Operations | Monitoring | ITSM | DevOps | Cloud

Most cost questions have more than one layer. Which team spent the most, which services drove it, and which accounts were behind those services? Previously, following that path meant changing dimensions, adjusting filters, and re-running the query at every step. Multi-dimensional drill-down has been one of the most-requested features in Explorer. The team shipped two-level group-by earlier this year, collected feedback, and kept going. Now the path goes eight levels deep.

On 7 October 2026, Daniel Stenberg published a blog post describing a plan to release a new version of curl on 14 October 2026 in order to address 22 known security vulnerabilities. These vulnerabilities have varying severities, with a single vulnerability assessed as high (CVE-2026-92392), while the others have a low or medium severity. The curl maintainer has coordinated with downstream vendors, including Ubuntu, under embargo and the vulnerabilities have been publicly disclosed on the planned date.

There is no single best neocloud for AWS or GCP teams. The right one depends on the workload. Bursty fine-tuning and batch jobs reward flexible billing and low hourly rates. Always-on inference and agents reward capacity you can keep plus a second place to run, and data-heavy pipelines reward cheap data movement.

Last quarter, our AI reviewer told a developer who was fixing a CSS bug to rethink how their component fetched data. The comment was well written and confidently worded. It was also about code they hadn’t touched. That’s what tends to happen when you hand an agent every team’s review guidelines at once.

Learn how to streamline deployment approvals with Harness CD native approval steps and configurable policies to reduce manual effort, improve consistency, and accelerate releases. Approvals shouldn’t cost you a shift. With Harness, the approval step lives inside your pipeline, so you get sign-off without the waiting and the glue code.

Renewing a certificate is the easy part. Getting it onto the server is where automation breaks. Somebody rotates the API token on the firewall. A service account password expires. A VM gets rebuilt and the agent never comes back. The certificate renews right on schedule, the deployment fails, and the server keeps serving the old certificate until it expires. Renewed and deployed are not the same thing.

Monitoring as code means defining hosts, checks, thresholds and notification rules in version-controlled files, and deploying them through review and automated validation, the same way infrastructure as code handles servers and networks. With Icinga you can do this with plain configuration files in Git, the Ansible collection maintained by NETWAYS, the Puppet modules maintained by Vox Pupuli, the Icinga Director, or the REST API from tools such as Terraform.

The first update to the MCP server since launch is out now, and the theme this time is servers. Your AI assistant can now change a server’s host-level settings, set up shared file systems for your containers, and show you what’s running on each machine and how much room is left.

Our cloud agents now test mobile pull requests on cloud simulators and leave screenshots and a recording behind. The agent collects the evidence, and a person decides whether the change is right. More and more of the code in that app is written by coding agents. Of the 144 pull requests opened against it in the last two weeks, 99 were opened with Claude Code or Cursor. The agents are good at writing the change. What they couldn't do was show it to you.