Operations | Monitoring | ITSM | DevOps | Cloud

Most people rebuild the same handful of Explorer queries: the monthly close view, spend by team for the staff meeting, the filter set that isolates a service you’ve been watching for two months. When we shipped query history and favorites earlier this year, it gave you a way to save up to 12 Explorer configurations.

What survives when a former employee comes back: the 30-day restore window, the unlicensed OneDrive clocks, inactive mailboxes, and how to give a returning employee their old data.

Why a SharePoint or OneDrive file is marked Archived, who can reactivate it, how long it takes, the 120-day re-archive lock, and the file-level alternative that restores in one click.

Why a Teams chat disappears or shows Unknown User after an employee's account is deleted, where the messages really are, the eDiscovery route, and how to keep leavers' chats.

Pull request queues keep growing, reviewers lose context between rounds of feedback, and merges stall for days. If your team’s code review process has become a bottleneck instead of a quality gate, the tooling around it may be the real issue. GitKraken gives you a unified code review workspace that cuts through noise and surfaces meaningful changes so reviewers focus on what matters.

Most Operational Readiness Testing (ORT) programs follow the same ritual. A checklist gets filled out. Someone runs a load test in a war room the week before launch. A failover drill gets scheduled, and everyone hopes it goes cleanly. Then the release is shipped and testing is done. But with Harness you can make this process continuous and your services resilience is protected with the same ORT check list with every small change that is happening in your SDLC.

Internal developer portals need native CI/CD integration to scale effectively. Learn how integrated pipelines improve velocity. Explore Harness IDP. This article explains why internal developer portals require native CI/CD integration to achieve true scalability.

Eight LLM and AI agent observability platforms compared: what each tracks, pricing and free tiers, self-hosting options, and who each is built for. Sejal Pandey works on content and growth at Last9, writing about observability, reliability, and SRE practices.

Netdata AI sees everything your infrastructure does: every metric, every anomaly, every alert. It does not see what your infrastructure is: which services matter, which host is supposed to run hot, who owns what, what your team considers normal. Without that context, “CPU at 91%” is just a finding. With it, it might be a machine doing exactly its job.