Abstract: Provided are a computer program product, system, and method for determining tracks to prestage into cache from a storage. Information is provided related to determining tracks to prestage from the storage to the cache in a stage group of sequential tracks including a trigger track comprising a track number in the stage group at which to start prestaging tracks and Input/Output (I/O) activity information to a machine learning module. A new trigger track in the stage group at which to start prestaging tracks is received from the machine learning module having processed the provided information. The trigger track is set to the new trigger track. Tracks are prestaged in response to processing an access request to the trigger track in the stage group.

Abstract: A host computational device transmits a first write command with a first token over a first interface to a storage controller. In response to receiving an indication by the host computational device that the first write command has failed in the storage controller, the host computational device transmits a second write command with a second token over a second interface to the storage controller, wherein the second write command is a retry of the first write command that failed, wherein the second token is identical to the first token, and wherein the second interface is a slower communication link than the first interface.

Abstract: Provided are a computer program product, system, and method for using alternate recovery actions for initial recovery actions in a computing system. An initial recovery table provides initial recovery actions to perform for errors detected in the computing system. An alternate recovery table is received including at least one alternate recovery action for at least one of the initial recovery actions. An alternative recovery action provided for an initial recovery action specifies a different recovery path involving at least one of a different action and a different component in the computing system than involved in the initial recovery action. A determination is made as to whether to use the initial recovery action in the initial recovery table for a detected error or the alternate recovery action in the alternate recovery table. The determined initial recovery action or alternate recovery action determined is used to address the detected error.

Abstract: Provided are a computer program product, system, and method for using trap cache segments to detect malicious processes. A trap cache segment to the cache for data in the storage and indicated as a trap cache segment. Cache segments are added to the cache having data from the storage that are not indicated as trap cache segments. A memory function call from a process executing in the computer system reads data from a region of a memory device to output the read data to a buffer of the memory device. A determination is made as to whether the region of the memory device includes the trap cache segment. The memory function call is blocked and the process is treated as a potentially malicious process in response to determining that the region includes the trap cache segment.

Abstract: Provided are a computer program product, system, and method for using a machine learning module to select one of multiple cache eviction algorithms to use to evict a track from the cache. A first cache eviction algorithm determines tracks to evict from the cache. A second cache eviction algorithm determines tracks to evict from the cache, wherein the first and second cache eviction algorithms use different eviction schemes. At least one machine learning module is executed to produce output indicating one of the first cache eviction algorithm and the second cache eviction algorithm to use to select a track to evict from the cache. A track is evicted that is selected by one of the first and second cache eviction algorithms indicated in the output from the at least one machine learning module.

Abstract: In response to an end of track access for a track in a cache, a determination is made as to whether the track has modified data and whether the track has one or more holes. In response to determining that the track has modified data and the track has one or more holes, an input on a plurality of attributes of a computing environment in which the track is processed is provided to a machine learning module to produce an output value. A determination is made as to whether the output value indicates whether one or more holes are to be filled in the track. In response to determining that the output value indicates that one or more holes are to be filled in the track, the track is staged to the cache from a storage drive.

Abstract: Provided are a computer program product, system, and method for recovering storage devices in a storage array having errors. A determination is made to replace a first storage device in a storage array with a second storage device. The storage array is rebuilt by including the second storage device in the storage array and removing the first storage device from the storage array resulting in a rebuilt storage array. The first storage device is recovered from errors that resulted in the determination to replace. Data is copied from the second storage device included in the rebuilt storage array to the first storage device. The recovered first storage device is swapped into the storage array to replace the second storage device in response to copying the data from the second storage device to the first storage device.

Abstract: In response to determining, by a storage controller, that a first process is to perform a write operation, a customer data track in a cache is configured for exclusive access while waiting for the write operation on the customer data track to be performed by the first process. In response to configuring the customer data track for the exclusive access, a copy of a metadata track is generated, wherein the metadata track stores metadata information of the customer data track and is configured for shared access. The copy of the metadata track is configured to provide exclusive access to a second process to perform operations on the copy of the metadata track, wherein the first process is able to perform the write operation on the customer data track that causes the metadata track to be updated while the second process performs the operations on the copy of the metadata track.

Abstract: Provided are a computer program product, system, and method for using a machine learning module to select one of multiple cache eviction algorithms to use to evict a track from the cache. A first cache eviction algorithm determines tracks to evict from the cache. A second cache eviction algorithm determines tracks to evict from the cache, wherein the first and second cache eviction algorithms use different eviction schemes. At least one machine learning module is executed to produce output indicating one of the first cache eviction algorithm and the second cache eviction algorithm to use to select a track to evict from the cache. A track is evicted that is selected by one of the first and second cache eviction algorithms indicated in the output from the at least one machine learning module.

Abstract: A method includes establishing, for a transaction processing system, a maximum number of transactions that the transaction processing system can optimally handle at a time, as well as an optimal transaction rate. The method monitors a current number of transactions being processed by the transaction processing system. Incoming transactions that would cause the current number to exceed the maximum number are received into a queue, and transactions are released from the queue in accordance with the optimal transaction rate. The method further monitors a number of transactions waiting in the queue. When the number reaches an upper threshold, the method declines to admit additional transactions into the queue. When the number reaches a lower threshold, the method begins to admit additional transactions into the queue. A corresponding system and computer program product are also disclosed.

Abstract: Copy source to target operations may be selectively and preemptively undertaken in advance of source destage operations. In another aspect, logic detects sequential writes including large block writes to point-in-time copy sources. In response, destage tasks on the associated point-in-time copy targets are started which include in one embodiment, stride-aligned copy source to target operations which copy unmodified data from the point-in-time copy sources to the point-in-time copy targets in alignment with the strides of the target. As a result, when write data of write operations is destaged to the point-in-time copy sources, such source destages do not need to wait for copy source to target operations since they have already been performed. In addition, the copy source to target operations may be stride-aligned with respect to the stride boundaries of the point-in-time copy targets. Other features and aspects may be realized, depending upon the particular application.

Abstract: A peer to peer remote copy operation is performed between a primary storage controller and a secondary storage controller, to establish a peer to peer remote copy relationship between a primary storage volume and a secondary storage volume. Subsequent to indicating completion of the peer to peer remote copy operation to a host, a determination is made as to whether the primary storage volume and the secondary storage volume have identical data, by performing operations of staging data of the primary storage volume from auxiliary storage of the primary storage controller to local storage of the primary storage controller, and transmitting the data of the primary storage volume that is staged, to the secondary storage controller for comparison with data of the secondary storage volume stored in an auxiliary storage of the secondary storage controller.

Abstract: Provided are a computer program product, system, and method for destaging metadata tracks from cache A counter for a metadata track is updated in response to modifying the metadata track in the cache, wherein there are counters for metadata tracks in the cache. The metadata track is destaged from the cache in response to the counter for the metadata track being less than a threshold value. The counter for the metadata track is decremented based on a number of modified metadata tracks in the cache.

Abstract: Provided are a computer program product, system, and method for determining tracks to prestage into cache from a storage. Information is provided related to determining tracks to prestage from the storage to the cache in a stage group of sequential tracks including a trigger track comprising a track number in the stage group at which to start prestaging tracks and Input/Output (I/O) activity information to a machine learning module. A new trigger track in the stage group at which to start prestaging tracks is received from the machine learning module having processed the provided information. The trigger track is set to the new trigger track. Tracks are prestaged in response to processing an access request to the trigger track in the stage group.

Abstract: A method for dynamically balancing I/O workload is disclosed. In one embodiment, such a method includes transmitting, from a host system to a storage system, read requests and write requests over a communication path, such as a zHyperLink communication path. The method further determines whether first and second sets of conditions (e.g., read cache hit ratio, read and write response times, read and write reject rates, etc.) are satisfied on one or more of the host system and storage system. In the event the first set of conditions is satisfied, the method increases a ratio of read requests to write requests that are transmitted over the communication path. In the event the second set of conditions is satisfied, the method decreases the ratio of read requests to write requests that are transmitted over the communication path. A corresponding system and computer program product are also disclosed.

Abstract: In one embodiment, storage drive dependent track removal processing logic performs destage tasks for tracks cached in a cache as a function of whether the storage drive is classified as a fast class or as slow class of storage drives, for example. In one embodiment, a destage task configured for a slow class storage drive, transfers an entry for a track selected for destaging from a main cache list to a wait cache list to await destaging to the slow class drive. A destage task configured for a fast class storage drive allows the cache list entry for the selected track to remain on the main cache list while the selected track is being destaged to the fast class storage drive, thereby bypassing the transfer of the entry to a wait cache list. Other features and aspects may be realized, depending upon the particular application.

Abstract: Dynamic compression with dynamic multi-stage encryption for a data storage system in accordance with the present description includes, in one aspect of the present description, preserves end-to-end encryption between a host and a storage controller while compressing data which was received from the host in encrypted but uncompressed form, using MIPs and other processing resources of the storage controller instead of the host. In one embodiment, the storage controller decrypts encrypted but uncompressed data received from the host to unencrypted data and compresses the unencrypted data to compressed data. The storage controller then encrypts the compressed data to encrypted, compressed data and stores the encrypted, compressed data in a storage device controlled by the storage controller. Other aspects and advantages may be realized, depending upon the particular application.

Abstract: In one embodiment, a safe data commit process manages the allocation of task control blocks (TCBs) as a function of the type of task control block (TCB) to be allocated for destaging and as a function of the identity of the RAID storage rank to which the data is being destaged. For example, the allocation of background TCBs is prioritized over the allocation of foreground TCBs for destage operations. In addition, the number of background TCBs allocated to any one RAID storage rank is limited. Once the limit of background TCBs for a particular RAID storage rank is reached, the distributed safe data commit logic switches to allocating foreground TCBs. Further, the number of foreground TCBs allocated to any one RAID storage rank is also limited. Other features and aspects may be realized, depending upon the particular application.

Abstract: Provided are a computer program product, system, and method for using at least one machine learning module to select a priority queue from which to process an Input/Output (I/O) request. Input I/O statistics are provided on processing of I/O requests at the queues to at least one machine learning module. Output is received from the at least one machine learning module for each of the queues. The output for each queue indicates a likelihood that selection of an I/O request from the queue will maintain desired response time ratios between the queues. The received output for each of the queues is used to select a queue of the queues. An I/O request from the selected queue is processed.

Abstract: Provided are a computer program product for managing bus interface errors in a storage system coupled to a host and storage. A determination is made as to whether a first number of correctable errors on a first bus interface, connecting a first processing unit to the storage, exceeds a second number of correctable errors on a second bus interface, connecting a second processing unit to the storage, by a difference threshold. The correctable errors in the first and second bus interfaces are detected and corrected in the first and second bus interfaces by first hardware and second hardware, respectively. In response to determining that the first number of correctable errors exceeds the second number of correctable errors by the difference threshold, at least a portion of Input/Output (I/O) requests are redirected to a second processing unit using the second bus interface to connect to the storage.