Operations | Monitoring | ITSM | DevOps | Cloud

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Introducing AI Platform Traffic Visibility in Kentik

Generative AI has quickly emerged as a distinct over-the-top (OTT) traffic category, yet service providers have lacked the visibility to track it. Kentik now identifies traffic from 35+ AI services across 28 providers, showing operators how it enters their networks, where it’s growing, and what it costs to deliver.

Agent Guard: Control AI Assets Before They Become Shadow AI

A developer on your team just told Claude Code to connect to a new MCP server, the protocol coding agents use to reach organizational tools and data. Nobody in security reviewed it. Nobody in security even knows it happened. For two-thirds of enterprises, the primary obstacle to scaling agentic development isn’t budget or headcount — it’s security risk.

Your AI agent can now set up uptime monitoring. No signup required.

We’re happy to introduce you to the first agentic uptime monitoring setup! Now your AI agents can continue their coding, testing, and deploy flows into setting up the monitors, including a free account. The agent submits your site’s URL and your email, you confirm with one click in the email you receive, and you have a working monitor plus a free account. No registration form, API key, or dashboard configuration needed.

Who Owns Deployment Governance? Structuring Accountability in the AI Era

In this series, we have talked about how generative AI is shifting the landscape of software creation. In The New Software Creator, we explored how AI expands who can write code. In When Anyone Can Build Software, Deployment Governance Is What Keeps It Safe, we looked at why the deployment pipeline is the ultimate control point. Finally, in Security at Scale: What Changes When Everyone Can Deploy, we dug into the technical realities of patching, container hygiene, and identity management.

Our 3-month AI roadmap - the future of smart dashboards

AI is set to transform our technology landscape. For many of us working in software, it already has — developers are now writing more code, building more features, and deploying more applications, faster. For the teams supporting IT and software services that means more applications to support, across a greater breadth of technologies, and with more complexity (that is probably less well understood by the developers who created it). Your operational tooling needs to keep pace.

Your AI Agents Can Take Action Now. Can You Prove They Should Have?

Enterprise AI agents clear every demo and pilot, then hit a compliance wall. The gap isn't technology—it's architecture. Discover why governance must sit inside the execution flow across six control points, not bolt on afterward as an afterthought at input and output only.

How AI Agents Are Changing ITSM Faster Than We Think | Motadata Webinar

AI is transforming ITSM beyond co-pilots with autonomous AI agents that can understand, decide, and act. In this webinar, discover how AI agents are reducing manual workloads, accelerating incident resolution, improving service quality, and enabling intelligent service operations. Learn real-world use cases, key implementation strategies, and how organizations can move from reactive support to proactive, AI-driven IT service management. Watch now to explore the future of smarter, faster, and more efficient ITSM.

Software is a team sport. AI tooling forgot that - Upsun Product Highlights

AI tools made individual developers faster. Teams still aren't shipping more product. That gap is the whole reason Upsun Dispatch exists. In this Product Highlights conversation, Kateryna Dvornichenko, a product manager at Upsun who has spent the past several months building Upsun Dispatch, explains why the tooling market got the unit wrong. Her take: "Making software is a team sport." We get into.

Model Rightsizer: the agent that stops your other agents from defaulting to Fable

Model Rightsizer is an open-source Claude Code sub-agent from CloudZero that scores each task on capability need versus cost pressure, then routes it to the smallest model that can handle it. In its first week, it cut Opus spend 75% while shifting 234x more work to Sonnet. Every Claude Code agent you run has to answer a question it usually never gets asked: does this task need the smartest model available, or are you paying Fable prices to rename a variable across three files?