AI agents are rapidly transforming software engineering—introducing new architectural patterns, terminology, and operational workflows designed to automate repetitive tasks. One of the most compelling emerging use cases is Agents for Ops . In this post, I share my journey building a Kubernetes namespace monitoring agent. Think of it as a digital intern performing Level 1 SRE tasks: it monitors K8s workloads and automatically remediates failures strictly within the guardrails of a provided knowledge base—nothing more, nothing less. I built 2 agents: 1 for K8s namespaces per cluster and 1 for VMs fleet; but to keep this post short I will focus on the k8s-namespace-monitoring-agent. The Demo: OpenClaw: Kagenti: The usecase: My usecase is simple: The Environment: Two workloads (a web server and a database-backed microservice) running on OpenShift, with a "Chaos Monkey" injecting random failures to simulate real life application failures. The Knowledge Base: A mapping of known...
Managing edge devices has been a complex process as traditional IT ops tools fall short in distributed, low-connectivity environment to manage huge quantity of devices. Red Hat Edge Manager (Open source project: FlightControl , GA'd by Red Hat on late Jan, 2026) solves these challenges by providing streamlined management of edge devices and applications through a declarative approach . Now, there's a fair bit to unpack here. But for simplicity this is how I am going to map those 3 things here: Management of edge devices: I am mapping this to LCM (including upgrade, patch etc) of the underlying OS (in this case RHEL OS of BootC flavor or at least UBI based RHEL ). Managing applications: Mapping this to deploying applications and LCM of the applications stack on the OS. Declarative approach: This one is super interesting. To me this is very K8s-yy but in the world of edge devices running linux (RHEL OS, as of today). And then this thing also has MCP : This is my next prob...