Bringing Browser-Based MFA SSO to the OpenStack CLI
Learn how a lightweight keystoneauth1 plugin brings your existing browser-based MFA and SSO to the OpenStack CLI, with no changes to any client tools.
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Learn how a lightweight keystoneauth1 plugin brings your existing browser-based MFA and SSO to the OpenStack CLI, with no changes to any client tools.
Hyperscaler AI looks fast but hides long-term lock-in and rising costs. See how OpenStack and Kubernetes deliver GPU infrastructure you actually control.
Many AI clusters run at only 30–50% GPU utilization. Learn why GPUs sit idle and how Kubernetes, scheduling, and better infrastructure design can improve AI infrastructure efficiency.
A Kubernetes Scheduler is a part of the components (pods, nodes, volume, etc.) that make up the orchestration engine's structure. Read on.
A Kubernetes Scheduler is a part of the various components (pods, nodes, volume, etc.) that make up the open source orchestration engine's structure. Here is a brief overview of the topic to help better understand K8s and its components.
The Kubernetes scheduler is a monolithic component of the Kubernetes (K8s) platform that handles performance, capacity, and availability through set policies and topology awareness.
It is decoupled from the API server that manages clusters and isn't an admission controller (plug-in code intercepting requests to the K8s API. Virtualization administrators detect the Kubernetes scheduler as the containerization counterpart of VM scheduling.
Kubernetes deploys containers within pods that reside within nodes. Specific workload requirements are set through an API. Here, the scheduler matches each pod to a corresponding set of nodes' IT resources. If desired, the scheduler is also capable of distributing copies of pods across nodes for high availability.
If the Kubernetes scheduler cannot locate hardware corresponding to the pod's specifications, it is left unscheduled. The scheduler tries the process again and again until a machine becomes available.
The scheduler is configurable with namely two policies - PriorityFunction and FitPredicate. The former applies when the scheduler has already performed checks on multiple systems for the best fit. If the scheduler locates various options that can support pods, PriorityFunction directs the scheduler to rank the machines based on the best fit.
The FitPredicate policy complies with the set rules while detecting labels on nodes or the number of requested resources by the containers. This approach helps to determine whether containers exceed the shared hardware resources capacity. If the selected resources are zero, the scheduler can add another pod to the node.
Kubernetes allows the user to implement a chosen scheduler instead of the default one and thereby execute concurrent scheduling. These schedulers, including the default one, work simultaneously. Some pods use the default scheduler, while the others use the other options within the same K8s deployment.
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