Abstract: Techniques for optimizing resource claims for containers is described. In one example, resource utilization data associated with at least one container may be obtained for a period. A set of forecasting models may be trained based on the resource utilization data associated with a portion of the period. Resource utilization of the at least one container may be predicted for a remaining portion of the period using the set of trained forecasting models. The predicted resource utilization may be compared with the obtained resource utilization data for the remaining portion of the period. A forecasting model may be determined from the set of trained forecasting models based on the comparison to optimize resource claims for the at least one container.

Abstract: Embodiments disclosed herein relate to a method, system, and computer-readable medium for monitoring an application executing across a plurality of containers. A performance monitor requests a list of containers created on at least one computing system. The performance monitor retrieves information associated with a creation of each container in the list. The performance monitor parses the information associated with each container in the list to identify a cluster of related containers that are running the applications. The performance monitor displays a topology that relates the containers of the cluster to resources in the at least one computing system. The performance monitor identified a pair of containers that are negatively correlated based on the topology. The performance monitor adjusts the application to remove the negative correlation between the pair of containers.

Abstract: Techniques for optimizing resource claims for containers is described. In one example, resource utilization data associated with at least one container may be obtained for a period. A set of forecasting models may be trained based on the resource utilization data associated with a portion of the period. Resource utilization of the at least one container may be predicted for a remaining portion of the period using the set of trained forecasting models. The predicted resource utilization may be compared with the obtained resource utilization data for the remaining portion of the period. A forecasting model may be determined from the set of trained forecasting models based on the comparison to optimize resource claims for the at least one container.

Abstract: The present disclosure is related to predicting application response lime based on metrics. An example machine-readable medium may store instructions executable by a processing resource to determine a particular response time and an average response time of an application based on a plurality of relevant performance metrics associated with the application during a first period of time, classify the particular response time into a group based on the average response time, and determine a relationship between the plurality of relevant performance metrics and the particular response time of the application. The example machine-readable medium may further store instructions executable by the processing resource to determine whether a response time of the application is likely to change sufficiently to change the classification to a different group during a second period of time based on the relationship.

Abstract: Examples disclosed herein provide for the handling of a print job for a printer via a mobile device. The mobile device receives a notification from a computing device to indicate the print job is available for printing. Upon the mobile device joining a wireless network associated with the printer, the mobile device delivers the print job from the mobile device to the printer via the wireless network.