Abstract: A mechanism is provided for implementing operation optimization. Responsive to a request to load data via a input/output (I/O) load operation, prior to loading the data, transformed data in a local memory is searched for a match to the requested data. Responsive to identifying transformed that matches the requested data, the transformed data in the local memory is used to fulfill the request. Responsive to failing to identify transformed data in the local memory that matches the requested data, untransformed data in the local memory is searched for a match to the requested data. Responsive to identifying untransformed data that matches the requested data, the untransformed data in the local memory is used to fulfill the request. Responsive to failing to identify untransformed data in the local memory that matches the requested data, the requested data may be loaded from the storage system via the I/O load operation.

Abstract: A mechanism is provided for implementing operation optimization. Responsive to a request to load data via a input/output (I/O) load operation, prior to loading the data, transformed data in a local memory is searched for a match to the requested data. Responsive to identifying transformed that matches the requested data, the transformed data in the local memory is used to fulfill the request. Responsive to failing to identify transformed data in the local memory that matches the requested data, untransformed data in the local memory is searched for a match to the requested data. Responsive to identifying untransformed data that matches the requested data, the untransformed data in the local memory is used to fulfill the request. Responsive to failing to identify untransformed data in the local memory that matches the requested data, the requested data may be loaded from the storage system via the I/O load operation.

Abstract: Managing data in a cloud computing environment, including data transfers. File level and block level similarities are identified, including for archive and nested archive files, residing on datacenters and regional repositories. A replication plan is generated based on receiving a replication instruction, and further based on similarity clusters by transferring unique data blocks and files from best available sources including regional repositories.

Abstract: A mechanism is provided for implementing operation optimization. Responsive to a request to load data via a input/output (I/O) load operation, prior to loading the data, transformed data in a local memory is searched for a match to the requested data. Responsive to identifying transformed that matches the requested data, the transformed data in the local memory is used to fulfill the request. Responsive to failing to identify transformed data in the local memory that matches the requested data, untransformed data in the local memory is searched for a match to the requested data. Responsive to identifying untransformed data that matches the requested data, the untransformed data in the local memory is used to fulfill the request. Responsive to failing to identify untransformed data in the local memory that matches the requested data, the requested data may be loaded from the storage system via the I/O load operation.

Abstract: A mechanism is provided for implementing operation optimization. Responsive to a request to load data via a input/output (I/O) load operation, prior to loading the data, transformed data in a local memory is searched for a match to the requested data. Responsive to identifying transformed that matches the requested data, the transformed data in the local memory is used to fulfill the request. Responsive to failing to identify transformed data in the local memory that matches the requested data, untransformed data in the local memory is searched for a match to the requested data. Responsive to identifying untranstormed data that matches the requested data, the untransformed data in the local memory is used to fulfill the request. Responsive to failing to identify untransformed data in the local memory that matches the requested data, the requested data may be loaded from the storage system via the I/O load operation.

Abstract: Managing data in a cloud computing environment, including data transfers. File level and block level similarities are identified, including for archive and nested archive files, residing on datacenters and regional repositories. A replication plan is generated based on receiving a replication instruction, and further based on similarity clusters by transferring unique data blocks and files from best available sources including regional repositories.

Abstract: Managing data in a cloud computing environment, including data transfers. File level and block level similarities are identified, including for archive and nested archive files, residing on datacenters and regional repositories. A replication plan is generated based on receiving a replication instruction, and further based on similarity clusters by transferring unique data blocks and files from best available sources including regional repositories.

Abstract: Managing data in a cloud computing environment, including data transfers. File level and block level similarities are identified, including for archive and nested archive files, residing on datacenters and regional repositories. A replication plan is generated based on receiving a replication instruction, and further based on similarity clusters by transferring unique data blocks and files from best available sources including regional repositories.

Abstract: A system and method for efficiently transferring virtual machine images across nodes in a cloud computing environment, includes analyzing each image on each node to create hash code clusters and a similarity matrix. An instruction to transfer an image from a source node to a target node is received. The clusters and the similarity matrix are used to determine to what extent the data from the image is already on the source node, or on any other node, and further determines the cost and speed of transferring such data to the target node. An optimal transfer plan is generated, and data that is not already on the target node is transferred to the target node from the most efficient node on which it is available, according to the optimal transfer plan.

Abstract: A system and method for efficiently transferring virtual machine images across nodes in a cloud computing environment, includes analyzing each image on each node to create hash code clusters and a similarity matrix. An instruction to transfer an image from a source node to a target node is received. The clusters and the similarity matrix are used to determine to what extent the data from the image is already on the source node, or on any other node, and further determines the cost and speed of transferring such data to the target node. An optimal transfer plan is generated, and data that is not already on the target node is transferred to the target node from the most efficient node on which it is available, according to the optimal transfer plan.

Abstract: A system and method for efficiently transferring virtual machine images across nodes in a cloud computing environment, includes analyzing each image on each node to create hash code clusters and a similarity matrix. An instruction to transfer an image from a source node to a target node is received. The clusters and the similarity matrix are used to determine to what extent the data from the image is already on the source node, or on any other node, and further determines the cost and speed of transferring such data to the target node. An optimal transfer plan is generated, and data that is not already on the target node is transferred to the target node from the most efficient node on which it is available, according to the optimal transfer plan.

Abstract: One embodiment of a system for provisioning a new virtual machine instance on a target host based on an image of the new virtual machine instance includes a local storage for storing images of virtual machine instances currently running on the target host and a virtual machine creator coupled to the local storage for constructing the image of the new virtual machine instance at least in part using the images of virtual machine instances currently running on the target host.

Abstract: An apparatus for enabling resiliency for cloud computing systems is provided. An apparatus includes a processor and a memory storing computer program code. The memory and the computer program code are configured to, with the processor, cause the apparatus to perform actions. The actions include modifying a topology graph of a network architecture by mapping processes flows onto the topology graph and creating a resiliency graph based on the modified topology graph. The actions also include modifying the resiliency graph by translating at least one SLA into the resiliency graph and identifying overlaps and dependencies in the modified resiliency graph. Apparatus and computer readable instructions are also described.

Abstract: One embodiment of a system for provisioning a new virtual machine instance on a target host based on an image of the new virtual machine instance includes a local storage for storing images of virtual machine instances currently running on the target host and a virtual machine creator coupled to the local storage for constructing the image of the new virtual machine instance at least in part using the images of virtual machine instances currently running on the target host.

Abstract: One embodiment of a method for provisioning a new virtual machine instance based on the content of an image of the new virtual machine instance includes identifying, from among a plurality of host machines, the host machine having the highest percentage of the content available in local storage, and provisioning the new virtual machine instance on the host machine having the highest percentage of the content available in local storage. Another embodiment of a method for provisioning a new virtual machine instance based on an image of the new virtual machine instance includes constructing at least a portion of the image using data stored locally on a target machine hosting the new virtual machine instance, and completing the image using data obtained over a network from remote storage.

Abstract: Techniques for improving virtual machine-to-image affinity on a physical server. A method includes identifying physical machines in a network as candidate source physical machines, wherein each candidate source physical machine stores a first virtual machine image and a set of additional virtual machine images, identifying physical machines in the network as candidate target physical machines, wherein each candidate target physical machine stores one of the additional virtual machine images, and selecting a virtual machine image from the set of additional virtual machine images and selecting a physical machine from the candidate target physical machines such that migrating the selected virtual machine image from a candidate source physical machine to the selected target physical machine results in a maximized image affinity per virtual machine in comparison to each image migration scenarios for the set of additional virtual machine images.

Abstract: Systems and articles of manufacture for improving virtual machine-to-image affinity on a physical server include identifying physical machines in a network as candidate source physical machines, wherein each candidate source physical machine stores a first virtual machine image and a set of additional virtual machine images, identifying physical machines in the network as candidate target physical machines, wherein each candidate target physical machine stores one of the additional virtual machine images, and selecting a virtual machine image from the set of additional virtual machine images and selecting a physical machine from the candidate target physical machines such that migrating the selected virtual machine image from a candidate source physical machine to the selected target physical machine results in a maximized image affinity per virtual machine in comparison to each image migration scenarios for the set of additional virtual machine images.

Abstract: A method for enabling resiliency for cloud computing systems is described. The method includes modifying a topology graph of a network architecture by mapping processes flows onto the topology graph. A resiliency graph is created based on the modified topology graph. The method includes modifying the resiliency graph by translating at least one SLA into the resiliency graph. Overlaps and dependencies in the modified resiliency graph are identified. Apparatus and computer readable instructions are also described.

Abstract: A system and an article of manufacture for de-duplicating virtual machine image accesses include identifying one or more identical blocks in two or more images in a virtual machine image repository, generating a block map for mapping different blocks with identical content into a same block, deploying a virtual machine image by reconstituting an image from the block map and fetching any unique blocks remotely on-demand, and de-duplicating virtual machine image accesses by storing the deployed virtual machine image in a local disk cache.

Abstract: An apparatus for enabling resiliency for cloud computing systems is provided. An apparatus includes a processor and a memory storing computer program code. The memory and the computer program code are configured to, with the processor, cause the apparatus to perform actions. The actions include modifying a topology graph of a network architecture by mapping processes flows onto the topology graph and creating a resiliency graph based on the modified topology graph. The actions also include modifying the resiliency graph by translating at least one SLA into the resiliency graph and identifying overlaps and dependencies in the modified resiliency graph. Apparatus and computer readable instructions are also described.