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Cloud Provider Pod: Automated Cloud Deployment

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For example, in the following pod spec, two readinessGates are specified. Another pod condition ContainerReady will be introduced to capture the old pod Ready condition. Need to use client-go or other KubeClient implementations. Naming Convention: The type of custom pod condition must comply with k8s label key format. For the workloads that take pod readiness as a critical signal for its decision making, they will automatically comply with this proposal without any change.

Majority, if not all, of the workloads satisfy this condition. This allows existing manifests to just work with features that require ReadinessGate. Each feature will bear the burden of injecting ReadinessGate and keep its custom pod condition in sync. ReadinessGate can be injected using mutating webhook at pod creation time.

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After pod creation, each feature is responsible for keeping its custom pod condition in sync as long as its ReadinessGate exists in the PodSpec. This can be achieved by running k8s controller to sync conditions on relevant pods. This is to ensure that PodStatus is observable and recoverable even when catastrophic failure e. There are a lot of workloads including core workloads such as deployment and 3rd party workloads such as spark operator.

Most if not all of them take pod readiness as a critical signal for decision making, while ignoring higher level abstractions e. To complicate the problem more, label selector makes membership relationship implicit and dynamic.

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Solving this problem in all workload controllers would require much bigger change than this proposal. Container readiness is tied to low level constructs such as runtime. This inherently implies that the kubelet and underlying system has full knowledge of container status.

Injecting external feedback into container status would complicate the abstraction and control flow. Meanwhile, higher level abstractions e.

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