Systems and methods for automated remediation of issues arising in a data management storage system are provided. Deployed assets of a storage solution vendor may deliver telemetry data to the vendor on a regular basis. The received telemetry data may be processed by an AIOps platform to perform predictive analytics and arrive at “community wisdom” from the vendor's installed user base. In one embodiment, an insight-based approach is used to facilitate risk detection and remediation including proactively addressing issues before they turn into more serious problems. For example, based on continuous learning based on the community wisdom and making one or both of a rule set and a remediation set derived therefrom available for use by cognitive computing co-located with a customer's storage system, a risk to which the storage system is exposed may be determined and a corresponding remediation may be deployed to address or mitigate the risk.
Techniques are provided for on-demand creation and/or utilization of containers and/or serverless threads for hosting data connector components. The data connector components can be used to perform integrity checking, anomaly detection, and file system metadata analysis associated with objects stored within an object store. The data connector components may be configured to execute machine learning functionality to perform operations and tasks. The data connector components can perform full scans or incremental scans. The data connector components may be stateless, and thus may be offlined, upgraded, onlined, and/or have tasks transferred between data connector components. Results of operations performed by the data connector components upon base objects may be stored within sibling objects.
G06F 16/2457 - Query processing with adaptation to user needs
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 16/21 - Design, administration or maintenance of databases
G06F 16/22 - Indexing; Data structures therefor; Storage structures
G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
3.
DATA MANAGEMENT ACROSS A PERSISTENT MEMORY TIER AND A FILE SYSTEM TIER
Techniques are provided for data management across a persistent memory tier and a file system tier. A block within a persistent memory tier of a node is determined to have up-to-date data compared to a corresponding block within a file system tier of the node. The corresponding block may be marked as a dirty block within the file system tier. Location information of a location of the block within the persistent memory tier is encoded into a container associated with the corresponding block. In response to receiving a read operation, the location information is obtained from the container. The up-to-date data is retrieved from the block within the persistent memory tier using the location information for processing the read operation.
Techniques are provided for implementing additional compression for existing compressed data. Format information stored within a data block is evaluated to determine whether the data block is compressed or uncompressed. In response to the data block being compressed according to a first compression format, the data block is decompressed using the format information. The data block is compressed with one or more other data blocks to create compressed data having a second compression format different than the first compression format.
One or more techniques and/or computing devices are provided for synchronous replication. For example, synchronous replication relationships are established between a first storage object (e.g., a file, a logical unit number (LUN), a consistency group, etc.), hosted by a first storage controller, and a plurality of replication storage objects hosted by other storage controllers. In this way, a write operation to the first storage object is implemented in parallel upon the first storage object and the replication storage objects in a synchronous manner, such as using a zero-copy operation to reduce overhead otherwise introduced by performing copy operations. Reconciliation is performed in response to a failure so that the first storage object and the replication storage objects comprise consistent data. Failed write operations and replication write operations are retried, while enforcing a single write semantic. Dependent write order consistency is enforced for dependent write operations, such as overlapping write operations.
G06F 3/06 - Digital input from, or digital output to, record carriers
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
6.
EXTENSIBLE AND ELASTIC DATA MANAGEMENT SERVICES ENGINE EXTERNAL TO A STORAGE DOMAIN
A data management services architecture includes architectural components that run in both a storage and compute domains. The architectural components redirect storage requests from the storage domain to the compute domain, manage resources allocated from the compute domain, ensure compliance with a policy that governs resource consumption, deploy program code for data management services, dispatch service requests to deployed services, and monitor deployed services. The architectural components also include a service map to locate program code for data management services, and service instance information for monitoring deployed services and dispatching requests to deployed services. Since deployed services can be stateless or stateful, the services architecture also includes state data for the stateful services, with supporting resources that can expand or contract based on policy and/or service demand. The architectural components also include containers for the deployed services.
G06F 16/20 - Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
H04L 67/142 - Managing session states for stateless protocols; Signalling session states; State transitions; Keeping-state mechanisms
H04L 67/63 - Routing a service request depending on the request content or context
7.
AUTOMATED REMEDIATION OF ISSUES ARISING IN A DATA MANAGEMENT STORAGE SOLUTION
Systems and methods for automated remediation of issues arising in a data management storage system are provided. Deployed assets of a storage solution vendor may deliver telemetry data to the vendor on a regular basis. The received telemetry data may be processed by an AIOps platform to perform predictive analytics and arrive at “community wisdom” from the vendor's installed user base. In one embodiment, an insight-based approach is used to facilitate risk detection and remediation including proactively addressing issues before they turn into more serious problems. For example, based on continuous learning based on the community wisdom and making one or both of a rule set and a remediation set derived therefrom available for use by cognitive computing co-located with a customer's storage system, a risk to which the storage system is exposed may be determined and a corresponding remediation may be deployed to address or mitigate the risk.
Techniques are provided for incremental snapshot copy to an object store. A list of deallocated block numbers of primary storage of a computing device are identified. Entries for the list of deallocated block numbers are removed from a mapping metafile. A list of changed block numbers corresponding to changes between a current snapshot of the primary storage and a prior copied snapshot copied from the primary storage to the object store is determined. The mapping metafile is evaluated using the list of changed block numbers to identify a deduplicated set of changed block numbers without entries within the mapping metafile. An object, comprising data of the deduplicated set of changed block numbers, is transmitted to the object store for storage as a new copied snapshot.
Techniques are provided for incremental backup to an object store. A request may be received from an application to perform a backup from a volume hosted by a node to a backup target within the object store. A set of changed files within the volume since a prior backup of the volume was performed to the backup target is identified, along with metadata associated with the set of changed files. The metadata is utilized to identify changed data blocks comprising data of the set of changed files that was modified since the prior backup. The changed data blocks are backed up to the object store.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
10.
MECHANISM TO MAINTAIN DATA COMPLIANCE WITHIN A DISTRIBUTED FILE SYSTEM
A method performed by one or more processing resources of one or more computer systems is disclosed. The method comprises receiving an object at a first of a plurality of nodes from a second of the plurality of storage nodes within a cluster switch fabric, examining a value associated included within the received object, wherein the value is associated with a clock value of the second node and updating a clock operating at the first node with the received value.
Techniques are provided for failing over an aggregate from one file system instance to a different file system instance of a distributed scale-out storage system. The aggregate may be stored within distributed storage that is accessible to a plurality of file system instances of the distributed scale-out storage system. When the aggregate is failed over from a first file system instance to a second file system instance, the first file system instance may still have a valid read lease that allows the first file system instance to serve client I/O, directed to the aggregate, using a cache. In order to prevent the first file system instance from serving stale data from the cache before the read lease expires, state machines and a set of control data are used to ensure that the second file system instance attaches to the aggregate only after the read lease has expired.
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
G06F 11/16 - Error detection or correction of the data by redundancy in hardware
12.
MECHANISM TO MAINTAIN DATA COMPLIANCE WITHIN A DISTRIBUTED FILE SYSTEM
A method performed by one or more processing resources of one or more computer systems is disclosed. The method comprises receiving an object at a first of a plurality of nodes from a second of the plurality of storage nodes within a cluster switch fabric, examining a value associated included within the received object, wherein the value is associated with a clock value of the second node and updating a clock operating at the first node with the received value.
CROSS-SITE HIGH-AVAILABILITY DISTRIBUTED CLOUD STORAGE SYSTEM TO MONITOR VIRTUAL CHANNELS BETWEEN STORAGE NODES AND PREVENT CHANNEL SHARING OF A RECEIVE QUEUE
According to one embodiment, a computer implemented method comprises providing multiple channels between a first storage node and a second storage node with each channel having a separate network connection for packets of a transport layer session, assigning packets from each channel to a group of receive queues of the second storage node, continuously monitoring whether two or more channels of the multiple channels share a same receive queue of the second storage node, and sending a communication via a channel to the first storage node to indicate a dynamic change in a hash input field (e.g., a source port, a destination port, a source internet protocol (IP) address, and a destination IP address) when two or more channels of the multiple channels share a same receive queue of the second storage node.
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
H04L 67/1023 - Server selection for load balancing based on a hash applied to IP addresses or costs
A method, computing device, and non-transitory machine-readable medium for detecting malware attacks and mitigating data loss. In various embodiments, an agent is implemented in the operating system of a storage node to provide protection at the bottommost level in a data write path. The agent intercepts write requests and observes file events over time to detect anomalous behavior. For example, the agent may monitor incoming write requests and, when an incoming write request is detected, determine whether the file is associated with a malware attack risk based on an analysis of an encryption state of data in the file.
G06F 21/56 - Computer malware detection or handling, e.g. anti-virus arrangements
G06F 21/54 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems during program execution, e.g. stack integrity, buffer overflow or preventing unwanted data erasure by adding security routines or objects to programs
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
Systems and methods for performing single I/O writes are provided. According to one embodiment, responsive to receipt of a write operation from a client by a file system layer of a node of a distributed storage system and a data payload of the operation having been determined to meet a compressibility threshold, an intermediate storage layer of the node logically interposed between the file system layer and a block storage media is caused to perform a single input/output (I/O) write operation that persists the compressed data payload and corresponding metadata to support asynchronous journaling of the write operation. The single I/O write operation coupled with the use of a new pool file that maintains a list of available blocks for single I/O write operations and a modified node crash recovery approach allows the write operation to be acknowledged to the client while the journaling is performed asynchronously.
Techniques are provided for coupled compute and storage resource autoscaling. Applications may be hosted within an application hosting environment (e.g., containerized applications hosted within Kubernetes) that allocations certain amounts of compute resources (e.g., processor and memory resources) to the applications for execution. The applications may store data within persistent of a backend storage platform separate from the application hosting environment. An autoscaler monitors the health of storage resources allocated to an application during deployment and runtime of the application so that issues with the storage resources can be preemptively identified and resolved for non-disruptive operation of the application. The autoscaler scales both the compute resources and the storage resources assigned to the application so that the application can continue operation in a non-disruptive manner.
Systems and methods are provided for sharing ephemeral storage of a virtual machine (VM) for use as victim caches for virtual storage appliances running on the VM. According to one embodiment, a central service may run within the VM and be responsible for managing allocation and reclamation of ephemeral storage space of the VM to/from the virtual storage appliances. Responsive to startup of a new virtual storage appliance on the VM, the new virtual storage appliance may request space from the central service to inform creation of its victim cache. In connection with servicing the request, the central service may take into consideration various factors including one or more of the total aggregate size of multiple local ephemeral drives associated with the VM, remaining available ephemeral storage space, the number of active virtual storage appliances, and the SLO of the virtual storage appliance seeking to establish its victim cache.
One or more techniques and/or computing devices are provided for managing an arbitrary set of storage items using a granset. For example, a storage controller may host a plurality of storage items and/or logical unit numbers (LUNs). A subset of the storage items are grouped into a consistency group. A granset is created for tracking, managing, and/or providing access to the storage items within the consistency group. For example, the granset comprises application programming interfaces (APIs) and/or properties used to provide certain levels of access to the storage items (e.g., read access, write access, no access), redirect operations to access either data of an active file system or to a snapshot, fence certain operations (e.g., rename and delete operations), and/or other properties that apply to each storage item within the consistency group. Thus, the granset provides a persistent on-disk layout used to manage an arbitrary set of storage items.
Techniques are provided for block allocation for persistent memory during aggregate transition. In a high availability pair including first and second nodes, the first node makes a determination that control of a first aggregate is to transition from the first node to the second node. A portion of available free storage space is allocated from a first persistent memory of the first node as allocated pages within the first persistent memory. Metadata information for the allocated pages is updated with an identifier of the first aggregate to create updated metadata information reserving the allocated pages for the first aggregate. The updated metadata information is mirrored to the second node, so that the second node also reserves those pages. Control of the first aggregate is transitioned to the second node. As a result, the nodes do not attempt allocating the same free pages to different aggregates during a transition.
One or more systems, devices, computer program products, and/or computer-implemented methods provided herein to use a redundant array of disks. A system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components can comprise a control component that directs, for n physical drives of a redundant array of disks (RAID) storing data for at least n logical volumes, log-structured writing of data of each logical volume of the at least n logical volumes vertically across chunks of only a single physical drive of the n physical drives, wherein the control component further directs writing of parity data at each of the physical drives, which parity data at each physical drive of the subset respectively corresponds to other ones of the physical drives of the n physical drives.
In one embodiment, distributed data storage systems and methods integrate a change tracking manager with scalable databases. According to one embodiment, a computer implemented method comprises integrating change tracking of storage objects into the distributed object storage database that includes a first database of a first type and one or more chapter databases of a second type with the distributed object storage database supporting a primary lookup index and a secondary lookup index in order to locate a storage object. The method includes recording in a header of a chapter database a network topology for connecting a bucket having the chapter database to a first peer bucket when a new mirror to the first peer bucket is being established, and recording a first directive into the header of the chapter database to express a type of content to be mirrored from the bucket to the first peer bucket.
G06F 16/22 - Indexing; Data structures therefor; Storage structures
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
Methods and systems for a networked storage environment are provided. One method includes generating a plurality of metrics associated with a file system from a scan of the file system; defining a synthetic file tree based on a tree descriptor, a seed value and a total number of entries for the synthetic tree, the tree descriptor based on one or more of the plurality of metrics; utilizing, by a first worker process, a first portion of the tree descriptor and the seed value to generate a first subset of the synthetic file tree; and utilizing, by a second worker process, a second portion of the tree descriptor and the seed value to generate a second subset of the synthetic file tree.
Techniques are provided for utilizing a log to free pages from persistent memory. A log is maintained to comprise a list of page block numbers of pages within persistent memory of a node to free. A page block number, of a page, within the log is identified for processing. A reference count, corresponding to a number of references to the page block number, is identified. In response to the reference count being greater than 1, the reference count is decremented and the page block number is removed from the log. In response to the reference count being 1, the page is freed from the persistent memory and the page block number is removed from the log.
Techniques are provided for implementing write ordering for persistent memory. A set of actions are identified for commitment to persistent memory of a node for executing an operation upon the persistent memory. An episode is created to comprise a first subset of actions of the set of actions that can be committed to the persistent memory in any order with respect to one another such that a consistent state of the persistent memory can be reconstructed in the event of a crash of the node during execution of the operation. The first subset of actions within the episode are committed to the persistent memory and further execution of the operation is blocked until the episode completes.
G06F 3/06 - Digital input from, or digital output to, record carriers
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
Techniques are provided for on-demand serverless disaster recovery. A primary node may host a primary volume. Snapshots of the primary volume may be backed up to an object store. In response to failure, a secondary node and/or an on-demand volume may be created on-demand. The secondary node may provide clients with failover access to the on-demand volume while a restore process restores a snapshot of the primary volume to the on-demand volume. In some embodiments, there was no secondary node and/or on-demand volume while the primary node was operational. This conserves computing resources that would be wasted by otherwise hosting the secondary node and/or on-demand volume while clients were able to access the primary volume through the primary node. Modifications directed to the on-demand volume are incrementally backed up to the object store for subsequently restoring the primary volume after recovery.
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
26.
STORAGE AREA NETWORK ATTACHED CLUSTERED STORAGE SYSTEM
A storage area network (SAN)-attached storage system architecture is disclosed. The storage system provides strongly consistent distributed storage communication protocol semantics, such as SCSI target semantics. The system includes a mechanism for presenting a single distributed logical unit, comprising one or more logical sub-units, as a single logical unit of storage to a host system by associating each of the logical sub-units that make up the single distributed logical unit with a single host visible identifier that corresponds to the single distributed logical unit. The system further includes mechanisms to maintain consistent context information for each of the logical sub-units such that the logical sub-units are not visible to a host system as separate entities from the single distributed logical unit.
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
H04L 43/10 - Active monitoring, e.g. heartbeat, ping or trace-route
27.
COLD DATA STORAGE ENERGY CONSUMPTION EVALUATION AND RESPONSE
Various mechanisms and workflows are described that can utilize power and/or carbon footprint-based metrics to manage storage unit usage and/or configuration, which can provide a more efficient and environmentally friendly computing environment. In some example configurations, storage system management mechanisms collect power consumption for storage units (e.g., individual drives, storage shelfs, nodes, clusters) and can utilize the power consumption information with other storage unit characteristics to generate power and carbon footprint metrics.
Techniques are provided for repairing a primary slice file, affected by a storage device error, by using one or more dead replica slice files. The primary slice file is used by a node of a distributed storage architecture as an indirection layer between storage containers (e.g., a volume or LUN) and physical storage where data is physically stored. To improve resiliency of the distributed storage architecture, changes to the primary slice file are replicated to replica slice files hosted by other nodes. If a replica slice file falls out of sync with the primary slice file, then the replica slice file is considered dead (out of sync) and could potentially comprise stale data. If a storage device error affects blocks storing data of the primary slice file, then the techniques provided herein can repair the primary slice file using non-stale data from one or more dead replica slice files.
Systems and methods for an improved HA resource reservation approach are provided. According to one embodiment, for a given cluster of greater than two nodes in which a number (f) of concurrent node failures are to be tolerated, more efficient utilization of resources for an HA system may be achieved by distributing HA reserved capacity across more than f nodes of the cluster rather than naively concentrating the HA reserved capacity in f nodes. As node failures are not a common occurrence, those of the nodes of the cluster having HA reserved capacity may allow for some bursting of one or more units of compute executing thereon unless or until f concurrent node failures occur, thereby promoting more efficient utilization of node resources.
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]
30.
REBALANCING SCANNER FOR USE IN REBALANCING FILES IN A DISTRIBUTED FILE SYSTEMS
Redistribution of files in a containerized distributed file system is disclosed. An indication of at least one remote container to which files from the local container are to be transferred is received from a rebalancing engine in the local container. One or more transfer parameters for use in selecting one or more files in the local container to be transferred the at least one remote container are received from the rebalancing engine. The local container is scanned to identify files that satisfy the one or more transfer parameters. An indication of the identified files to a file transfer mechanism is provided. Operation of the scanner is terminate until triggered in response to a query by the engine of the local container or for a predetermined period of time.
H04L 67/1029 - Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers using data related to the state of servers by a load balancer
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
31.
Co-located Journaling and Data Storage for Write Requests
Methods and systems for co-locating journaling and data storage are provided. Separate journal and volume partitions may be maintained within each logical storage unit (e.g., Logical Unit Number (LUN)) of a distributed storage system. Journaling of metadata associated with write requests received from one or more clients may be distributed by identifying a destination logical storage unit to which data associated with a given write request is to be stored and causing the data and metadata to be persisted to disk by journaling the metadata and the data to respective portions of an active log within the journal partition of the destination logical storage unit. By using the same logical storage unit for both journaling of write requests and writing the data associated with such write requests, the bottleneck due to there being only a single device or storage unit handling all metadata for all write requests can be avoided.
Approaches and mechanisms for cloning a file are described. A first node requests a clone of a file at a time when it also requests an exclusive delegation of the original file from a second node where the original file is stored. The second node marks the original file as delegated to the first node and the second node records an intent to create the clone file and a delegation record for the clone file. The second node creates the clone file. The delegation of and the identity of the clone file are returned to the first node. The first node marks in the delegation record that the clone file was committed in response to modification. If the clone file was committed the delegation is cleared and the clone file is kept, and if the clone file was not committed, the delegation is cleared, and the clone file is deleted.
Redistribution of files in a containerized distributed file system is disclosed. Containers each have an engine and a scanner and each of the containers stores files and parameters for characteristics of files stored on the container. A first engine in a first container monitors characteristics of files stored on the first container and, responsive to determining that the parameters for files on the first container exceed one or more predetermined thresholds, communicates with a second engine in a second container to determine a destination container for one or more files from the first container. The second engine in the second container indicates to the first engine in the first container whether the second container is available to receive one or more files from the first container. The first engine triggers file system scanning by the scanner of the first container to identify files to be moved to the second container.
Techniques are provided for implementing asynchronous region-aware caching for snapshot prefetching and restore. A first application within a first container of a container orchestration platform may be hosted at a first region of a multi-cloud environment. A second application within a second container of the container orchestration platform may be hosted at a second region of the multi-cloud environment. Data of the first application may be stored within storage located within the first region of the multi-cloud environment. In response to determining that the second application has a threshold probability of accessing the data of the first application (e.g., a snapshot that the second application can restore), the data may be cached as cached data within a network edge of the second region for access by the second application.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
35.
SPARE RESOURCE AVAILABILITY PREDICTION WITH LIMITED HISTORICAL DATA
A system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a correlation component that, based on a first context defining a first spare resource instance to be utilized in a networked system, identifies a second spare resource instance, and an evaluation component that generates an availability score defining prediction of availability of the first spare resource instance based on a second context defining the second spare resource instance, wherein the evaluation component further deploys the first spare resource instance, based on the availability score, in the networked system.
Techniques are provided for a recovery process with selective ordering and concurrent operations in order to recover from a failure. Representations of active log structures are rebuilt within memory according to ordering values assigned to I/O operations logged within the active log structures. Representation of certain active log structures may be concurrently rebuilt based upon the active log structures comprising I/O operations that are non-overlapping within a distributed file system, have no dependencies, relate to different services, and/or target independent files. Representation of stale log structures are concurrently rebuilt within memory. While rebuilding the log structures and executing the I/O operations, a key value map is concurrently rebuilt within the memory for locating data of the I/O operations. Concurrent operations during the recovery process reduces the time to complete the recovery process, and thus reduces client downtime during the recovery process.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
37.
METHODS FOR DYNAMIC THROTTLING TO SATISFY MINIMUM THROUGHPUT SERVICE LEVEL OBJECTIVES AND DEVICES THEREOF
Methods, non-transitory machine readable media, and computing devices that dynamically throttle non-priority workloads to satisfy minimum throughput service level objectives (SLOs) are disclosed. With this technology, a determination is made when a number of detection intervals with a violation within a detection window exceeds a threshold, when a current one of the detection intervals is outside an observation area. The detection intervals are identified a violated based on an average throughput for priority workloads within the detection intervals exceeding a minimum throughput SLO. A throttle is then set to rate-limit non-priority workloads, when the number of violated detection intervals within the detection window exceeds the threshold. Advantageously, throughput for priority workloads is more effectively managed and utilized with this technology such that throttling oscillations are reduced, throttling is not deployed in conditions in which it would not improve throughput, and throttling is minimally deployed to maximize throughput.
Various mechanisms and workflows are described that can utilize power and/or carbon footprint-based metrics to manage storage unit usage and/or configuration, which can provide a more efficient and environmentally friendly computing environment. In some example configurations, storage system management mechanisms collect power consumption for storage units (e.g., individual drives, storage shelfs, nodes, clusters) and can utilize the power consumption information with other storage unit characteristics to generate power and carbon footprint metrics.
Methods and systems for a storage environment are provided. One method includes copying a data unit from a first temporary storage location corresponding to each zoned solid-state drive (ZNS SSD) of a first ZNS SSD set of a storage system to a first XOR module, while determining a first partial horizontal parity using the data unit stored in the first temporary storage location; and determining a vertical parity for each ZNS SSD of the first ZNS SSD set using the data unit provided to the first XOR module in a current cycle and vertical parity determined from a previous cycle.
The disclosed technology relates to determining physical zone data within a zoned namespace solid state drive (SSD), associated with logical zone data included in a first received input-output operation based on a mapping data structure within a namespace of the zoned namespace SSD. A second input-output operation specific to the determined physical zone data is generated wherein the second input-output operation and the received input-output operation is of a same type. The generated second input-output operation is completed using the determined physical zone data within the zoned namespace SSD.
Techniques are provided for key-value store and file system integration to optimize key value store operations. A key-value store is integrated within a file system of a node. A log structured merge tree of the key-value store may be populated with a key corresponding to a content hash of a value data item stored separate from the key. A random distribution search may be performed upon a sorted log of the log structured merge tree to identify the key for accessing the value data item. A starting location for the random distribution search is derived from key information, a log size of the sorted log, and/or a keyspace size of a keyspace associated with the key.
G06F 16/215 - Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
42.
Methods and systems to interface between a multi-site distributed storage system and an external mediator to efficiently process events related to continuity
Systems and methods are described for efficiently processing events related to a relationship between a primary copy of data at a primary storage system and a mirror copy of the data at a cross-site secondary storage system of a multi-site distributed storage system. According to an example, a mediator agent that is configured on both primary and secondary storage systems provides coordination and serialization for various events generated in the relationship. The multi-site distributed storage system performs actions based on the event processing such as performing a failover operation from the primary storage system to the secondary storage system or resynchronizing the relationship to ensure application protection and availability.
G06F 3/00 - Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
G06F 3/06 - Digital input from, or digital output to, record carriers
43.
AUTOMATED REMEDIATION OF ISSUES ARISING IN A DATA MANAGEMENT STORAGE SOLUTION
Systems and methods for automated remediation of issues arising in a data management storage system are provided. Deployed assets of a storage solution vendor may deliver telemetry data to the vendor on a regular basis. The received telemetry data may be processed by an AIOps platform to perform predictive analytics and arrive at “community wisdom” from the vendor's installed user base. In one embodiment, an insight-based approach is used to facilitate risk detection and remediation including proactively addressing issues before they turn into more serious problems. For example, based on continuous learning based on the community wisdom and making one or both of a rule set and a remediation set derived therefrom available for use by cognitive computing co-located with a customer's storage system, a risk to which the storage system is exposed may be determined and a corresponding remediation may be deployed to address or mitigate the risk.
Techniques are provided for implementing a distributed control plane to facilitate communication between a container orchestration platform and a distributed storage architecture. The distributed storage architecture hosts worker nodes that manage distributed storage that can be made accessible to applications within the container orchestration platform through the distributed control plane. The distributed control plane includes control plane controllers that are each paired with a single worker node of the distributed storage architecture. The distributed control plane is configured to selectively route commands to control plane controllers that are paired with worker nodes that are current owners of objects targeted by the commands. If ownership of an object has changed from one worker node to another worker node, then subsequent commands will be re-routed to a control plane controller paired with the other worker node now owning the object.
G06F 3/06 - Digital input from, or digital output to, record carriers
45.
METHODS AND SYSTEMS TO IMPROVE INPUT/OUTPUT (I/O) RESUMPTION TIME DURING A NON-DISRUPTIVE AUTOMATIC UNPLANNED FAILOVER FROM A PRIMARY COPY OF DATA AT A PRIMARY STORAGE SYSTEM TO A MIRROR COPY OF THE DATA AT A CROSS-SITE SECONDARY STORAGE SYSTEM
Multi-site distributed storage systems and computer-implemented methods are described for improving a resumption time of input/output (I/O) operations during an automatic unplanned failover (AUFO). A computer-implemented method includes monitoring, with a second cluster, heartbeat information received at ultra-short time intervals from a first connection of one or more storage objects of the first cluster, determining, with the second cluster, whether the heartbeat information from the first connection is received during an ultra-short time interval, and intelligently routing heartbeat information from the one or more storage objects of the first cluster from the first connection to a second connection when the heartbeat information from the first connection is not received during the ultra-short time interval.
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
G06F 11/07 - Responding to the occurrence of a fault, e.g. fault tolerance
46.
METHODS AND SYSTEMS TO IMPROVE INPUT/OUTPUT (I/O) RESUMPTION TIME BY BATCHING MULTIPLE NON-CONFLICTING OPERATIONS DURING A NON-DISRUPTIVE AUTOMATIC UNPLANNED FAILOVER FROM A PRIMARY COPY OF DATA AT A PRIMARY STORAGE SYSTEM TO A MIRROR COPY OF THE DATA AT A CROSS-SITE SECONDARY STORAGE SYSTEM
Multi-site distributed storage systems and computer-implemented methods are described for improving a resumption time of input/output (I/O) operations during an automatic unplanned failover (AUFO). A computer-implemented method includes determining, with a second storage cluster, whether heartbeat information from one or more storage objects of a CG of a first set of CGs is received during a time period, determining an out of sync state for a data replication relationship between the CG of the first set of CGs and a mirrored CG of a second set of CGs when the heartbeat information is not received during the time period and sending a single bulk role change call with a cluster identifier from the second cluster to an external mediator to provide a role change from follower to leader in the second set of CGs.
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
47.
METHODS AND SYSTEMS FOR MANAGING A RESOURCE IN A NETWORKED STORAGE ENVIRONMENT
Methods and systems for a networked storage system are provided. One method includes receiving a resource identifier identifying a resource of a network storage environment as an input to a processor executable application programming interface (API); and predicting available performance capacity of the resource by using an optimum utilization of the resource, a current utilization and a predicted utilization based on impact of a workload change at the resource, where the optimum utilization is an indicator of resource utilization beyond which throughput gains for a workload is smaller than increase in latency in processing the workload.
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
48.
METHODS AND SYSTEMS TO IMPROVE RESUMPTION TIME OF INPUT/OUTPUT (I/O) OPERATIONS BASED ON PREFETCHING OF CONFIGURATION DATA AND EARLY ABORT OF CONFLICTING WORKFLOWS DURING A NON-DISRUPTIVE AUTOMATIC UNPLANNED FAILOVER FROM A PRIMARY COPY OF DATA AT A PRIMARY STORAGE SYSTEM TO A MIRROR COPY OF THE DATA AT A CROSS-SITE SECONDARY STORAGE SYSTEM
Multi-site distributed storage systems and computer-implemented methods are described for improving a resumption time for processing of input/output (I/O) operations during an automatic unplanned failover (AUFO). A first storage cluster includes a first set of consistency groups (CGs) and a second storage cluster includes a second mirrored set of CGs. A computer-implemented method includes prefetching, with a user space of the second storage cluster, configuration information from a replicated database prior to starting the AUFO workflow, sending the configuration information to a kernel space of the second storage cluster on a per CG level while queuing the AUFO workflow, and determining if any in progress workflows conflict with the AUFO workflow.
Methods and systems for solid state drives are provided, including assigning a first namespace to a first instance of a storage operating system and a second instance of the storage operating system for enabling read access to a first portion of a flash storage system by the first instance, and read and write access to the second instance; allocating a second namespace to the first instance for exclusive read and write access within a second portion of the flash storage system; generating, by the first instance, a request for the second instance to transfer a data object from the second portion owned by the first instance to the first portion; storing, by the second instance, the data object at the first portion; and updating metadata of the data object at the second portion, the metadata indicating a storage location at the second portion where the data object is stored.
Systems and methods that make use of cluster-level redundancy within a distributed storage management system to address various node-level error scenarios are provided. According to one embodiment, a first node of multiple nodes of distributed storage system represented in a form of a cluster of the multiple of nodes, identifies the potential existence of an error associated with a Redundant Array of Independent Disks (RAID) stripe. A list of block identifiers (IDs) associated with the RAID stripe may then be identified. Rather than performing a traditional RAID recovery/reconstruction approach that is resource intensive in nature and that requires an excessive amount of rebuild time, a more efficient RAID stripe resynchronization process may be performed to restore data associated with the RAID stripe.
G06F 11/16 - Error detection or correction of the data by redundancy in hardware
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
G06F 11/10 - Adding special bits or symbols to the coded information, e.g. parity check, casting out nines or elevens
Techniques are provided for implementing a distributed control plane to facilitate communication between a container orchestration platform and a distributed storage architecture. The distributed storage architecture hosts worker nodes that manage distributed storage that can be made accessible to applications within the container orchestration platform through the distributed control plane. The distributed control plane includes control plane controllers that are each paired with a single worker node of the distributed storage architecture. Thus, the distributed control plane is configured to selectively route commands to control plane controllers that are paired with worker nodes that are current owners of objects targeted by the commands. In this way, the control plane controllers can facilitate communication and performance of commands between the applications of the container orchestration platform and the worker nodes of the distributed storage architecture.
Systems and methods are for improving latency and throughput for metadata-heavy workloads and/or workloads including metadata bursts by decoupling data journal records and metadata-only journal records are provided. According to one embodiment, expedited and independent space reclamation is facilitated by differentiating between various types of journal records chains of which should be retained until different conditions are met. For example, data journal records may be added to data journal record chains within a persistent KV store and metadata-only journal records may be added to metadata-only journal record chains within the persistent KV store. Reclamation of spaced utilized by a data journal record chain may be reclaimed after both remote node data flush has been completed and the completion of a local CP for all records in the chain, whereas records of a metadata-only journal chain may be freed independently upon completion of a local CP for all records.
A method, a computing device, and a non-transitory machine-readable medium for detecting malware attacks. In one example, an agent implemented in an operating system detects an overwrite in which an original data component is overwritten with a new data component. The agent computes a plurality of features associated with the overwrite, the plurality of features including an original entropy corresponding to the original data component, a new entropy corresponding to the new data component, an overwrite fraction, and a set of divergence features. The agent determines whether the new data component is encrypted using the plurality of features.
Techniques are provided for multi-tier write allocation. A storage system may store data within a multi-tier storage environment comprising a first storage tier (e.g., storage devices maintained by the storage system), a second storage tier (e.g., a remote object store provided by a third party storage provider), and/or other storage tiers. A determination is made that data (e.g., data of a write request received by the storage system) is to be stored within the second storage tier. The data is stored into a staging area of the first storage tier. A second storage tier location identifier, for referencing the data according to a format utilized by the second storage tier, is assigned to the data and provided to a file system hosting the data. The data is then destaged from the staging area into the second storage tier, such as within an object stored within the remote object store.
G06F 11/10 - Adding special bits or symbols to the coded information, e.g. parity check, casting out nines or elevens
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
An application may store data to a dataset comprising a plurality of volumes stored on a plurality of storage systems. The application may request a dataset image of the dataset, the dataset image comprising a volume image of each volume of the dataset. A dataset image manager operates with a plurality of volume image managers in parallel to produce the dataset image, each volume image manager executing on a storage system. The plurality of volume image managers respond by performing requested operations and sending responses to the dataset image manager in parallel. Each volume image manager on a storage system may manage and produce a volume image for each volume of the dataset stored to the storage system. If a volume image for any volume of the dataset fails, or a timeout period expires, a cleanup procedure is performed to delete any successful volume images.
G06F 3/06 - Digital input from, or digital output to, record carriers
G06F 11/07 - Responding to the occurrence of a fault, e.g. fault tolerance
56.
Methods and storage nodes to decrease delay in resuming input output (I/O) operations after a non-disruptive event for a storage object of a distributed storage system by utilizing asynchronous inflight replay of the I/O operations
In one embodiment, a method comprises maintaining state information regarding a data replication status for a storage object of the storage node of a primary storage cluster with the storage object being replicated to a replicated storage object of a secondary storage cluster, temporarily disallowing input/output (I/O) operations when the storage object has a connection loss or failure. The method further includes initiating a resynchronization between the storage object and the replicated storage object including initiating asynchronous persistent inflight tracking and replay of any missing I/O operations that are missing from one of a first Op log of the primary storage cluster and a second Op log of the secondary storage cluster, and allowing new I/O operations to be handled with the storage object of the primary storage cluster without waiting for completion of the asynchronous persistent inflight tracking and replay at the secondary storage cluster.
Methods and systems for a networked storage environment are provided. One method includes splitting, by a first node, a payload into a plurality of data packets, each data packet having a portion of the payload indicated by an offset value indicating a position of each portion within the payload; transmitting, by the first node, the plurality of data packets to a second node using a network connection for a transaction, each data packet including a header generated by the first node having the offset value and a payload size; receiving, by the first node, a message from the second node indicating an offset value of a missing payload of a missing data packet from among the plurality of data packets; and resending, by the first node, the missing data packet and any other data packet whose offset value occurs after the offset value of the missing payload.
Systems and methods for identifying anomalous activities in a cloud computing environment are provided. According to one embodiment, a customer's infrastructure may be fortified by leveraging deep learning technology (e.g., an encoder-decoder machine-learning (ML) model) to predict events in the cloud environment. During a training phase, the ML model may be trained to make a prediction regarding a next event based on a predetermined or configurable length of a sequence of contextual events. For example, historical events (e.g., cloud application programming interface (API) events logged to a cloud activity trace) observed within the customer's cloud infrastructure over the course of a particular date range may be split into appropriate event/context pairs and fed to the ML model. Subsequently, during a run-time anomaly detection phase, the ML model may be used to predict a next event based on a sequence of immediately preceding events to facilitate identification of anomalous activity.
H04L 41/16 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
59.
AUTOMATICALLY TUNING A QUALITY OF SERVICE SETTING FOR A DISTRIBUTED STORAGE SYSTEM WITH A DEEP REINFORCEMENT LEARNING AGENT
Systems and methods are described for using a Deep Reinforcement Learning (DRL) agent to automatically tune Quality of Service (QoS) settings of a distributed storage system (DSS). According to one embodiment, a DRL agent is trained in a simulated environment to select QoS settings (e.g., a value of one or more of a minimum IOPS parameter, a maximum IOPS parameter, and a burst IOPS parameter). The training may involve placing the DRL agent into every feasible state representing combinations of QoS settings, workload conditions, and system metrics for a period of time for multiple iterations, and rewarding the DRL agent for selecting QoS settings that minimize an objective function based on a selected measure of system load. The trained DRL agent may then be deployed to one or more DSSs to constantly update QoS settings so as to minimize the selected measure of system load.
Methods and systems for a networked storage system is provided. One method includes transforming by a processor, performance parameters associated with storage volumes of a storage system for representing each storage volume as a data point in a parametric space; generating by the processor, a plurality of bins in the parametric space using the transformed performance parameters; adjusting by the processor, bin boundaries for the plurality of bins for defining a plurality of service levels for the storage system based on the performance parameters; and using the defined plurality of service levels for operating the storage system.
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
H04L 41/12 - Discovery or management of network topologies
Methods and systems for applications and/or virtual machines (“VM”) are provided. As an example, one method includes registering a storage system configured to store data for a VM; creating a policy for the VM for generating a VM backup by a storage management system interfacing with the storage system and a cloud-based microservice; storing, by the cloud-based micro-service, a copy of the VM backup at a cloud-based storage; receiving, by the cloud-based micro-service, an indication from the storage management system of a successful execution of a pre-restore operation upon unregistering the VM from a VM management system; and copying, by the cloud-based micro-service, VM data from the VM backup stored at the cloud-based storage to the storage system for executing a restore operation to restore the VM backup at the storage system.
Backup of application data associated with an application executing in a virtual machine managed by a hypervisor is performed. Backup of the application data includes retrieving a Logical Unit Number (LUN) identification (ID) used by the application to store the application data in a storage volume. Backup of the application data also includes performing a virtual storage resolution for the LUN ID to determine whether the application data is stored in the storage volume identified by the LUN ID based on a first virtual mapping or a physical mapping. Backup also includes storing in metadata for the backup the LUN ID and whether the LUN ID is based on the first virtual mapping or the physical mapping. Backup includes creating a backup of the application data stored in the storage volume. Application data can subsequently be restored based on the application data that is backed up.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 9/455 - Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
Techniques are provided for microservices management and orchestration. A chart package is selectively retrieved from a chart repository based upon the chart package corresponding to a set of services to host within a cluster and dependencies amongst the set of services. A set of container images may be retrieved from a container repository based upon the set of container images corresponding to the set of services. A cluster may be created within a computing environment. The set of services may be deployed as resources of the computing environment within the cluster and the dependencies may be configured using the chart package and the set of container images.
G06F 8/71 - Version control ; Configuration management
G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
One or more techniques and/or computing devices are provided for resilient replication of storage operations. For example, a first storage controller may host first storage having a replication relationship with second storage hosted by a second storage controller. To improve resiliency against transient network issues of a network between the storage controllers, the first storage controller may implement a queue and retry mechanism to retry replication operations not acknowledge back by the second storage controller within a threshold time. The second storage controller may maintain a cumulative sequence number of a latest replication operation performed in order, an operation response map of replication operations performed out of order, and an operation finder map identifying currently implemented replication operations, which may be used to process incoming replication operations. Single write semantics, write order consistency, and reduction of write amplification may be provided.
Techniques are provided for tiering snapshots to archival storage in remote object stores. A restore time metric, indicating that objects comprising snapshot data of snapshots created within a threshold timespan are to be available within a storage tier of a remote object store for performing restore operations, may be identified. A scanner may be executed to evaluate snapshots using the restore time metric to identify a set of candidate snapshots for archival from the storage tier to an archival storage tier of the remote object store. For each candidate snapshot within the set of candidate snapshots, the scanner may evaluate metadata associated with the candidate snapshot to identity one or more objects eligible for archival from the storage tier to the archival storage tier, and may archive the one or more objects from the storage tier to the archival storage tier.
G06F 16/11 - File system administration, e.g. details of archiving or snapshots
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
66.
TECHNIQUES FOR LIF PLACEMENT IN SAN STORAGE CLUSTER SYNCHRONOUS DISASTER RECOVERY
Improved techniques for disaster recover within storage area networks are disclosed. Embodiments include replicating a LIF of a primary cluster on a secondary cluster. LIF configuration information is extracted from the primary cluster. A peer node from a secondary cluster is located. One or more ports are located on the located peer node that match a connectivity of the LIF from the primary cluster. One or more ports are identified based upon one or more filtering criteria to generate a candidate port list. A port from the candidate port list is selected based at least upon a load of the port. Other embodiments are described and claimed.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 11/16 - Error detection or correction of the data by redundancy in hardware
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
Techniques are provided for implementing a persistent memory storage tier to manage persistent memory of a node. The persistent memory is managed by the persistent memory storage tier at a higher level within a storage operating system storage stack than a level at which a storage file system of the node is managed. The persistent memory storage tier intercepts an operation targeting the storage file system. The persistent memory storage tier retargets the operation from targeting the storage file system to targeting the persistent memory. The operation is transmitted to the persistent memory.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 3/06 - Digital input from, or digital output to, record carriers
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
Techniques are provided for microservices management and orchestration. A chart package is selectively retrieved from a chart repository based upon the chart package corresponding to a set of services to host within a cluster and dependencies amongst the set of services. A set of container images may be retrieved from a container repository based upon the set of container images corresponding to the set of services. A cluster may be created within a computing environment. The set of services may be deployed as resources of the computing environment within the cluster and the dependencies may be configured using the chart package and the set of container images.
G06F 8/71 - Version control ; Configuration management
G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
Methods, non-transitory machine readable media, and computing devices that manage storage operations directed to dual-port solid state disks (SSDs) coupled to multiple hosts are disclosed. With this technology, context metadata comprising a checksum is retrieved based on a first physical address mapped, in a cached zoned namespace (ZNS) mapping table, to a logical address. The logical address is extracted from a request to read a portion of a file. A determination is made when the checksum is valid based on a comparison to identification information extracted from the request and associated with the file portion. At least the first physical address is replaced in the cached ZNS mapping table with a second physical address retrieved from an on-disk ZNS mapping table, when the determination indicates the checksum is invalid. The file portion retrieved from a dual-port SSD using the second physical address is returned to service the request.
Systems and methods for creating an instance of a 3D model of an IT component within an AR world coordinate space are provided. According to one embodiment, a layout of a system of IT components may be specified in terms of respective rack unit locations within a rack. Based on a relative position with respect to an anchor component and the location of the anchor component within the coordinate space, a high-accuracy calibrated model of an IT component with reference to which AR entities have been defined for various back panel elements may be used to create an instance of a 3D model of the IT component within the coordinate space. The instantiated 3D model may then be used to precisely overlay the AR entities on corresponding back panel elements within a through-the-lens view of the IT component, for example, to facilitate a guided wire-up of the system.
Methods and systems for a networked storage system are provided. One method includes predicting an IOPS limit for a plurality of storage pools based on a maximum allowed latency of each storage pool, the maximum allowed latency determined from a relationship between the retrieved latency and a total number of IOPS from a resource data structure; identifying a storage pool whose utilization has reached a threshold value, the utilization based on a total number of IOPS directed towards the storage pool and a predicted IOPS limit; detecting a bully workload based on a numerical value determined from a total number of IOPS issued by the bully workload for the storage pool and a rising step function; and implementing a corrective action to reduce an impact of the bully workload on a victim workload.
One or more techniques and/or systems are provided for dynamically provisioning logical storage pools of storage devices for applications. For example, a logical storage pool, of one or more storage devices, may be constructed based upon a service level agreement for an application (e.g., an acceptable latency, an expected throughput, etc.). Real-time performance statistics of the logical storage pool may be collected and evaluated against the service level agreement to determine whether a storage device does not satisfy the service level agreement. For example, a latency of a storage device within the logical storage pool may increase overtime as log files and/or other data of the application increase. Accordingly, a new logical storage pool may be automatically and dynamically defined and provisioned for the application to replace the logical storage pool. The new logical storage pool may comprise storage devices expected to satisfy the storage level agreement.
Systems and methods for managing data storage using a distributed file system are provided. In one example, a file system instance is deployed virtually in a node of a distributed storage system. The file system instance has a dynamic configuration including a set of services corresponding to a cluster management subsystem and a storage management subsystem. The storage management subsystem operates independently of a data management subsystem of the distributed storage system as a result of disaggregation from the data management subsystem. The data management subsystem performs storage and block management functions based on requests received from an application layer. An additional service corresponding to either the data management subsystem or the storage management subsystem is deployed virtually to meet the demand for the additional service in response to determining the presence of a demand for the additional service and availability a set of resources corresponding to the additional service.
Techniques are provided for caching data during an on-demand restore using a cloud block map. A client may be provided with access to an on-demand volume during a restore process that copies backup data from a snapshot within a remote object store to the on-demand volume stored within local storage. In response to receiving a request from the client for a block of the backup data not yet restored from the snapshot to the on-demand volume, the block may be retrieved from the snapshot in the remote object store. The block may be cached within a cloud block map stored within the local storage as a cached block. The client may be provided with access to the cached block.
G06F 3/06 - Digital input from, or digital output to, record carriers
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
75.
FACILITATING IMMEDIATE PERFORMANCE OF VOLUME RESYNCHRONIZATION WITH THE USE OF PASSIVE CACHE ENTRIES
Systems and methods for reducing delays between the time at which a need for a resynchronization of data replication between a volume of a local CG and its peer volume of a remote CG is detected and the time at which the resynchronization is triggered (Reseed Time Period) are provided. According to an example, information indicative of the direction of data replication between the volume and the peer volume is maintained within a cache of a node. Responsive to a disruptive operation (e.g., relocation of the volume from a first node to a second node), the Reseed Time Period is lessened by proactively adding a passive cache entry to a cache within the second node at the time the CG relationship is created when the second node represents an HA partner of the first node and prior to the volume coming online when the second node represents a non-HA partner.
Techniques are provided for restoring a directory from a snapshot of a volume backed up to an object store. The snapshot may be backed up from a node to the object store, such as a cloud computing environment. A user may want to restore the directory within the volume without having to restore the entire volume, which otherwise would waste computing resources, storage, network bandwidth, and time. Accordingly, the techniques provided herein are capable of restoring just the directory from the snapshot that is stored within the object store. Because snapshot data of the snapshot may be stored across multiple objects within the object store, certain objects are identified as comprising snapshot data (backup data) of the directory and content items within the directory. In this way, the snapshot data of the directory is restored from these objects to a restore directory at a restore target.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 16/11 - File system administration, e.g. details of archiving or snapshots
77.
DATA CONNECTOR COMPONENT FOR IMPLEMENTING DATA REQUESTS
Techniques are provided for implementing data requests associated with objects of an object store. A data connector component may be instantiated as a container for processing data requests associated with backup data stored within objects of an object store. The data connector component may evaluate the object store to identify snapshots stored as the backup data within the objects of the object store according to an object format. The data connector component may provide a client device with access to backup data of the snapshots.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 16/11 - File system administration, e.g. details of archiving or snapshots
78.
Network Storage Failover Systems and Associated Methods
Failover methods and systems for a networked storage environment are provided. In one aspect, a read request associated with a first storage object is received, during a replay of entries of a log stored in a non-volatile memory of a second storage node for a failover operation initiated in response to a failure at a first storage node. The second storage node operates as a partner node of the first storage node. The read request is processed using a filtering data structure that is generated from the log prior to the replay and identifies each log entry. The read request is processed when the log does not have an entry associated with the read request, and when the filtering data structure includes an entry associated with the read request, the requested data is located at the non-volatile memory.
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
Techniques are provided for coordinating snapshot operations across multiple file systems. A notification may be received that a snapshot of data stored across a persistent memory file system and a storage file system is to be generated. Forwarding, of modify operations from a persistent memory tier to a file system tier for execution through the storage file system, may be enabled. Framing may be initiated to notify the storage file system of blocks within the persistent memory file system that comprise more up-to-date data than corresponding blocks within the storage file system. In response to the framing completing, a consistency point operation is performed to create the snapshot and to create a snapshot image as part of the snapshot.
Systems and methods for making a cross-site storage solution resilient towards mediator unavailability are provided. According to one embodiment, a stretched storage system is operable to bring a mediator associated with a primary and secondary distributed storage system back into the role of an arbitrator for peered consistency groups (CGs). A mediator reseed status indicator is maintained for multiple CGs to identify when the mediator's status information for a CG is stale. When the mediator becomes available and a local CG is identified as the subject of a mediator reseed process, the master node of the primary that hosts a master copy of a dataset for the local CG performs the reseed process, including: (i) causing relationship status information for the local CG to be updated on the mediator to the current state maintained by the primary; and (ii) resetting the mediator reseed status indicator.
G06F 3/00 - Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
G06F 3/06 - Digital input from, or digital output to, record carriers
81.
USING EPHEMERAL STORAGE AS BACKING STORAGE FOR JOURNALING BY A VIRTUAL STORAGE SYSTEM
Systems and methods for making use of non-persistent storage as the journaling storage media for a virtual storage system are provided. According to one embodiment, in order to meet the needs of Extreme Low Latency Workloads while also seeking to provide predictable performance and the lowest possible latency, ephemeral storage of the virtual storage system is used to preserve state information (e.g., in the form of boot arguments and an operation log journal) across a host failure recovery scenario in which the virtual storage system is expected to be redeployed within a compute instance brought up by a cloud environment of a hyperscaler on the same host, thereby providing improved data durability (fewer host failure scenarios that result in lost data) as compared to the use of ephemeral memory of the compute instance and lower write latency than the use of persistent storage provided by the cloud environment.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
Systems and methods for automated tuning of Quality of Service (QoS) settings of volumes in a distributed storage system are provided. According to one embodiment, one or more characteristics of a workload of a client to which a storage node of multiple storage nodes of the distributed storage system is exposed are monitored. After a determination has been made that a characteristic meets or exceeds a threshold, (i) information regarding multiple QoS settings assigned to a volume of the storage node utilized by the client is obtained, (ii) a new value of a burst IOPS setting of the multiple QoS settings is calculated by increasing a current value of the burst IOPS setting by a factor dependent upon a first and a second QoS setting of the multiple QoS settings, and (iii) the new value of the burst IOPS setting is assigned to the volume for the client.
Systems and methods for managing data storage using a distributed file system are provided. In one example, a relocation event is detected that indicates a relocation is to be initialized. The relocation is initialized by identifying a destination node of a distributed storage system for the relocation of a set of objects in a cluster database, including a logical block device, a corresponding logical aggregate, and a corresponding file system volume. A state of each of the set of objects is changed to offline. The set of objects are then relocated from an originating node of the distributed storage system to the destination node in which the corresponding logical aggregate is relocated after the logical block device and the corresponding file system volume is relocated after the logical aggregate. Finally, the state of each of the set of objects is changed to online.
In various examples, data storage is managed using a distributed storage management system that is resilient. Data blocks of a logical block device may be distributed across multiple nodes in a cluster. The logical block device may correspond to a file system volume associated with a file system instance deployed on a selected node within a distributed block layer of a distributed file system. Each data block may have a location in the cluster identified by a block identifier associated with each data block. Each data block may be replicated on at least one other node in the cluster. A metadata object corresponding to a logical block device that maps to the file system volume may be replicated on at least another node in the cluster. Each data block and the metadata object may be hosted on virtualized storage that is protected using redundant array independent disks (RAID).
Techniques are provided for on-demand serverless disaster recovery. A primary node may host a primary volume. Snapshots of the primary volume may be backed up to an object store. In response to failure, a secondary node and/or an on-demand volume may be created on-demand. The secondary node may provide clients with failover access to the on-demand volume while a restore process restores a snapshot of the primary volume to the on-demand volume. In some embodiments, there was no secondary node and/or on-demand volume while the primary node was operational. This conserves computing resources that would be wasted by otherwise hosting the secondary node and/or on-demand volume while clients were able to access the primary volume through the primary node. Modifications directed to the on-demand volume are incrementally backed up to the object store for subsequently restoring the primary volume after recovery.
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
86.
OBJECT STORE DATA MANAGEMENT CONTAINER WITH INTEGRATED SNAPSHOT DIFFERENCE INTERFACE FOR COMPLIANCE SCANS
Techniques are provided for a snapshot difference interface integrated into an object store data management container. The snapshot difference interface is capable of interpreting an object format and snapshot file system format of snapshots backed up to an object store within objects formatted according to the object format. The snapshot difference interface can identify differences between snapshots, such as files that changed between the snapshots, while the snapshots are still resident within the object store. Because the snapshot difference interface does not retrieve the snapshots from the object store, security is improved, resource and network consumption is reduced, and there is less of an impact upon client I/O processing. Also, a compliance scan for the snapshots can be performed much quicker by skipping already scanned snapshot data from a prior compliance scan.
G06F 16/11 - File system administration, e.g. details of archiving or snapshots
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
87.
Methods and Systems for Managing Race Conditions During Usage of a Remote Storage Location Cache in a Networked Storage System
Methods and systems for a networked storage system are provided. One method includes: generating, by a first node, a dummy entry in a storage location cache of the first node, the dummy entry associated with a read request received by the first node for data stored using a logical object owned by a second node; receiving, by the first node, an invalidation request to invalidate any storage location entry associated with the data, the invalidation request sent in response to the second node receiving a write request to modify the data; invalidating, by the first node, the dummy entry; receiving, by the first node, a response to the read request from the second node with the requested data; and replacing, by the first node, the dummy entry with a storage location entry and invalidating the storage location entry based on the invalidated dummy entry.
G06F 12/0891 - Addressing of a memory level in which the access to the desired data or data block requires associative addressing means, e.g. caches using clearing, invalidating or resetting means
Systems, methods, and data structures for providing a file system with object versioning support are provided. Rather than adding object records for each version of an object to a chapter record, in one example, the chapter record may be limited to a single object record for the object including: (i) an object name of the object; (ii) an object file handle identifying an index of a file containing data of a current version of the multiple versions of the object; and (iii) a version table file handle identifying an index of a file containing a version table. In this manner, enumeration of objects associated with a given chapter may be performed more efficiently and prior versions of objects may be maintained within the version table without disproportionate growth of chapter records and without increasing the search depth with objects that are not referenced by the search at issue.
Techniques are provided for a snapshot difference interface integrated into an object store data management container. The snapshot difference interface is capable of interpreting an object format and snapshot file system format of snapshots backed up to an object store within objects formatted according to the object format. The snapshot difference interface can identify differences between snapshots, such as files that changed between the snapshots, while the snapshots are still resident within the object store. Because the snapshot difference interface does not retrieve the snapshots from the object store, security is improved, resource and network consumption is reduced, there is less of an impact upon client I/O processing, and a catalog of the snapshots can be more efficiently built and recovered in the event of corruption.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
A method, system and computer program product, the method comprising: determining properties of a set of containers that are deployed over a computer infrastructure, wherein the computer infrastructure is provisioned via an infrastructure management service; determining properties of one or more headroom containers, wherein the one or more headroom containers are not deployed over the computer infrastructure; simulating the container orchestrator using the properties of the set of container and the properties of the headroom containers, for obtaining an expected deployment of the set of containers together with the one or more headroom containers; based on the expected deployment, determining whether the computer infrastructure is sufficient for deploying the set of containers together with the one or more headroom containers; and subject to the computer infrastructure being insufficient, issuing a request to the infrastructure management service to allocate additional computer infrastructure.
A client identifies a first data unit to be shared from a first file to a second file and sends an operation to copy that indicates the first data unit to be shared. The operation to copy the first data unit from the first file to the second file is received. In response to receiving the operation to copy the first data unit from the first file to the second file, it is determined whether the first data unit can be shared with the second file. In response to determining that the first data unit cannot be shared with the second file, the first data unit is copied to the second file. In response to determining that the first data unit can be shared with the second file, the first data unit is shared between the first file and the second file.
G06F 16/174 - Redundancy elimination performed by the file system
H04L 67/06 - Protocols specially adapted for file transfer, e.g. file transfer protocol [FTP]
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
92.
MULTI-ADMIN VERIFICATION FOR IMPROVED SECURITY OF DATA STORES
Systems/techniques that facilitate multi-admin verification (MAV) for improved security of data stores are provided. In various embodiments, a system can access a request to perform an operation on an object stored in a data store. In various aspects, the system can identify an MAV rule that specifies: approver credentials authorized to approve the request; a threshold number of approvals needed to place the request into an approved state; a request expiration timespan denoting for how long the request can be approved; executor credentials authorized to execute the request once/when in the approved state; an approved state expiration timespan denoting for how long the request can be executed once/when in the approved state; and/or a maximum number of times the request can be executed once/when in the approved state. In various instances, the system can approve/execute the request according to the MAV rule, thereby safeguarding/protecting the object from the operation.
Systems/techniques that facilitate multi-admin verification (MAV) for improved security of data stores are provided. In various embodiments, auto-execution of electronic requests may be facilitated. For example, an electronic approval of an electronic request may be received from an approver credential. A determination can be made that the electronic approval is a final electronic approval that causes a threshold number of valid electronic approvals for placing the electronic request in an approved state to be met. The electronic request is marked as being in the approved state in response to determining that the electronic approval is the final electronic approval. The electronic request is executed automatically after the electronic request has entered the approved state when the electronic request has been designated for auto-execution.
One or more systems, devices, computer program products, and/or computer-implemented methods of use provided herein to a readahead process related to an object at an object storage system. A system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components can comprise a detection component that, based on data from a load balancer of an object storage system, determines a trigger to perform a readahead of an object at the object storage system prior to receipt of a request related to the object, and a readahead component that, based on the trigger, executes the readahead of the object. The detection component can determine a pattern of use of the object storage system. The detection component can comprise or access a machine learning model to perform the determination.
One or more systems, devices, computer program products, and/or methods provided herein to a process to direct a request related to an object at an object storage system. A system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components can comprise a listing component that writes a node storage location of an object of the object storage system to a listing, and a load balancing component that, based on the listing, directs a request regarding the object to a node having the object stored thereat. An analysis component can determine a pattern of access to the object storage system based on data defining access behavior to the object storage system. The analysis component can determine whether to instruct or recommend writing of the node storage location of the object to the listing.
Techniques are provided for determining a physical size of a snapshot backed up to an object store. Snapshot data of the snapshot may be backed up into objects that are stored from a node to the object store, such as a cloud computing environment. A tracking object is created to identify which objects within the object store comprise the snapshot data of the snapshot. In order to determine the physical size of the snapshot, the tracking object and/or tracking objects of other snapshots such as a prior snapshot are evaluated to identify a set of objects comprising snapshot data unique to the snapshot and not shared with the prior snapshot. The physical sizes of the set of objects are combined with a metadata size of metadata of the snapshot to determine the physical size of the snapshot.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
Techniques are provided for implementing a defragmentation process during a merge operation performed by a re-compaction process upon a log structured merge tree. The log structured merge tree is used to store keys of key-value pairs within a key-value store. As the log structured merge tree fills with keys over time, the re-compaction process is performed to merge keys down to lower levels of the log structured merge tree to re-compact the keys. Re-compaction can result in fragmentation because there is a lack of spatial locality of where the re-compaction operations re-writes the keys within storage. Fragmentation increases read and write amplification when accessing the keys stored in different locations within the storage. Accordingly, the defragmentation process is performed during a last merge operation of the re-compaction process in order to store keys together within the storage, thus reducing read and write amplification when accessing the keys.
Techniques are provided for implementing a garbage collection process and a prediction read ahead mechanism to prefetch keys into memory to improve the efficiency and speed of the garbage collection process. A log structured merge tree is used to store keys of key-value pairs within a key-value store. If a key is no longer referenced by any worker nodes of a distributed storage architecture, then the key can be freed to store other data. Accordingly, garbage collection is performed to identify and free unused keys. The speed and efficiency of garbage collection is improved by dynamically adjusting the amount and rate at which keys are prefetched from disk and cached into faster memory for processing by the garbage collection process.
Techniques are provided for volume group backup, volume group restore, and volume group garbage collection for volume groups backed up to an object store. A volume group workflow is implemented to orchestrate individual consistent volume workflows that are separately and individually implemented by nodes hosting constituent volumes of a volume group. The volume group workflow and the individual consistent volume workflows are performed to back up the volume group to the object store, restore a volume group backup from the object store to a restore destination, and/or perform garbage collection on slots of objects storing data unique to a volume group backup to delete.
Techniques are provided for volume group backup, volume group restore, and volume group garbage collection for volume groups backed up to an object store. A volume group workflow is implemented to orchestrate individual consistent volume workflows that are separately and individually implemented by nodes hosting constituent volumes of a volume group. The volume group workflow and the individual consistent volume workflows are performed to back up the volume group to the object store, restore a volume group backup from the object store to a restore destination, and/or perform garbage collection on slots of objects storing data unique to a volume group backup to delete.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
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