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Introducing AI Analytics Reports in InvGate Service Management

Most teams can confirm their AI features are turned on. Measuring how often employees use them, which requests get resolved without agent intervention, and where AI is helping support teams work more efficiently is a different question. In InvGate Service Management, those capabilities live in AI Hub, a set of built-in AI features that includes the Virtual Service Agent, AI-assisted ticket resolution for agents, automated knowledge generation, and more.

How to Measure AI ROI in IT Service Management

A service desk manager launches a virtual agent in January. By March, chat conversations are climbing, ticket volume hasn't changed much, and the monthly report doesn't explain whether the investment is delivering value. AI rarely produces a single number that proves its return. The gains accumulate across thousands of support interactions, making measurement just as important as deployment.

Outsourcing Web Development Benefits and Risks: A Practical Breakdown

Most articles about outsourcing web development read like a sales brochure: cheaper, faster, done. That's not wrong, exactly - it's just incomplete. Handing part of your codebase and your deploy pipeline to an outside team is a real trade-off, not a free win, and the teams that get burned by it usually aren't the ones who chose to outsource. They're the ones who never sat down and weighed the upsides against the risks before settling on a web development outsource partner. This piece is that conversation - the benefits worth taking seriously, the risks that actually bite, and what to do about both.

Trace without traces

A customer emailed on a Tuesday: checkout hung for ten seconds. I opened our tracing tool, punched in the time window, and got nothing. The trace was sampled out. We keep 1% of traces, like most shops with real traffic do. The one request that actually mattered was in the 99% we threw away. I spent twenty minutes admiring our observability stack before admitting it couldn’t answer a first-grader’s question: what happened to this person? Here’s what I know now.

ACP vs MCP: What's the difference for agentic coding?

An AI coding agent holds many conversations at once. Not only is the user prompting it, the agent also talks to the IDE, showing diffs and asking before it touches a file. At the same time it talks to tools, pulling a failing build or querying a database. Two open protocols standardize those conversations. This guide compares ACP vs MCP in practical terms: what each protocol does and when each applies. ACP (Agent Client Protocol) connects a code editor to an AI coding agent.

Autoscaling Checkly Private Location Agents in Kubernetes with KEDA

Monitoring load is not always steady. A team might add a new batch of checks or run several ad hoc tests during a rollout. When that happens, your Private Location agents need to pick up more work at once. If there aren’t enough agents available during a burst, checks start piling up in the queue, which can delay or disrupt check execution. But solving this by running a high number of agents around the clock has the opposite problem: most of that capacity sits idle until the next busy period.

Any Apple update can break our app. Here's how we find out first.

This is a guest post by Dan Mindru, a Frontend Developer and Designer who is also the co-host of the Morning Maker Show. Dan is currently developing a number of applications including PageUI, Clobbr, and CronTool. It feels like with every release, we are walking a tightrope. We need to keep our app lightweight, stable, and performant, all the while depending on APIs that can shift at any moment (without warning, too!).

Prepare for the EU AI Act with Harness AI Security | Harness Blog

Harness AI Security provides a unified control plane for AI discovery, risk visibility, and runtime protection, helping organizations operationalize key requirements of the EU AI Act. Instead of relying on manual audits or fragmented tooling, teams get continuous insight into how AI systems are built, exposed, and used, along with the evidence needed to demonstrate compliance.

AI Summary Agent in Turbo360

Handed over an Azure integration environment you've never seen before? Turbo360's AI Resource Summary agent gives any support operator or engineer an instant plain-English overview of what a resource is, how it behaves, and what to watch out for - without needing to ask the developers. In this demo: Great for: IT operations teams, MSP NOCs, cloud support engineers, and anyone responsible for running integration workloads they didn't build.