Abstract: The disclosure herein describes managing multiple clusters within a container environment using a control cluster. The control cluster includes a single deployment model that manages deployment of cluster components to a plurality of clusters at the cluster level. Changes or updates made to one cluster are automatically propagated to other clusters in the same environment, reducing system update time across clusters. The control cluster aggregates and/or stores monitoring data for the plurality of clusters creating a centralized data store for metrics data, log data and other systems data. The monitoring data and/or alerts are displayed on a unified dashboard via a user interface. The unified dashboard creates a single representation of clusters and monitor data in a single location providing system health data and unified alerts notifying a user as to issues detected across multiple clusters.

Abstract: A computerized method and system for containerized application deployment is disclosed that includes: receiving an identification of a containerized application; generating parameters for the containerized application; based at least on historical performance data for a previous deployment of the containerized application, optimizing the generated parameters for the containerized application to produce optimized parameters for the containerized application; validating the optimized parameters for the containerized application; committing the optimized parameters for the containerized application to a repository; and deploying a selected number of instances of the containerized application with the optimized parameters for the containerized application. This advantageously brings operational data into deployment optimization in order to permit optimization based on actual historical performance data.

Abstract: A computerized method and system for containerized application deployment is disclosed that includes: receiving an identification of a containerized application; generating parameters for the containerized application; based at least on historical performance data for a previous deployment of the containerized application, optimizing the generated parameters for the containerized application to produce optimized parameters for the containerized application; validating the optimized parameters for the containerized application; committing the optimized parameters for the containerized application to a repository; and deploying a selected number of instances of the containerized application with the optimized parameters for the containerized application. This advantageously brings operational data into deployment optimization in order to permit optimization based on actual historical performance data.

Abstract: The disclosure herein describes managing multiple clusters within a container environment using a control cluster. The control cluster includes a single deployment model that manages deployment of cluster components to a plurality of clusters at the cluster level. Changes or updates made to one cluster are automatically propagated to other clusters in the same environment, reducing system update time across clusters. The control cluster aggregates and/or stores monitoring data for the plurality of clusters creating a centralized data store for metrics data, log data and other systems data. The monitoring data and/or alerts are displayed on a unified dashboard via a user interface. The unified dashboard creates a single representation of clusters and monitor data in a single location providing system health data and unified alerts notifying a user as to issues detected across multiple clusters.