Operations | Monitoring | ITSM | DevOps | Cloud

Grafana Campfire - Assistant powered Dynamic dashboards - (Grafana Community Call - August 2026)

Many times, it feels like you're maintaining multiple versions of the same dashboard (with a slight modification), *OR* simply spending more time writing queries rather than actually looking at the actual data? In this Campfire community call, we're taking a deep dive into two things that are reshaping how Grafana dashboards get built: Dynamic Dashboards and the Grafana AI Assistant and showing you how to combine them to go from a blank canvas to a reusable, production-ready dashboard in minutes.

Trace an AI SRE Agent: AURA Docker Quickstart with Phoenix and OTel

You get an answer from the agent and no way to check how it got there. The route it took is recorded, and so is the reason it gave for taking it. AURA emits OpenTelemetry spans, and the Docker quickstart wires them straight into Phoenix. Four services come up together: AURA Web Server as the persistent agent harness, LibreChat as a browser interface for chatting with the agent, Phoenix to receive the spans, and MongoDB to store stateful data for LibreChat. The Compose file arrives pre-configured to point AURA at Phoenix and to enable content recording for the local demo.

Automate Your Entire Incident Response with Skylar Automation

See how Skylar Automation transforms incident response by orchestrating workflows across the tools your teams already use. In this demo, watch Skylar Automation respond to a critical service degradation by automatically creating a ServiceNow incident, paging the on-call engineer in PagerDuty, notifying the Microsoft Teams operations channel, and keeping updates synchronized across platforms. With Skylar Automation, teams can.

When to Use Grafana Assistant vs. MCP vs. gcx: Part 3

When should you use gcx? If Grafana Assistant is the brain and Grafana MCP is the easy hand, gcx is the power hand. Built for AI agents working in the terminal, gcx gives them deep access across Grafana Cloud—so they can pull telemetry, verify code, automate workflows, and access places MCP doesn’t. Coding agents? gcx. Need the full Grafana Cloud surface? gcx. Automating in CI/CD? gcx. Here’s where it fits, and when to use it — explained by Nicole van der Hoeven.

Internet Performance Monitoring: From Visibility to Control with LogicMonitor

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.

MSP Observability: Proactive Monitoring to Autonomous IT with SCC Digital

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.

Recurring Office Hours with the AI SRE Agent Team Behind AURA

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.

Gremlin app for Dynatrace - DEMO!

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.

AI finds vulnerabilities faster than you can fix them

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.