Operations | Monitoring | ITSM | DevOps | Cloud

Table of Contents In Part 1: Agentic AI at Scale – Building the Kubex Agentic AI Platform of this series, we laid the foundation for scaling agentic AI across cloud infrastructure. We examined why traditional ops workflows get stuck in reactive loops of dashboard watching, why static context limits intelligence, and how the Kubex platform uses context engineering and a distributed nervous system to bridge the gap between telemetry and deterministic actions.

A vendor saying it plays in a market is one thing. A respected independent research firm saying so is another. That’s why I’m pleased to share that Kubex has been included in Forrester’s The Cloud Cost Management And Optimization Solutions Landscape, Q3 2026.

Picture the bridge call at 2 am. A Sev1 has taken down a critical service, and the paging storm has pulled forty people out of bed, even though only six of them will ever touch the fix. The first hour disappears into roll call and trying to figure out which changes shipped last night, which alerts are related, and who actually owns the failing service.

Choosing a software engineering intelligence platform for an enterprise team means weighing SOC 2 compliance, data privacy controls, and the ability to scale across hundreds or thousands of contributors. You need visibility into DORA metrics, AI coding tool impact, and delivery velocity without compromising how your repositories and developer data are protected.

Sometimes you just want to fetch all Icinga 2 objects of a given type from the API and do something with them. Then you notice that Icinga 2’s memory usage jumps up with every large request and never comes back down, as if each HTTP request leaked a huge chunk of memory. And once enough of these requests run in parallel, no matter how much RAM the machine has, Icinga 2 runs out of memory and crashes. Here’s what was really going on, and how we fixed it in Icinga 2 v2.16.

Every enterprise board now expects an agentic AI plan. Far fewer operating leaders can say which workflow should carry it first, and why. That debate ran through the closed-door roundtable jointly hosted by iOPEX and Soroco in London, with senior operations and transformation leaders from telecom, banking, retail, financial data, and life sciences.

Rule-based routing pages the service that errored. Build a small triage service that reads the alert webhook, finds the origin span in your traces and pages the team that owns it. Last9 is an observability platform built for high-cardinality telemetry. It unifies logs, metrics, and traces with native OpenTelemetry and Prometheus support, real-time alerting, and long-term retention.

Wide events move observability cost instead of removing it. See what each signal is billed in, which question each answers cheapest, and how to size spend against cloud spend. Sejal Pandey works on content and growth at Last9, writing about observability, reliability, and SRE practices.

A data residency security review for observability in your own cloud account: vendor access, connection direction, PII redaction and egress, with what Last9 documents. Last9 is an observability platform built for high-cardinality telemetry. It unifies logs, metrics, and traces with native OpenTelemetry and Prometheus support, real-time alerting, and long-term retention.

AI coding agents lose context once a PR enters the pipeline. See how code context and delivery context work.