Abstract: Methods and apparatuses for online replacement of a node enclosure are provided. A storage array system includes a node-pair housed in a node enclosure. Each node of the node-pair are be linked to a network and further linked to each other by external interconnects, independent of the enclosure. The interconnects couple the first storage node to the second storage node externally of the node enclosure. The node-pairs are configured to communicate independently of the node enclosure and the enclosure is replaceable without disruption of communication over the network.

Abstract: A pattern-based cache eviction policy leverages I/O access patterns to optimize cache retention for data with predictable read-after-write behavior. The system generates and relies on pattern recognition and predictive analytics to identify the probability and timing of read operations following write operations on the same data blocks. The system enables retention of specific data in cache longer when a read operation is anticipated and evicts specific data when a read operation is not anticipated. A collection of I/O operations is received and analyzed for one or more access patterns. A predictive model is generated based on the one or more access patterns and is configured to forecast a future I/O operation. An I/O operation is input to the predictive model to determine an eviction event.

Abstract: A method for adjusting data processing unit (DPU) utilization of a secondary storage array, the method includes sampling, input-output of a primary storage array and a secondary storage array, forecasting, based on the sampling, demand for the primary storage array and the secondary storage array, where the primary storage array includes a primary DPU core matrix and the secondary storage array includes a secondary DPU core matrix, and combining the forecasting of the primary storage array and secondary storage array. The method further includes making a second determination, based on the combined forecast, that at least one service level (SL) of multiple SLs associated with the secondary DPU core matrix is out of compliance, identifying at least one DPU currently operating at a first SL, and adjusting operation of the at least one DPU to operate from the first SL to a second SL of the multiple SLs.

Abstract: Embodiments disclosed herein relate to selective inline compression of data using data processing units (DPUs) of hosts running on the file system prior to storing the data on a remote storage system. To be compressed by the DPUs of the hosts, data should be not already compressed, the data should not subject to frequent read/write cycles off the remote storage system, and the DPU should have sufficient computing resources to compress the data. A file system is connected to the hosts and the remote storage. The file system provides a file heatmap that forecasts whether the data is frequently accessed. The file heatmap is created using machine learning models. After receiving the file heatmap, the host writes the data to the remote storage system and uses the file heatmap to determine if the data should be compressed.

Abstract: Disclosed are systems and methods for enhancing local node performance in a storage system through offloading cache replacement tasks to remote nodes. A periodic time-series analysis of CPU cycle utilization and network latency is conducted on one or more arrays to identify and/or forecast underutilized nodes in the one or more arrays. A first array detects a shortage of available cache slots in an allocation queue and identifies underutilized remote nodes in either its own array or another array. The array shares the metadata pages with the remote node. A worker thread on the remote node runs a search algorithm on the received meta data pages and creates a list of candidate replacement memory slots.

Abstract: A method, comprising: executing an embedded malware detector, the embedded malware detector being executed inside a first guest operating system, the first guest operating system being executed on a storage processor that is part of a storage system, the storage processor being configured to execute one or more second guest operating systems in addition to the first guest operating system, each of the second guest operating systems being arranged to execute software for reading and/or writing data to one or more storage devices that are provided in the storage system; identifying, by the embedded malware detector, a given one of the storage devices; obtaining, by the embedded malware detector, a snapshot of the given one of the storage devices; mounting, by the embedded malware detector, the snapshot in the first guest operating system; scanning the mounted snapshot for malware.

Abstract: Disclosed are systems and methods for enhancing local node performance in a storage system through offloading cache replacement tasks to remote nodes. A periodic time-series analysis of CPU cycle utilization and network latency is conducted on one or more arrays to identify and/or forecast underutilized nodes in the one or more arrays. A first array detects a shortage of available cache slots in an allocation queue and identifies underutilized remote nodes in either its own array or another array. The array shares the metadata pages with the remote node. A worker thread on the remote node runs a search algorithm on the received meta data pages and creates a list of candidate replacement memory slots.

Abstract: A method for use in a storage processor, comprising: receiving an I/O request that is associated with a logical block address; allocating a cache slot that corresponds to the logical block address, wherein allocating the cache slot includes: identifying a type of memory that is required to host the cache slot by using one or more configuration settings that are associated with the cache slot, identifying a cache slot that is both available and hosted in the identified type of memory, and assigning the identified cache slot to the logical block address; and executing the I/O request by using the allocated cache slot, wherein using the allocated cache slot includes identifying a memory address that is associated with the cache slot and executing at least one direct memory access (DMA) command that is associated with the allocated cache slot.

Abstract: A method comprising: generating a write-on-write distribution for a plurality of data units in a data entity, the write-on-write distribution including a plurality of buckets, each bucket corresponding to a different write-on-write time range, each bucket having a respective bucket size that is based on a count of ones of the plurality of data units whose respective predicted write-on-write times fall within the bucket's write-on-write time range; identifying one or more utilization metrics of a storage system where the data entity is hosted; classifying a representative bucket size of the write-on-write distribution and the one or more utilization metrics with a machine learning model to predict a replication period for the data entity, the representative bucket size being a bucket size within a predetermined distance from a mean bucket size of the write-on-write distribution; and configuring the storage system to replicate the data entity in accordance with the replication period.

Abstract: An information handling system executing a predictive task adjusting and carbon dioxide (CO2) minimizing system may comprise a hardware processor executing code instructions of a time series forecasting engine to predict a future CO2 emissions value for hardware component within a data center within a future time window that exceeds a CO2 threshold value determined for the hardware component where changes in CO2 emissions are due to a forecasted future load of memory accessing functions causing a change in energy consumption, the hardware processor executing code instructions to identify an adjusted forecasted future load of memory accessing functions whose execution is predicted to decrease CO2 emitted during the future time window below the CO2 threshold value, and the network interface device to transmit a workload redistribution instruction for implementing the adjusted forecasted future load of memory accessing functions at the data center.

Abstract: Aspects of the present disclosure relate to optimizing atomic operations in storage arrays by selectively enabling fabric-less mode based on device access patterns. In embodiments, whether multi-path software is enabled is determined, and device-level access control mappings are analyzed to identify candidates for fabric-less mode operation. For devices without multi-path software, a fabric-less mode is enabled when mapped to a single board, allowing atomic operations via software locks instead of fabric hardware. When multi-path software is enabled, the embodiments either leverage ALUA states to identify optimized paths or employ time series analysis using ARIMA models to predict IO access patterns. Fabric-less mode is activated when forecasting indicates localized access patterns, significantly improving response time and IOPS by avoiding fabric bandwidth constraints and hardware vendor limitations.

Abstract: A system can obtain a first prompt as output from inputting an alert about a computer system to a first retrieval-augmented generation system (RAG). The system can obtain a first answer as output from inputting the first prompt to a first large language model (LLM). The system can obtain a value maintained by an entity associated with the computing system as output from inputting the alert to a second RAG. The system can obtain a second answer as output from inputting the first answer, the value, and a second prompt to a second LLM, wherein the second LLM comprises the first LLM or another LLM different from the first LLM. The system can obtain a third answer as output from inputting the second answer, user information associated with the entity, and a third prompt to a third LLM. The system can make the third answer available to the entity.

Abstract: One or more aspects of the present disclosure relate to paging metadata into memory. In embodiments, a metadata demand score is calculated for each extent of a storage array based on hit forecasts and read forecasts corresponding to input/output (IO) operations targeting each extent. Further, each extent can be ranked based on their respective metadata demand scores. Additionally, metadata can be paged into memory from a storage device of the storage array based on the ranking to reduce metadata page misses. For example, the memory can correspond to a global memory portion of the storage array.

Abstract: One or more aspects of the present disclosure relate to dynamically pre-allocating cache slots based on workload forecasting. In embodiments, characteristics corresponding to one or more input/output (IO) operations received by a storage array are determined. An IO workload for one or more cache segments of system memory of the storage array is also forecasted. In addition, a queue depth for each cache pool of the one or more cache segments is dynamically adjusted. Further, cache slots are dynamically pre-allocated to each cache pool based on the queue depth of each cache pool.

Abstract: Techniques for program code management are disclosed. For example, a method obtains resource utilization data from a computing network comprising a plurality of computing devices. The method then utilizes a multi-variate time series model representing at least a portion of the resource utilization data to automatically compute at least one time window in which to perform a program code update on at least a subset of the plurality of computing devices.

Abstract: A method for use in a storage system, comprising: detecting an event; and in response to the event, changing one or more replacement algorithms that are being used by the storage system, wherein changing the one or more replacement algorithms includes: (-)selecting a first segment in a cache of the storage system, the first segment being serviced with a first replacement algorithm; (-)generating a first signature representing a state of the storage system; (-)classifying the first signature with a selection engine to identify a second replacement algorithm, the second replacement algorithm being different from the first replacement algorithm; and (-)configurating the storage system to service the first segment with the second replacement algorithm.

Abstract: Aspects of the present disclosure relate to optimizing atomic operations in storage arrays by selectively enabling fabric-less mode based on device access patterns. In embodiments, whether multi-path software is enabled is determined, and device-level access control mappings are analyzed to identify candidates for fabric-less mode operation. For devices without multi-path software, a fabric-less mode is enabled when mapped to a single board, allowing atomic operations via software locks instead of fabric hardware. When multi-path software is enabled, the embodiments either leverage ALUA states to identify optimized paths or employ time series analysis using ARIMA models to predict IO access patterns. Fabric-less mode is activated when forecasting indicates localized access patterns, significantly improving response time and IOPS by avoiding fabric bandwidth constraints and hardware vendor limitations.

Abstract: One or more aspects of the present disclosure relate to dynamic battery-based cache size management. In embodiments, a charge level of a battery configured to provide power to a storage array is monitored. Further, a size of a mirrored write cache partition of system memory in the storage array is dynamically adjusted based on the charge level of the battery.

Abstract: An intelligent predictive battery replacement system to increase disaster recovery stability uses training samples created using battery report indexes and vault condition recovery reports to train a linear regression model learning process to learn a recursion between battery post recovery charge and a set of time series battery operational parameters. Once trained, the learning process is used in a predictive manner to predict the post recovery charge state of batteries deployed in storage controllers, to provide a predictive per-battery risk assessment. The per-battery risk assessment identify batteries that may be scheduled to be replaced to increase disaster recovery stability of the storage systems.

Abstract: A method, comprising: receiving write requests at a first storage system; destaging the write requests to a permanent storage of the first storage system and collecting one or more destage statistics that are associated with the write requests; generating a hint object corresponding to the write requests, the hint object being generated based at least in part on the destage statistics; transmitting the hint object to a second storage system; and transmitting at least some of the write requests to the second storage system for remote replication.