Operations | Monitoring | ITSM | DevOps | Cloud

When a CI pipeline runs on cloud infrastructure, the build machine is ephemeral. It spins up, executes your build, and disappears. During that window, you have zero visibility into how much CPU and memory your pipeline actually consumes. This blind spot creates real problems. Teams over-provision VMs "just in case," wasting compute spend. Others under-provision and deal with silent OOM-kills or CPU throttling — the only clue being a cryptic exit code 137.

Coherent routing, Routed Optical Networking, Converged Optical Routing Architecture (CORA), are all names for the same concept: an advanced network architecture which integrates coherent optical transceivers directly into IP routers. This convergence of layers creates a simplified and highly efficient IP-over-DWDM (IP over Dense Wavelength Division Multiplexing) network.

The shift to autonomous and AI-assisted security operations is well underway. But there is a quiet infrastructure decision that will determine whether your AI agents are sharp or sluggish: how your security data is structured before it ever reaches them.

Harness has been recognized as a Leader in the 2026 Gartner Magic Quadrant for DevSecOps Platforms for the third consecutive year. Harness was also positioned furthest on the Completeness of Vision axis in the report. Harness has been recognized as a Leader in the 2026 Gartner Magic Quadrant for DevSecOps Platforms for the third consecutive year. Harness was also positioned furthest on the Completeness of Vision axis in the report.

The CloudZero VS Code Extension 2.0 adds a sidebar that brings CostFormation namespace management directly into your editor, so you never have to break flow for a browser tab.

IT infrastructure automation sounds simple enough on the surface, right? You take repetitive infrastructure work, turn it into automated workflows, and give engineers more time for higher-value problems. This may seem easy, but in practice, it gets more interesting. Modern IT environments are spread across cloud platforms, legacy systems, identity tools, ITSM platforms, monitoring systems, network devices, and business-critical applications.

If you've read our previous piece on the 8 stages of AI engineering maturity, you know where your team sits. Turns out adopting AI is the easy part; adapting to its consequences is where most organizations struggle. For more than a decade, software organizations optimized around a single assumption: implementation capacity was scarce.