) and Brandon Dunlap (solution engineering, Catchpoint, a LogicMonitor company) show how to operationalize IPM, moving from visibility to control.

SCC replaced fragmented tooling, including Nagios, with unified observability the whole team can use. The session covers proactive monitoring, SLA protection, and serving more customers without adding headcount per account. It's made for MSP leaders exploring AIOps for MSPs and observability for MSPs.

Building an agent and not sure how to approach something? Bring it. AURA office hours are recurring working sessions with the people who build it. The team has been talking to people trying out AURA and hearing the same good questions come up more than once. Office hours are the answer to that: a standing slot on a schedule, rather than one conversation at a time. The format is deliberately loose. Nobody is arriving with thirty slides to spend an hour talking at you. The session goes wherever the questions go.

Dynatrace gives engineering teams deep, real-time visibility into every service they run. That visibility is the foundation of every effective reliability practice, and it's exactly the foundation Gremlin is built to extend. Once you can see how your distributed systems behave today, the next step is knowing how they'll behave under failure tomorrow—and to do it before those failures happen.

If an AI model can find a vulnerability for an attacker, the same model should help a defender fix it. In practice, the math doesn't favor the defender. This quick video digs into the real asymmetry AI-powered vulnerability discovery creates: The goal is models acting as tools for defenders, not weapons for attackers. Getting there means rethinking how much ground your team can realistically cover on its own.

We catch up with Franck Pachot, a longtime database community figure who has moved through Oracle, CERN, Yugabyte, MongoDB and, most recently, the PostgreSQL team at Microsoft. Hear stories from Franck's varied career, learn what makes technical content genuinely useful to developers, how PostgreSQL's MVCC and extension model differs from Oracle's, and what's really going on with Microsoft's growing family of PostgreSQL offerings (Flexible Server, Horizon DB, and DocumentDB).

Huxley Kendell demonstrates how Redgate Flyway Enterprise enables safe, governed, and deterministic integration of AI and agentic workflows into database development processes. Local Workflows Huxley showcases how developers can use an MCP server to interact with Flyway Enterprise through local AI tools like Claude. Agentic Workflows The demo presents a future-ready, fully agentic workflow designed for enterprise automation through an autonomous copilot.

Location Management in Skylar One gives IT teams a centralized way to create, maintain, and organize location data, building the foundation for trusted geographic visibility across distributed environments. In this walkthrough, Brian Harding, Director of Product Management at ScienceLogic, demonstrates how to create and manage locations in Skylar One. See how teams can define locations, associate them with the right organizations, and use accurate latitude and longitude data to establish the geographic context needed for devices, services, and Geographic Maps.

Geographic Maps in Skylar One give IT teams a faster, more intuitive way to understand infrastructure and service health across distributed environments. In this walkthrough, Brian Harding, Director of Product Management at ScienceLogic, demonstrates how to create and configure a Geographic Map in Skylar One. See how to create locations, align devices and services, use filters to control what appears on a map, and visualize infrastructure health based on real-world locations.

A big tool result does not have to be a big context cost. AURA moves it to disk and hands the model a pointer plus the tools to navigate what is there. A large MCP tool result can consume or overflow an agent's context window, and on a third-party server you do not control how much comes back. Scratchpad breaks the link between how big a tool result is and how much context it costs: the full output goes to disk, and only the slice the model asks for ever enters the window. Errors always pass through inline, so the model can react to them.