Operations | Monitoring | ITSM | DevOps | Cloud

WireMock alternatives: pick the one that fits your problem

Picture this. You’re standing up a new service. Cursor or Claude Code wrote most of the controller, and it calls a payment API your team doesn’t own. Now you need tests. The agent is gamely inventing the response shape from whatever OpenAPI doc you fed it (which is a year stale), and the WireMock stubs it just generated are guesses dressed up as JSON. Three weeks later production breaks, the test suite was green the whole time, and nobody knows where to start looking.

How to Set Up an API Server

NinjaOne Field CTO Jeff Hunter shows how to set up an API server. An API server is a framework for securely integrating data from other services into NinjaOne. One example (and next week's video) would be retrieving current CVE data from a third-party vulnerability scanner and regularly importing that CVE data into NinjaOne for visibility and remediation. Chapter Markers.

How to measure developer experience (DevEx) in the AI era

As AI coding assistants dramatically inflate PR counts, commit frequency, and lines of code, the limitations of individual output metrics have never been more apparent. A developer can now produce significantly more lines per session, but higher volume doesn’t guarantee that the code is stable, maintainable, or successfully running in production. GitClear analyzed over 200 million lines of code and found that code churn nearly doubled following widespread AI adoption.

The Checkly Playwright Reporter: Live Demo, Rocky AI RCA & Production Monitoring

Your Playwright tests catch bugs. The hard part is figuring out what actually broke — and sharing that context with your team. This session shows exactly how the Checkly Playwright Reporter solves that: one shared home for all your test runs, AI-powered root cause analysis, and a direct path from failing test to production monitor. María de Antón, PM for Playwright features at Checkly, runs a live demo on a real app with real failures.

Ubuntu Core 26 fleet observability

What is Ubuntu Core? Ubuntu Core is a minimal and strictly confined variant of Ubuntu powering devices around the world. Ubuntu Core 26 now integrates with the Canonical Observability Stack, streaming device logs and metrics to centralized Grafana, Loki, and Prometheus infrastructure, deployable in the cloud or on-premise, without burdening the device's primary workloads.

More Results, Less Busywork: The AI Agent that Works for All

Raise the bar for how your IT team operates by going beyond the AI basics. Ivanti’s agentic AI delivers autonomous, goal-oriented support with multi-agent collaboration. Think fewer menial tasks for IT, more opportunities for faster resolutions and elevated employee experience. Discover how Ivanti Neurons AI Self-Service Agent benefits everyone: IT teams: Reduce repetitive work, get AI-powered guidance and spend more time on meaningful projects that power innovation and business outcomes.

Faster Workflows, Better Knowledge, Smarter Assets | InvGate Updates

New updates are now available across InvGate Service Management and InvGate Asset Management. Watch the video for a quick look at some of our latest additions, including Knowledge Discovery, intelligent CMDB suggestions, and more. We’re also introducing the new AI adoption lifecycle whitepaper and quiz.

Zero to Dashboard with Grafana Assistant and the Infinity datasource plugin

Senior Developer Advocate Nicole van der Hoeven demonstrates how to go from zero to dashboard in a few minutes without using any queries, with the help of Grafana Assistant and the infinity datasource plugin for Grafana. Nicole is using the rawg.io video game database API to visualize games and get recommendations for what to play next!

Episode 11 - Karthik Ravindran Human Choices in an AI Future (Part 1)

#ArtificialIntelligence #EnterpriseAI #AILeadership #GenerativeAI #FutureOfWork #DigitalTransformation #ResponsibleAI #MicrosoftAI #AIInnovation #BusinessTransformation #HumanPlusAI #DataAndAI #Leadership #AIStrategy #EnterpriseTransformation #TheIntelligentEnterprise #TechPodcast #AIForBusiness #FutureReady #InnovationLeadership #AIPodcast #ContextMatters #AITransformation #DigitalLeaders #TomStoneman #KarthikRavindran

Autonomous K8s Optimization Involves Both Compute and Storage Resources - Are You Doing Both?

One of the most powerful capabilities in K8s is the ability to autoscale resources to meet demands, scaling resources up during peak periods to ensure performance, and down again during lower periods to save money. In this joint session, Lucidity and Kubex walk through what end-to-end K8s optimization looks like when you address both layers together. We cover: Expect real examples, not slides full of theory. You’ll leave with a clear picture of where waste is hiding in your environment and a prioritized approach to addressing it.