Abstract:
Various aspects are disclosed for optimization of dependent systems for serverless frameworks. In some examples, a load test executes instances of a function on a dependent system to generate datapoints. The datapoints are organized, using a clustering algorithm, into an acceptable group and at least one unacceptable group. A maximum number of concurrent instances of the function is determined based on a number of instances specified by at least one datapoint selected from the acceptable group. A live workload is performed on the dependent system. The live workload includes instances of the function that are assigned to the dependent system according to the maximum number of concurrent instances.
Abstract:
A system can provide a visual representation of an inventory of data entities for a distributed computing system. Inventory data including cost and operational data for data entities such as data centers, servers, and virtual machines, can be converted into a format file. The format file can be used to create a tree of nodes and node summaries corresponding to the data entities. A user interface can display hierarchical and isolated views of the tree revealing parent child relationships between data entities within a computing system infrastructure. Node summaries including cost and utilization data can be displayed to reveal how specific sub-costs such as labor and licensing, are driven by data entities in one level of the infrastructure and pushed to respective parent or child data entities in other levels. Views of the tree can be used to determine areas of inefficiency or reduced value within the computing system.
Abstract:
Methods, apparatus, systems and articles of manufacture are disclosed for managing cloud applications. An example apparatus includes a monitor to determine current states of virtual machines, a cloud manager to communicate with a hybrid cloud infrastructure, a healer to: compare the current states of the virtual machines to target states to determine a value of the difference, and in response to determining that the difference indicates that there are not enough healthy virtual machines to meet the target states, instructing the cloud manager to add virtual machines based on the value of the difference.
Abstract:
The disclosure provides an approach for managing an application workload on a computer system that includes data centers. The application workload includes first application instances running on a first data center and second application instances running on a second data center. The method comprises collecting usage data of first application instances, usage data of second application instances, and combining the collected data. The method further comprises evaluating the combined data to determine low health in least one application instance, and restarting the at least one application instance or creating a new application instance. The method further comprises evaluating the combined data to determine whether to change size of the application workload, and in which data center to place a second new application instance if increasing size. The method further comprises contacting a component of the chosen data center to place the second new application instance within a local host machine.
Abstract:
A system can provide a visual representation of an inventory of data entities for a distributed computing system. Inventory data including cost and operational data for data entities such as data centers, servers, and virtual machines, can be converted into a format file. The format file can be used to create a tree of nodes and node summaries corresponding to the data entities. A user interface can display hierarchical and isolated views of the tree revealing parent child relationships between data entities within a computing system infrastructure. Node summaries including cost and utilization data can be displayed to reveal how specific sub-costs such as labor and licensing, are driven by data entities in one level of the infrastructure and pushed to respective parent or child data entities in other levels. Views of the tree can be used to determine areas of inefficiency or reduced value within the computing system.
Abstract:
A management system and method for remediating poor-performing clients running in a distributed computer system uses a machine learning technique to automatically detect one or more poor-performing clients among a plurality of clients running in the distributed computer based on at least performance data and resource usage data of the clients. An action is then initiated to mitigate the effects of the poor-performing clients.
Abstract:
A management system and method for remediating poor-performing clients running in a distributed computer system uses a machine learning technique to automatically detect one or more poor-performing clients among a plurality of clients running in the distributed computer based on at least performance data and resource usage data of the clients. An action is then initiated to mitigate the effects of the poor-performing clients.