Abstract: A system receives a request to store data at a first layer of servers in a cluster, configured to authenticate and authorize the request. The system compresses the data upon authenticating and authorizing the request and encrypts the compressed data at the first layer of servers when encryption is enabled. The system sends the request and the encrypted data to a second layer of servers in the cluster, configured to store data structures used to manage data storage in a third layer of servers in the cluster, and to distribute the request and the encrypted data to the third layer of servers using the data structures. The system stores the encrypted data in the third layer of servers. Encrypting the data at the first layer of servers reduces latency associated with transferring the data between the first, second, and third layers of servers.

Abstract: A system stores data in data units in a cluster in a cloud computing system, the data stored in the data units being encrypted or unencrypted depending on whether encryption is enabled or disabled when storing data in the data units. The system identifies one or more data units to defragment and defragments the identified data units by writing the data from the identified data units to one or more new data units and by releasing the identified data units for storing new data. The system encrypts unencrypted data from the identified data units when writing the data from the identified data units to the one or more new data units.

Abstract: In various embodiments, methods and systems for implementing hash-based partitioning in distributed computing systems are provided. At a high level, a distributed computing system having an underlying range-based partitioning architecture for storage may be configured as a hash-based partitioning system, for example, a hybrid range-hash table storage. An operations engine of the hash-based partitioning system receives a tenant request to provision input/output operations per second (IOPS). The tenant request comprises a requested number of IOPS. Based on the tenant request, a provisioning operation to provision IOPS in a hybrid range-hash table storage with hash-based partitioning is determined. The provisioning operation is selected from one of the following: a table creation provisioning operation, an IOPS increase provisioning operation, and an IOPS decrease provisioning operation. The selected provisioning operation is executed for a corresponding table.

Abstract: Methods, systems, apparatuses, and computer program products are provided that enable immediate access to data associated with a source blob. The foregoing is achieved by creating a copy-on-read blob based on the source blob and a link blob based on the copy-on-read blob for each virtual machine to be deployed. When creating the copy-on-read blob, the source blob is not copied. Instead, data from the source blob is copied to the copy-on-read blob upon request by a virtual machine. Subsequent requests for that data are retrieved from the copy-on-read blob. Each link blob stores write data provided by its corresponding virtual machine. When a virtual machine requests data, its corresponding link blob is checked for the data. If the data is not stored therein, the copy-on-read blob is checked for the data. If the copy-on-read blob does not store the data, the data is retrieved from the source blob.

Abstract: Techniques for managing resources among clusters of computing devices in a computing system are described herein. In one embodiment, a method includes receiving, via a computer network, a resource reassignment message indicating that a server is reassigned from a first cluster to a second cluster and in response to the received resource reassignment message, establishing communications with the server reassigned from the first cluster to the second cluster via the computer network. The method further includes subsequent to establishing communications with the server via the computer network, assigning a compute load to the server reassigned from the first cluster to the second cluster without physically relocating the server from the first cluster to the second cluster.

Abstract: A snapshot of data from a table associated with a particular user may be generated. Tree data structures that are distributed across multiple computer systems may be accessed. Each of the tree structures may include data associated with one or more users. At least one tree data structure of the tree data structures that includes data associated with the particular user of the one or more users may be identified. The at least one tree data structure may then be filtered. Filtering may comprise identifying only data that is associated with the particular user. A snapshot of the data associated with the particular user may be generated. Generating the snapshot of the data associated with the particular user comprises generating a data structure that is configured to map to each data page of the at least one tree data structure that includes data associated with the particular user.

Abstract: Prefetching metadata stream sub-portions and/or log stream sub-portions to recreate partition states in a distributed computing system. A system monitors performance metrics associated with a first node running an instance of a partition and, based thereon, cause a second node to duplicate a desired operational state of the partition. The desired operational state may result from transactions being performed on the partition after a previous operational state. Re-creating the desired operational state may include causing multiple prefetch buffers to simultaneously load sub-portions of the transactions and then commencing a replay operation after an initial subset of the transactions is loaded but prior to the entirety of the transactions being fully loaded. The system may preemptively analyze individual prefetch buffers to identify partial buffers that have not fully loaded. Then, the system may cause other prefetch buffers to assist the partial buffers in fully loading a corresponding subset of transactions.

Abstract: The use of a single physical server in which there are multiple virtual nodes operating different components of a distributed application under test. Each virtual node emulates an actual physical node in a prospective distributed environment. The virtual nodes might be, for example, virtual machines or emulated services, and may operate their own operating system within the context of the virtual node. The distributed environment is emulated on the physical server by having the virtual nodes communicate with each other using the protocols that they would normally use in a deployed distributed environment. A configuration data source may be used to setup and perhaps upgrade the virtual nodes so as to emulate the distributed environment. Accordingly, the distributed application may be tested without actually setting up a distributed environment.

Abstract: The use of a single physical server in which there are multiple virtual nodes operating different components of a distributed application under test. Each virtual node emulates an actual physical node in a prospective distributed environment. The virtual nodes might be, for example, virtual machines or emulated services, and may operate their own operating system within the context of the virtual node. The distributed environment is emulated on the physical server by having the virtual nodes communicate with each other using the protocols that they would normally use in a deployed distributed environment. A configuration data source may be used to setup and perhaps upgrade the virtual nodes so as to emulate the distributed environment. Accordingly, the distributed application may be tested without actually setting up a distributed environment.

Abstract: A code fix is communicated using an automatically executable code patch that has an additional code element that allows the code to perform the functions of registration, detection, setup, reporting, tracking, policy verification or clean up.

Abstract: A system and method for last known good (LKG) for patches. A file cache is created to store binaries which have shipped as part of a previous wide public release—security fixes (GDRs) and service packs. There are two levels of cache, including an SP cache which keeps all of the files which were shipped as part of the service pack, and a GDR cache which keeps all of the files shipped in the GDRs. Customers do not need to download all of the binaries contained in a package when they already have the version of the dependent binaries on their system when they get the new patch. Customers only need to test the binaries which have changed, rather than everything in the new package, which speeds up the deployment of critical patches.

Abstract: A code fix is communicated using an automatically executable code patch that has an additional code element that allows the code to perform the functions of registration, detection, setup, reporting, tracking, policy verification or clean up.

Abstract: A system and method for last known good (LKG) for patches. A file cache is created to store binaries which have shipped as part of a previous wide public release—security fixes (GDRs) and service packs. There are two levels of cache, including an SP cache which keeps all of the files which were shipped as part of the service pack, and a GDR cache which keeps all of the files shipped in the GDRs. Customers do not need to download all of the binaries contained in a package when they already have the version of the dependent binaries on their system when they get the new patch. Customers only need to test the binaries which have changed, rather than everything in the new package, which speeds up the deployment of critical patches.