Operations | Monitoring | ITSM | DevOps | Cloud

Kafka migrations get talked about like they're impossible. They aren't. They're a sequence of decisions, preparations, and good compromises - plus a working playbook. In this session, Dirk runs a real Confluent Cloud-to-Aiven migration live. Top to bottom: target Kafka cluster deployment, MirrorMaker 2 setup, replication flow and offset handling, and a staged cutover that keeps producer and consumer downtime to almost zero.

You've seen the updates about our new Shift-Based Schedules update. Join us Thursday to get a deeper look at how you can use the new features to create the schedules you need for your teams!

Will AI replace engineers? Hugo Charré from Cursor argues the opposite. In this clip from the upcoming summit, Hugo Charré (Cursor) explains why the number of engineers is going to grow as we scale agentic systems — and why AI raises the bar for who's on the team.

Thousands of configuration options. Optimisations everywhere. No clear way to track what's running where. Civo Platform Engineer M R Rishi breaks down why running AI on your own infrastructure is harder than it should be and how Konstruct changes that.

Discover how Motadata ServiceOps unifies IT service management, IT asset management, and patch management in a single ITIL-aligned platform. Powered by AI, it helps automate workflows, streamline ticket resolution, and improve service delivery. One platform for service, assets, and everything in between.

Dataspaces and Datasets | The Structured Data Layer for Teams and AI | Coralogix Dataspaces and Datasets from Coralogix: the structured data layer teams and AI were waiting for. Turn a single query into a reusable dataset, share it across teams, and keep dashboards fast as your data scales. In this video: Timestamps: Dataspaces and Datasets are available now in Coralogix. Whether you're building dashboards, running background queries, or powering AI agents with telemetry data, Dataspaces give your organization a governed, high-performance data architecture that scales with your teams.

Kepler is GitKraken's agentic development environment: mission control for running parallel coding agents at scale. Running one agent is easy. Running five of them across three repos is where things break: scattered terminals, no shared view, no idea what's done or stuck. Kepler puts every agent session on one surface so you can plan work, write code, and review what ships without losing track of anything.

The Grafana AI team (Engineers Ivana Huckova and Sonia Aguilar) share what's new in AI Observability this week: a new way to instrument and visualize agent workflows, plus a neat trick for jumping straight from a metric spike to the exact conversation that caused it using Prometheus exemplars. In this episode: We're showing parts of our team meetings to build in public in some small way and give you a sneak preview of what's to come. But not all features we show may make it to production! You've been warned. :)