Abstract: Techniques for virtual machine placement in a datacenter are provided. The techniques include using one or more server power characteristics to determine a power cost for any given virtual machine placement in the datacenter, using a heat profile of one or more datacenter components in relation to one or more cooling resources in the datacenter to determine cooling cost for any given virtual machine placement in the datacenter, and using the power cost and cooling cost to apply integrated energy cost minimization at one or more levels of hierarchy in the datacenter to determine placement of a virtual machine in the datacenter such that the integrated energy cost of the datacenter is minimized.

Abstract: Methods determine workload resource usage patterns of a computerized workload, using a computerized device. Such methods use the computerized device to place the computerized workload with a computer server cluster within a private cloud computing environment. Also, methods herein place the computerized workload on a selected computer server within the computer server cluster that has a resource usage pattern complementary to the workload resource usage profile, also using the computerized device. The complementary resource usage pattern peaks at different times from the workload resource usage patterns.

Abstract: A method for scaling is provided. The method of scaling may include determining a predicted workload of a multi-tier application for a defined time period. A change in application capacity for the predicted workload may be determined. A scaling strategy may be dynamically selected for the change in application capacity. The scaling strategy may include vertical scaling and horizontal scaling.

Abstract: A computer program product, a system and method for scaling are provided. The method of scaling may include determining a predicted workload of a multi-tier application for a defined time period. A change in application capacity for the predicted workload may be determined. A scaling strategy may be dynamically selected for the change in application capacity. The scaling strategy may include vertical scaling and horizontal scaling.

Abstract: Methods and systems for image migration. There are received, at an image reader, files of at least one image of at least one virtual machine from a first environment. Points of variability are identified within the files, with respect to preparation for functioning in a second environment. Each point of variability is associated with corresponding metadata, and each point of variability is stored with its corresponding metadata. The at least one image is reconfigured to function in the second environment, such reconfiguring comprising adjusting the points of variability via using the metadata. The reconfigured image is deployed to the second environment.

Abstract: During a process of migrating a source system into a standardized virtual environment, virtual machine instances of the source system executing in a hypervisor are snapshotted as virtual machine images in an operational repository of the hypervisor. The virtual machine images in the operational repository are short-term snapshots. From time to time during the migration process, long-term snapshots of the source system are created by checking given ones of the virtual machine images from the hypervisor operational repository into an image library as image objects.

Abstract: An arbitrary customer instance is transferred from a customer environment to a target managed-infrastructure-as-a-service cloud environment as a transferred image. An image adjustment plan, capturing at least one adjustment required to render the transferred image compliant with standards of the target managed-infrastructure-as-a-service cloud environment, is formulated. The image adjustment plan is executed to adjust the transferred image to obtain an adjusted image compliant with standards of the target managed-infrastructure-as-a-service cloud environment. The adjusted image is on-boarded into the managed-infrastructure-as-a-service cloud environment as a standard image thereof.

Abstract: Techniques for minimizing storage power consumption are provided. The techniques include generating one or more physical storage volumes and one virtual storage volume for each physical storage volume, creating a mapping from virtual storage volumes to physical storage volumes, determining input/output (I/O) access behavior of one or more applications using statistical analysis, and re-mapping the virtual to physical volume mapping based on the determined I/O access behavior of the one or more applications to minimize storage power consumption while meeting a required performance.

Abstract: A system and computer program product for virtual machine placement in a datacenter include using one or more server power characteristics to determine a power cost for any given virtual machine placement in the datacenter, using a heat profile of one or more datacenter components in relation to one or more cooling resources in the datacenter to determine cooling cost for any given virtual machine placement in the datacenter, and using the power cost and cooling cost to apply integrated energy cost minimization at one or more levels of hierarchy in the datacenter to determine placement of a virtual machine in the datacenter such that the integrated energy cost of the datacenter is minimized.

Abstract: A method and system for image instance mapping is provided. The method includes receiving from change agents on virtual machine instances periodic monitoring data indicating changes for each virtual machine instance. The periodic monitoring data is analyzed and unique updates are applied to the virtual machine instances. High level semantic updates to the virtual machine instances are identified and updates associated with a golden master image are tracked. High level semantic updates to the golden master image are identified and in response, a version tree configured to track drift of each virtual machine instance with respect to golden master image is maintained.

Abstract: Techniques for problem determination and diagnosis in a shared dynamic cloud environment. A method includes monitoring each virtual machine and physical server in the shared dynamic cloud environment for at least one metric, identifying a symptom of a problem and generating an event based on said monitoring, analyzing the event to determine a deviation from normal behavior, and classifying the event as a cloud-based anomaly or an application fault based on existing knowledge.

Abstract: A method, an apparatus and an article of manufacture for problem determination and diagnosis in a shared dynamic cloud environment. The method includes monitoring each virtual machine and physical server in the shared dynamic cloud environment for at least one metric, identifying a symptom of a problem and generating an event based on said monitoring, analyzing the event to determine a deviation from normal behavior, and classifying the event as a cloud-based anomaly or an application fault based on existing knowledge.

Abstract: A virtual machine placement framework is described to enable a data center operator to develop a placement scheme to satisfy its particular constraints while simultaneously optimizing resource utilization. To generate a placement solution, the virtual machine placement problem is first characterized as a “bin packing” problem. The framework provides simple interface tools and processing modules, and a pluggable architecture for receiving placement algorithms. To generate a solution, an administrator creates an XML representation that abstracts physical entities (e.g., data center, subnet, rack, physical server, and the like) into a hierarchical tree of bins. The administrator also defines a set of “rules” that govern (direct) the placement of the virtual machines by placing constraints on the placement scheme. Using the hierarchical tree and the rules, the framework is executed to generate a placement as a solution to a bin packing problem, preferably on a layer-by-layer basis.

Abstract: A predicted workload of a multi-tier application is determined for a defined period of time. A change in application capacity is determined for the predicted workload. A scaling strategy is dynamically selected for the change in application capacity, in which the scaling strategy including vertical scaling and horizontal scaling.

Abstract: A predicted workload of a multi-tier application is determined for a defined period of time. A change in application capacity is determined for the predicted workload. A scaling strategy is dynamically selected for the change in application capacity, in which the scaling strategy including vertical scaling and horizontal scaling.

Abstract: Embodiments of the invention provide power savings via performing application workload consolidation to servers using off-peak values for application workload demand. Embodiments of the invention are designed to achieve significant power savings while containing performance risk associated with server consolidation.

Abstract: Applications in a data center can be consolidated by identifying different combinations of software executing on hardware. The software can include a set of applications that execute upon a set of servers. The different combinations can have different arrangements of applications running on different ones of the servers. For each of the different combinations, a licensing cost, an operating cost, and a total cost can be calculated. The total cost of operation for each of the configurations can be calculated by summing the licensing costs, the operating costs adjusted for the cost savings for complementary workload patterns, and migration costs for adjusting a current configuration of the applications and servers to arrive at the configuration. The total cost results per configuration can be reported to a user for at least a set of the configurations.

Abstract: Applications in a data center can be consolidated by identifying different combinations of software executing on hardware. The software can include a set of applications that execute upon a set of servers. The different combinations can have different arrangements of applications running on different ones of the servers. For each of the different combinations, a licensing cost, an operating cost, and a total cost can be calculated. The total cost of operation for each of the configurations can be calculated by summing the licensing costs, the operating costs adjusted for the cost savings for complementary workload patterns, and migration costs for adjusting a current configuration of the applications and servers to arrive at the configuration. The total cost results per configuration can be reported to a user for at least a set of the configurations.

Abstract: Methods determine workload resource usage patterns of a computerized workload, using a computerized device. Such methods use the computerized device to place the computerized workload with a computer server cluster within a private cloud computing environment. Also, methods herein place the computerized workload on a selected computer server within the computer server cluster that has a resource usage pattern complementary to the workload resource usage profile, also using the computerized device. The complementary resource usage pattern peaks at different times from the workload resource usage patterns.

Abstract: Techniques for virtual machine placement in a datacenter are provided. The techniques include using one or more server power characteristics to determine a power cost for any given virtual machine placement in the datacenter, using a heat profile of one or more datacenter components in relation to one or more cooling resources in the datacenter to determine cooling cost for any given virtual machine placement in the datacenter, and using the power cost and cooling cost to apply integrated energy cost minimization at one or more levels of hierarchy in the datacenter to determine placement of a virtual machine in the datacenter such that the integrated energy cost of the datacenter is minimized.