Operations | Monitoring | ITSM | DevOps | Cloud

Why artifact management can't stop at npm and Python

npm and Python get all the security attention, but attackers don't limit themselves to your highest-volume formats. A Docker image, a Helm chart, or a Rust crate can all be an entry point. If your security policy is built around the formats you use most, the formats you've deprioritized become the blind spot. This video breaks down why artifact management needs to be centralized across every package format, not just the popular ones.

On Release Days We Wear Teal for release 4.19.1

In this episode, Leon explores some of the new features, functions, updates, and improvements in release 4.19.1, which includes private links, setting a region per workspace, choosing a release channel per workspace, and a look at Output Routers, an incredibly useful (but unfortunately under-loved) feature that’s been around for a hot minute.

How to Integrate Multiple Help Desks Into One ITSM Solution

Managing separate help desks for different departments can make support harder to keep consistent. Each team may have its own processes, tools, and data, while employees have to figure out where to go for help. InvGate Service Management brings those teams together in one platform. IT, HR, Finance, Maintenance, and other departments can manage their services from the same place, with shared processes, centralized data, and a single point of contact for employees.

Multi-Agent Orchestration for SRE: AURA Runs a Model per Specialist

Give one agent every tool and every incident is a question of trust. This one hands each job to a worker that can only reach what that job needs. One AURA configuration defines a coordinator and three specialist workers. Qdrant stores the runbooks, Prometheus measures workload health, and Kubernetes provides inspection and remediation, and each of the three is wired to one worker.

You Vibe Coded an App...Now What?

"Hey, I built this over the weekend. I want to get it in front of customers." And it always hits architecture, security, and infrastructure. Ross Hendrickson, CTO at Inspectiv, calls that gap the chasm. His team crosses it on Control Plane: AI-written code secured, reviewed, and released in a day. Control Plane combines AWS, GCP, Azure and your own hardware into one virtual cloud shaped to your workloads.

When to Use Grafana Assistant vs. MCP vs. GCX: Part 2

When should you reach for Grafana MCP? It’s one of the two “hands” in Grafana’s AI toolkit — and the easy one at that. MCP lets you bring Grafana into the tools you already use, like ChatGPT, Claude, or Cursor, without changing your workflow. No terminal? MCP. Want to stick with your favorite AI tool? MCP. Want easy tool discovery out of the box? MCP. Here’s where it fits, and when to use it — explained by Nicole van der Hoeven.

From vibe coder to enterprise: How Konstruct scales with you

Platform teams spend 6–12 months building the thing Konstruct gives you on day one. Secrets, certs, DNS, cluster provisioning, then doing it all again for the next team, the next cloud. Konstruct is one control plane that scales from a solo builder to a hundred-person platform org, without you ever re-architecting. Climb the responsibility ladder on your terms, hosted app, hosted cluster, hosted control plane, fully self-hosted. You decide where the line sits.

AI Agents Need Guardrails: Building Autonomous IT with Resolve Agent Lab | Agents of IT

AI agents are moving fast. For enterprises, the bigger question is how to make them useful, trusted, and safe enough to take action. In this episode of Agents of IT, Zach Austin and Ian Coppock unpack what it takes to move from experimenting with AI to operationalizing agentic AI across the enterprise. They explore why organizations are racing to deploy AI before defining the problems they want to solve, why governance and scoped responsibilities are critical, and why the real value of AI comes from fixing and orchestrating the workflows underneath it.

Why we stopped hiring for the skills we used to hire for

Six engineers, two QA, a product owner and a Scrum Master used to be a normal squad. With today's tooling, that's bloat. Teams are being rebuilt around three people. Not because the work got smaller — because agentic tooling absorbed the parts that needed all those hands. The engineer's job shifts from writing the code to directing the agents that write it, and owning the outcome that comes out the other end.