Operations | Monitoring | ITSM | DevOps | Cloud

One of the key Kubernetes security concepts is that workload identity is tied back to information that the orchestrator has. The orchestrator is actually the authoritative entity for what the actual workloads are in the platform. Kubernetes uses labels to select objects and to identify collections of objects that satisfy certain conditions. We, and others in the Kubernetes networking space, often talk about using Kubernetes ‘labels’ as identity bearers.

OpsRamp, the service-centric AIOps software-as-a-service (SaaS) platform for the hybrid enterprise, today announced new topology maps, enhanced artificial intelligence for IT operatzions (AIOps) features and new monitoring capabilities for cloud native workloads.

Kubernetes is a fantastic tool for building large containerised software systems in a manner that is both resilient and scalable. But the architecture and design of Kubernetes has evolved over time, and there are some areas that could do with tweaking or rethinking. This post digs into some issues related to how image tags are handled in Kubernetes and how they are treated differently in plain Docker.

Kubernetes clusters can manage large numbers of unrelated workloads concurrently and organizations often choose to deploy projects created by separate teams to shared clusters. Even with relatively light use, the number of deployed objects can quickly become unmanageable, slowing down operational responsiveness and increasing the chance of dangerous mistakes.