Abstract: The disclosure herein describes using a monitoring tool and a management tool from a cloud native system to monitor and manage an application executing on a legacy system. Network addresses of services running in the application on the legacy systems are discovered. Based on the discovered addresses, a probe is configured for execution on the legacy system by a monitoring tool deployed on the legacy system to obtain metrics data associated with the services running on the legacy system, the metrics data representing execution loads of the application. A management tool deployed on the cloud native system receives the obtained metrics data. The management tool compares the metrics data to one or more performance thresholds associated with the application. Based on the comparison, the management tool adjusts a quantity of instances of the application running on the cloud native system, enabling the cloud native system to share the execution loads.

Abstract: The disclosure herein describes automating runbook operations associated with an application within an application host on an application platform. A runbook definition associated with the application is accessed by a processor, wherein the runbook definition includes trigger events and runbook operations associated with the trigger events. A runbook operator is executed on the application platform based on the accessed runbook definition and a runbook sidecar container is added to the application host by the runbook operator, wherein the runbook operator is enabled to perform the runbook operations within the application host via the runbook sidecar container. Based on detecting a trigger event, a runbook operation associated with the detected trigger event is performed by the runbook operator, via the runbook sidecar container, whereby the application is maintained based on performance of the runbook operations from within the application host.

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 using a monitoring tool and a management tool from a cloud native system to monitor and manage an application executing on a legacy system. Network addresses of services running in the application on the legacy systems are discovered. Based on the discovered addresses, a probe is configured for execution on the legacy system by a monitoring tool deployed on the legacy system to obtain metrics data associated with the services running on the legacy system, the metrics data representing execution loads of the application. A management tool deployed on the cloud native system receives the obtained metrics data. The management tool compares the metrics data to one or more performance thresholds associated with the application. Based on the comparison, the management tool adjusts a quantity of instances of the application running on the cloud native system, enabling the cloud native system to share the execution loads.

Abstract: The disclosure herein describes automating runbook operations associated with an application within an application host on an application platform. A runbook definition associated with the application is accessed by a processor, wherein the runbook definition includes trigger events and runbook operations associated with the trigger events. A runbook operator is executed on the application platform based on the accessed runbook definition and a runbook sidecar container is added to the application host by the runbook operator, wherein the runbook operator is enabled to perform the runbook operations within the application host via the runbook sidecar container. Based on detecting a trigger event, a runbook operation associated with the detected trigger event is performed by the runbook operator, via the runbook sidecar container, whereby the application is maintained based on performance of the runbook operations from within the application host.

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 using a monitoring tool and a management tool from a cloud native system to monitor and manage an application executing on a legacy system. Network addresses of services running in the application on the legacy systems are discovered. Based on the discovered addresses, a probe is configured for execution on the legacy system by a monitoring tool deployed on the legacy system to obtain metrics data associated with the services running on the legacy system, the metrics data representing execution loads of the application. A management tool deployed on the cloud native system receives the obtained metrics data. The management tool compares the metrics data to one or more performance thresholds associated with the application. Based on the comparison, the management tool adjusts a quantity of instances of the application running on the cloud native system, enabling the cloud native system to share the execution loads.