Abstract: Embodiments presented herein techniques for balancing a multidimensional set of resources of different types within a distributed resources system. Each host computer providing the resources publishes a status on current resource usage by guest clients. Upon identifying a local imbalance, the host computer determines a source workload to migrate to or from the resources container to minimize the variance in resource usage. Additionally, when placing a new resource workload, the host computer selects a resources container that minimizes the variance to further balance resource usage.

Abstract: Embodiments of the disclosure provide techniques for partitioning a resource object into multiple resource components of a cluster of host computer nodes in a distributed resources system. The distributed resources system translates high-level policy requirements into a resource configuration that the system accommodates. The system determines an allocation based on the policy requirements and identifies resource configurations that are available. Upon selecting a resource configuration, the distributed resources system assigns the allocation and associated values to the selected configuration and publishes the new configuration to other host computer nodes in the cluster.

Abstract: The disclosure herein describes providing and accessing data on an object storage platform using a log-structured merge (LSM) tree file system. The LSM tree file system on the object storage platform includes sorted data tables, each sorted data table including a payload portion and an index portion. Data is written to the LSM tree file system in at least one new sorted data table. Data is ready by identifying a data location of the data based on index portions of the sorted data tables and reading the data from a sorted data table associated with the identified data location. The use of the LSM tree file system on the object storage platform provides an efficient means for interacting with the data stored thereon.

Abstract: The present disclosure provides techniques for managing a cache of a computer system using a cache management data structure. The cache management data structure includes a cold queue, a ghost queue, and a hot queue. The techniques herein improve the functioning of the computer because management of the cache management data structure can be performed in parallel with multiple cores or multiple processors, because a sequential scan will only pollute (i.e., add unimportant memory pages) cold queue, and to an extent, ghost queue, but not hot queue, and also because the cache management data structure has lower memory requirements and lower CPU overhead on cache hit than some prior art algorithms.

Abstract: The disclosure herein describes synchronizing cached index copies at a first site with indexes of a log-structured merge (LSM) tree file system on an object storage platform at a second site. An indication that the LSM tree file system has been compacted based on a compaction process is received. A cached metadata catalog of the included parent catalog version at the first site is accessed. A set of cached index copies is identified at the first site based on the metadata of the cached metadata catalog. The compaction process is applied to the identified set of cached index copies and a compacted set of cached index copies is generated at the first site, whereby the compacted set of cached index copies is synchronized with a respective set of indexes of the plurality of sorted data tables of the LSM tree file system at the second site.

Abstract: The present disclosure provides techniques for scaling out deduplication of files among a plurality of nodes. The techniques include designating a master component for the coordination of deduplication. The master component divides files to be deduplicated among several slave nodes, and provides to each slave node a set of unique identifiers that are to be assigned to chunks during the deduplication process. The techniques herein preserve integrity of the deduplication process that has been scaled out among several nodes. The scaled out deduplication process deduplicates files faster by allowing several deduplication modules to work in parallel to deduplicate files.

Abstract: Techniques for decoupling compute and storage resources in a hyper-converged infrastructure (HCI) are provided. In one set of embodiments, a control plane of the HCI deployment can provision a host from a host platform of an infrastructure on which the HCI deployment is implemented and can provision one or more storage volumes from a storage platform of the infrastructure, where the storage platform runs on physical server resources in the infrastructure that are separate from the host platform. The control plane can then cause the one or more storage volumes to be network-attached to the host in a manner that enables a hypervisor of the host to make the one or more storage volumes available, as part of a virtual storage pool, to one or more virtual machines in the HCI deployment for data storage.

Abstract: Embodiments of the disclosure provide techniques for partitioning a resource object into multiple resource components of a cluster of host computer nodes in a distributed resources system. The distributed resources system translates high-level policy requirements into a resource configuration that the system accommodates. The system determines an allocation based on the policy requirements and identifies resource configurations that are available. Upon selecting a resource configuration, the distributed resources system assigns the allocation and associated values to the selected configuration and publishes the new configuration to other host computer nodes in the cluster.

Abstract: Embodiments presented herein techniques for balancing a multidimensional set of resources of different types within a distributed resources system. Each host computer providing the resources publishes a status on current resource usage by guest clients. Upon identifying a local imbalance, the host computer determines a source workload to migrate to or from the resources container to minimize the variance in resource usage. Additionally, when placing a new resource workload, the host computer selects a resources container that minimizes the variance to further balance resource usage.

Abstract: Techniques for decoupling compute and storage resources in a hyper-converged infrastructure (HCI) are provided. In one set of embodiments, a control plane of the HCI deployment can provision a host from a host platform of an infrastructure on which the HCI deployment is implemented and can provision one or more storage volumes from a storage platform of the infrastructure, where the storage platform runs on physical server resources in the infrastructure that are separate from the host platform. The control plane can then cause the one or more storage volumes to be network-attached to the host in a manner that enables a hypervisor of the host to make the one or more storage volumes available, as part of a virtual storage pool, to one or more virtual machines in the HCI deployment for data storage.

Abstract: Techniques are disclosed for maintaining high availability (HA) for virtual machines (VMs) running on host systems of a host cluster, where each host system executes a HA module in a plurality of HA modules and a storage module in a plurality of storage modules, where the host cluster aggregates, via the plurality of storage modules, locally-attached storage resources of the host systems to provide an object store, where persistent data for the VMs is stored as per-VM storage objects across the locally-attached storage resources comprising the object store, and where a failure causes the plurality of storage modules to observe a network partition in the host cluster that the plurality of HA modules do not. In one embodiment, a host system in the host cluster executing a first HA module invokes an API exposed by the plurality of storage modules for persisting metadata for a VM to the object store.

Abstract: Embodiments of the disclosure provide techniques for measuring congestion and controlling quality of service to a shared resource. A module that interfaces with the shared resource monitors the usage of the shared resource by accessing clients. Upon detecting that the rate of usage of the shared resource has exceeded a maximum rate supported by the shared resource, the module determines and transmits a congestion metric to clients that are currently attempting to access the shared resource. Clients, in turn determine a delay period based on the congestion metric prior to attempting another access of the shared resource.

Abstract: Examples disclosed herein relate to propagating changes made on a file system volume of a primary cluster of nodes to the same file system volume also being managed by a secondary cluster of nodes. An application is executed on both clusters, and data changes on the primary cluster are mirrored to the secondary cluster using an exo-clone file. The exo-clone file includes the differences between two or more snapshots of the volume on the primary cluster, along with identifiers of the change blocks and (optionally) state information thereof. Just these changes, identifiers, and state information are packaged in the exo-clone file and then exported to the secondary cluster, which in turn makes the changes to its version of the volume. Exporting just the changes to the data blocks and the corresponding block identifiers drastically reduces the information needed to be exchanged and processed to keep the two volumes consistent.

Abstract: The present disclosure provides techniques for deallocating previously allocated storage blocks. The techniques include obtaining a list of chunk IDs to analyze, choosing a chunk ID, and determining the storage blocks spanned by the chunk corresponding to the chosen chunk ID. The technique further includes determining whether any file references any storage blocks spanned by the chunk. The determining may be performed by comparing an internal reference count to a total reference count, where the internal reference count is the number of reference to the storage block by a chunk ID data structure. If no files reference any of the storage blocks spanned by the chunk, then all the storage blocks of the chunk can be deallocated.

Abstract: The disclosure provides techniques for deduplicating files. The techniques include, upon creating or modifying a file, placing a logical timestamp of the current logical time, within a queue associated with the directory of the file. The techniques further include placing the logical timestamp within a queue of each parent directory of the directory of the file. To determine a set of files for deduplication, the techniques disclosed herein identify files that have been modified within a logical time range. The set of files modified within a logical time is identified by traversing directories of a storage system, the directories being organized within a tree structure. If a directory's queue does not contain a timestamp that is within the logical time range, then all child directories can be skipped over for further processing, such that no files within the child directories end up being within the set of files for deduplication.

Abstract: The present disclosure provides techniques for deduplicating files. The techniques include creating a data structure that organizes metadata about chunks of files, the organization of the metadata preserving order and locality of the chunks within files. The organization of the metadata within storage blocks of storage devices matches the order of chunks within files. Upon a read or write operation to a metadata, the preservation of locality of metadata results in the likely fetching, from storage into a memory cache, metadata of subsequent and contiguous chunks. The preserved locality results in faster subsequent read and write operations of metadata, because the read and write operations are likely to be executed from memory rather than from storage.

Abstract: The present disclosure provides techniques for scaling out deduplication of files among a plurality of nodes. The techniques include designating a master component for the coordination of deduplication. The master component divides files to be deduplicated among several slave nodes, and provides to each slave node a set of unique identifiers that are to be assigned to chunks during the deduplication process. The techniques herein preserve integrity of the deduplication process that has been scaled out among several nodes. The scaled out deduplication process deduplicates files faster by allowing several deduplication modules to work in parallel to deduplicate files.

Abstract: The present disclosure provides techniques for deduplicating files. The techniques include creating a cache or subset of a large data structure. The large data structure organizes information by random hash values. The random hash values result in a random organization of information within the data structure, with the information spanning a large number of storage blocks within a storage system. The cache, however, is within memory and is small relative to the data structure. The cache is created so as to contain information that is likely to be needed during deduplication of a file. Having needed information within memory rather than in storage results in faster read and write operations to that information, improving the performance of a computing system.

Abstract: Disclosed techniques include deduplication. Techniques include determining whether a file is unique, and depending on whether the file is unique, deduplicating only part of the file or the entire file. The techniques include processing the first chunk of a file to determine whether the hash of the chunk hash is already within a chunk hash table, and if not, then a percentage of chunks of the file is similarly processed. If any of the hashes of chunks are already in the chunk hash table, then at least some of file has been previously deduplicated, and file is not unique the storage system. If none of the processed chunks have a hash that is already in the chunk hash table, then the file is considered to be unique within chunk store and only a partial percentage of the file's chunks are deduplicated. Not all of a unique file's chunks are deduplicated.

Abstract: Certain aspects provide systems and methods of compacting data within a log-structured merge tree (LSM tree) using sharding. In certain aspects, a method includes determining a size of the LSM tree, determining a compaction time for a compaction of the LSM tree based on the size, determining a number of compaction entities for performing the compaction in parallel based on the compaction time, determining a number of shards based on the number of compaction entities, and determining a key range associated with the LSM tree. The method further comprises dividing the key range by the number of shards into a number of sub key ranges, wherein each of the number of sub key ranges corresponds to a shard of the number of shards and assigning the number of shards to the number of compaction entities for compaction.