Netapp, Inc.

Austino Nicholas Longo

Daniel David McCarthy

Tyler W Cady

Christopher Clark Corey

Sneheet Kumar Mishra

Jared Cantwell

Christopher Cason

Randolph Wesley Sterns

James Philip Wittig

Disclosed are systems, computer-readable mediums, and methods for managing client performance in a storage system. According to one embodiment, a total Input/Output Operations per Second (IOPS) pool and a read/write IOPS pool are managed for clients to ensure their write requests can be accommodated by both pools. In one example, a write request is received from a client by the storage system. A requested number of write IOPS is determined for a time period to accommodate the request. Based on the requested number of write IOPS exceeding a number of allocated write IOPS to the client for the time period, a target total IOPS for the client during the time period is determined by subtracting the number of allocated write IOPS from a number of allocated total IOPS to the client. At least a portion of the request is performed by executing the target total IOPS during the time period.

Quality of service policy sets

A system is described. The system includes a processing resource and a non-transitory computer-readable medium, coupled to the processing resource, having stored therein instructions that when executed by the processing resource cause the processing resource to receive a plurality of quality of service (QoS) parameters and client preferences from a client device and manage a QoS policy based on a plurality of QoS objectives included in the received QoS parameters, wherein the plurality of QoS objectives comprise input output operations per second (IOPS), throughput and latency.

Quality of service management mechanism

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.

Automated tuning of a quality of service setting for a distributed storage system based on internal monitoring

A technique is configured to provide various data protection schemes, such as replication and erasure coding, for data blocks of volumes served by storage nodes of a cluster configured to perform deduplication of the data blocks. Additionally, the technique is configured to ensure that each deduplicated data block complies with data redundancy guarantees of the data protection schemes, while improving storage space of the storage nodes. In order to satisfy the data integrity guarantees while improving available storage space, the storage nodes perform periodic garbage collection for data blocks to optimize storage in accordance with currently applicable data protection schemes.

Storage space optimization in a system with varying data redundancy schemes

Systems and methods for quality of service management are provided. According to one embodiment, a non-transitory computer-readable medium comprises instructions that when executed by the processing resource cause the processing resource to collect, from a plurality of volumes on a per-volume basis, one or more real-time performance metrics for one or more compute processes executing on the one or more computer systems, generate an inertial parameter for one or more volumes in the plurality of volumes, and generate an instruction that cause a processor to use the real-time performance metrics and the inertial parameter to determine whether to transfer responsibility for a compute process on a first storage server node to a second storage server node.

Dynamic load balancing by analyzing performance of volume to quality of service

Disclosed are systems, computer-readable mediums, and methods for managing client performance in a storage system. In one example, the storage system receives a request from a client to write data to the storage system. The storage system estimates, based on a system metric associated with the storage system reflecting usage of the storage system, a requested write QoS parameter for storing the data by the storage system during a first time period. The storage system further determines a target write QoS parameter for the client based on the estimated requested write QoS parameter and an allocated write QoS parameter for the client. Then, the storage system independently regulates read performance and write performance of the client using a controller to adjust the write performance toward the determined target write QoS parameter within the first time period based on feedback regarding the estimated requested write QoS parameter.

Systems and methods are described for smoothing-out latency of IO operations processed by a distributed storage system. In some examples, latency is distributed among IO operations to more evenly spread processing of the IO operations over an IO processing interval. A target latency for IO operations for a volume of a distributed storage system is periodically calculated each sample period based on the number of IO operations to be processed during the next IO processing interval for the volume. As IO operations are received for the volume, a latency may be associated with the IO operation based on the target latency and the IO operation may be queued or synchronously processed as appropriate. Responsive to expiration of a time period that is based on at time at which a given IO operation at the head of the queue was received and the assigned latency, the given IO operation is dequeued and processed.

Processing of input/ouput operations by a distributed storage system based on latencies assigned thereto at the time of receipt

A system, method, and machine-readable storage medium for providing a recommendation to a client to modify minimum IOPS settings are provided. In some embodiments, a client may assign a minimum input/output operations per second (IOPS) setting to each volume of a plurality of volumes. The plurality of volumes may reside in a common cluster and include a first number of volumes. A set of volumes of the plurality of volumes may be determined, where each volume of the set of volumes has a relative disparity that satisfies a relative threshold. The set of volumes includes a second number of volumes. A minimum IOPS recommendation may be transmitted to the client to modify (e.g., increase or decrease) the minimum IOPS settings of the set of volumes in response to determining that a ratio of the second number of volumes to the first number of volumes is greater than a performance threshold.

Disparity of quality of service (QoS) settings of volumes across a cluster

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, responsive to a predetermined event, information regarding a multiple QoS settings assigned to a volume of a distributed storage system that is being utilized by a client are obtained. A difference between a first QoS setting of the multiple QoS settings and a second QoS setting of the multiple QoS settings is determined. Responsive to determining the difference is less than a threshold a new value of the first QoS setting or a third QoS setting of the multiple QoS settings that is greater than a respective current value of the first QoS setting or the third QoS setting is determined and assigned to the volume for the client.

A technique provides efficient data protection, such as erasure coding, for data blocks of volumes served by storage nodes of a cluster. Data blocks associated with write requests of unpredictable client workload patterns may be compressed. A set of the compressed data blocks may be selected to form a write group and an erasure code may be applied to the group to algorithmically generate one or more encoded blocks in addition to the data blocks. Due to the unpredictability of the data workload patterns, the compressed data blocks may have varying sizes. A pool of the various-sized compressed data blocks may be established and maintained from which the data blocks of the write group are selected. Establishment and maintenance of the pool enables selection of compressed data blocks that are substantially close to the same size and, thus, that require minimal padding.

Pooling blocks for erasure coding write groups

Systems and methods for quality of service management are provided. According to one embodiment, a non-transitory computer-readable medium comprises instructions that when executed by the processing resource cause the processing resource to receive, in a normalizing agent, one or more compute load parameters from one or more background compute processes executing on the one or more computer systems and one or more Quality of Service (QoS) parameters for one or more client compute processes executing on the one or more computer systems, convert the one or more compute load parameters to one or more normalized utilization metrics, and execute instructions that cause a processor to adjust a compute resource allocation dedicated to the one or more background compute processes based at least in part on the one or more normalized utilization metrics and the one or more QoS parameters.

Centralized quality of service management

A bin syncing technique ensures continuous data protection, such as replication and erasure coding, for content driven distribution of data served by storage nodes of a cluster in the event of failure to one or more block services configured to process the data. The cluster maintains information about the block services assigned to host a bin with a copy of the data in a bin assignment table associated with a state. The copies of the data are named, e.g., replica 0 (R0), replica 1 (R1) or replica 2 (R2). In response to failure of one or more block services assigned to host a bin with a replica of the data, an alternate or replacement block service may access the assignments maintained in the bin assignment table, which specify names of the replicas associated with the state.

Bin syncing technique for multiple data protection schemes

Available storage space in a system with varying data redundancy schemes

Disclosed are systems, computer-readable mediums, and methods for managing input/output operations within a system including at least one client and a storage system. A processor receives information regarding allocated input-output operations (IOPS) associated with a client accessing a storage system storing client data. The information includes a number of allocated total IOPS, a number of allocated read IOPS, and a number of allocated write IOPS. The processor also receives a requested number of write IOPS associated with the at least one client's request to write to the storage system. The processor determines a target write IOPS based on the number of allocated total IOPS, the number of allocated write IOPS and the requested number of write IOPS, and executes the determined target write IOPS within the first time period.

Growing community of inventors

Lafayette, CO, United States of America

Austino Nicholas Longo