Operations | Monitoring | ITSM | DevOps | Cloud

The promise of agentic AI is dead simple to understand. Instead of waiting for a human to draft every instruction, an AI agent can interpret a goal, take action, and work across systems until the task is done. For IT teams, that motion sounds like the next logical phase of automation. That promise is real... but it’s also where the risk starts. Traditional automation followed instructions. Agentic AI, by contrast, pursues outcomes. That difference turns the entire governance model on its head.

How to choose one, and what options exist on the market.

‍ Learn how to master Azure deployment with CI/CD pipelines, progressive delivery, and feature flags. See how Harness helps engineering teams ship faster and safer on Azure. Azure deployment sounds straightforward. Push code, it runs in the cloud. But if you've managed a 2 a.m. production incident because a deployment went sideways on AKS, you know the gap between "it deploys" and "it deploys safely at scale" is significant.

The Harness VS Code Extension is now on the Marketplace. Monitor pipelines, debug logs, approve deployments, and query failures with Claude Code, Copilot, or Cursor, without leaving VS Code. Your Harness pipelines, logs, and deployment approvals are now a sidebar panel away inside VS Code. The Harness VS Code Extension is live on the VS Code Marketplace today, no.vsix download, no manual install.

Previous articles walked through RDMA (Remote Direct Memory Access) as a programming model and InfiniBand as the fabric that was built around it. Both led to the same conclusion, even if it was never stated outright: moving data, not compute, becomes the bottleneck once systems scale. So what happens when you want RDMA, but you’re already running an Ethernet network you’re not keen to replace? That’s usually where RDMA over Converged Ethernet (RoCE) enters the conversation.

Organizations invest heavily in cybersecurity tools, yet many still struggle to confidently understand what is actually protected across their environment. This blog explores how disconnected systems, unknown assets, and inconsistent data create blind spots, and how Teneo’s Cyber Asset Attack Surface Management (CAASM), powered by ThreatAware, helps organizations gain a trusted view of security coverage.

Security teams today are managing growing volumes of cybersecurity data across increasingly complex environments. This blog explores the hidden operational cost of disconnected tools, manual data reconciliation, and fragmented reporting, and how Teneo’s Cyber Asset Attack Surface Management (CAASM), powered by ThreatAware, helps organizations create a more unified and trusted view across their security estate. Most organizations are not short of security tools.

Predictive maintenance is one of the most compelling use cases for time series data. Instead of waiting for equipment to fail or servicing it on a fixed calendar regardless of condition, you watch the live sensor data and act when it indicates that a failure is coming. That “watch the data and act” loop is exactly what the InfluxDB 3 Processing Engine was built for.