Abstract: The disclosed technology teaches tuning containers in pods, in a high availability environment that runs two or more pods to implement a service, while the containers are running, including instrumenting a tunable container to communicate application metrics to a tuning engine that runs in a pod and maintains current configuration state information for the container. The tuning engine accesses the application metrics and a rule that specifies tuning of resource configuration for the container. The rule combines variables in the metrics to determine whether an update should be applied to the container. The tuning engine determines a new resource configuration for the tunable container and updates the configuration state information for the container according to the new configuration. An update manager detects updating of the configuration state information and performs a rolling update of instances of the tunable container in the pods that implement the service.

Abstract: The disclosed technology teaches tuning containers in pods, in a high availability environment that runs two or more pods to implement a service, while the containers are running, including instrumenting a tunable container to communicate application metrics to a tuning engine that runs in a pod and maintains current configuration state information for the container. The tuning engine accesses the application metrics and a rule that specifies tuning of resource configuration for the container. The rule combines variables in the metrics to determine whether an update should be applied to the container. The tuning engine determines a new resource configuration for the tunable container and updates the configuration state information for the container according to the new configuration. An update manager detects updating of the configuration state information and performs a rolling update of instances of the tunable container in the pods that implement the service.

Abstract: The disclosed technology teaches tuning containers in pods, in a high availability environment that runs two or more pods to implement a service, while the containers are running, including instrumenting a tunable container to communicate application metrics to a tuning engine that runs in a pod and maintains current configuration state information for the container. The tuning engine accesses the application metrics and a rule that specifies tuning of resource configuration for the container. The rule combines variables in the metrics to determine whether an update should be applied to the container. The tuning engine determines a new resource configuration for the tunable container and updates the configuration state information for the container according to the new configuration. An update manager detects updating of the configuration state information and performs a rolling update of instances of the tunable container in the pods that implement the service.

Abstract: The disclosed technology teaches tuning containers in pods, in a high availability environment that runs two or more pods to implement a service, while the containers are running, including instrumenting a tunable container to communicate application metrics to a tuning engine that runs in a pod and maintains current configuration state information for the container. The tuning engine accesses the application metrics and a rule that specifies tuning of resource configuration for the container. The rule combines variables in the metrics to determine whether an update should be applied to the container. The tuning engine determines a new resource configuration for the tunable container and updates the configuration state information for the container according to the new configuration. An update manager detects updating of the configuration state information and performs a rolling update of instances of the tunable container in the pods that implement the service.