Operations | Monitoring | ITSM | DevOps | Cloud

Here at Speedscale, our monorepo has 19 Go projects in CI. Fifteen produce container images for both amd64 and arm64; a few of those need CGO. We also publish cross-compiled CLI binaries for macOS, Linux, and Windows.

Running one AI coding agent is productive. Running five of them at once across three repositories? That’s a coordination problem. Agentic development environments (ADEs) give you a single surface to orchestrate multiple agents, review what each one changed, and get code merged. Kepler by GitKraken is one of the most capable options in this growing category. It’s built around agent-agnostic orchestration and Git workflow control from backlog to merged PR.

TL;DR - We made a way to use Cycle with AI models for doing things like deploying applications faster and diagnosing complex issues. If you'd like to get started right away with Cycle's Hosted MCP, check out our documentation. Today, we're launching a brand new way to interface with the Cycle Platform, that just a year or two ago would have felt entirely like science fiction. Our first ever AI-oriented tooling, Cycle's Hosted MCP, is live today.

Set up the NVIDIA DCGM Exporter with Docker or Helm, pick the right DCGM metrics, enable profiling counters, map GPUs to Kubernetes pods, and add alerts. Sejal Pandey works on content and growth at Last9, writing about observability, reliability, and SRE practices.

Get Ship Done: Everything We Shipped in September 2026.

⁠Operating across 110 countries, Agilent Technologies supports scientists working in life science research, patient diagnostics and testing that helps ensure the safety of water, food and pharmaceuticals. Keeping the technology behind that work running effectively helps employees stay focused on the science and services that contribute to Agilent’s mission to advance quality of life.

AI spend now comes from every department, and it can double in a week without anyone deciding it should. The invoice arrives after the month closes. By then the usual response is a spend cap, which slows every team, including the ones getting real work done with AI. You need to know about spend that breaks its normal pattern while there’s still time to act. The alert should reach the person who can act on it, with proper context and detail.