Netapp, Inc.

Keith Arnold Smith

David Slik

John K Edwards

Steven Robert Kleiman

Peter Shah

Jiri Schindler

John William Haskins, Jr

Maxim Gerard Smith

Garth Richard Goodson

James F Lentini

Atish Kathpal

Stephen Michael Byan

Giridhar Appaji Nag Yasa

Minglong Shao

David Anthony Slik

Peter Macko

Shehbaz Jaffer

Sethuraman Subbiah

William Karl Jannen

A durable file system has been designed for storage devices that do not support write in place and/or that are susceptible to errors or failures. The durable file system also facilitates organization and access of large objects (e.g., gigabytes to terabytes in size). Regardless of whether target storage devices are configured with sequential write constraints, the durable file system writes object fragments across a set of sequences or ranges of storage units, such as logical blocks. The durable file system sequentially writes an object fragment into each storage unit sequence along with indexing information for the object fragments. In addition to writing the indexing information for the object fragments into the set of storage unit sequences, the durable file system updates the file system index with the object indexing information.

Sequential write based durable file system

Techniques are provided for offloading the management of sensor data and generating custom views of sensor data. Sensor data received from a data network through a message is stored within storage managed by a computing device. A handle is generated to identify the sensor data. The sensor data within the message is replaced with the handle, and the message is transmitted to a device within the data network. The device may use handles of sensor data to request custom views of sensor data.

Custom views of sensor data

Storage offload engine for distributed network device data

A rebuild node of a storage system can assess risk of the storage system not being able to provide a data object. The rebuild node(s) uses information about data object fragments to determine health of a data object, which relates to the risk assessment. The rebuild node obtains object fragment information from nodes throughout the storage system. With the object fragment information, the rebuild node(s) can assess object risk based, at least in part, on the object fragments indicated as existing by the nodes. To assess object risk, the rebuild node(s) treats absent object fragments (i.e., those for which an indication was not received) as lost. When too many object fragments are lost, an object cannot be rebuilt. The erasure coding technique dictates the threshold number of fragments for rebuilding an object. The risk assessment per object influences rebuild of the objects.

Risk based rebuild of data objects in an erasure coded storage system

A storage system writes an object across zones of a set of zones ('zone set'). Each zone of a zone set is contributed from an independently accessible storage medium. To create a zone set, the storage system arbitrarily selects disks to contribute a zone for membership in the zone set. This results in a fairly even distribution of zone sets throughout the storage system, which increases fault tolerance of the storage system. Although disk selection for zone set membership is arbitrary, the arbitrary selection can be from a pool of disks that satisfy one or more criteria (e.g., health or activity based criteria). In addition, weights can be assigned to disks to influence the arbitrary selection. Although manipulating the arbitrary selection with weights or by reducing the pool of disks reduces the arbitrariness, this evenly distributes zone sets while accounting for client demand and/or disk health.

Storage zone set membership

A write request is received to write a data block having a logical block address to a nonvolatile storage device. The method includes writing a value of the data block to the nonvolatile storage device. The writing includes locating a position in a tree-based data structure that includes first and second nodes. The first node is configured to store a first set of data blocks having logical block addresses in a first numerical range, and the second node is configured to store a second set of data blocks having logical block addresses in a second numerical range. The position is located in the first node or the second node depending on the value of the logical block address. The writing includes storing the value of the data block in the position in the tree-based data structure.

Using a tree-based data structure to map logical addresses to physical addresses on a storage device

A method, device, and non-transitory computer readable medium that dynamically allocates cache resources includes monitoring a hit or miss rate of a service level objective for each of a plurality of prior workloads and a performance of each of a plurality of cache storage resources. At least one configuration for the cache storage resources for one or more current workloads is determined based at least on a service level objective for each of the current workloads, the monitored hit or miss rate for each of the plurality of prior workloads and the monitored performance of each of the plurality of cache storage resources. The cache storage resources are dynamically partitioned among each of the current workloads based on the determined configuration.

Method for using service level objectives to dynamically allocate cache resources among competing workloads

A hierarchically tagged cache provides abstraction between access requests for data and the cached data. The cache is managed by hierarchical layers of indexes including reference to the data. Access requests indicate a header for the requested data, which is associated with one of the layers. Cache management determines what layer is associated with the header, and can traverse the indexes, beginning at the layer associated with the header, to access the data. If the header does not exist at the index of that layer, it can be created. Indexes can be appropriately updated with indexes at each layer being referenced by one or more indexes of the layer higher up in the hierarchy.

Hierarchically tagged cache

A storage system provides highly flexible data layouts that can be tailored to various different applications and use cases. The system dynamically balances performance with block sharing, based on service level objectives (SLOs). The system defines several types of data containers, including 'regions', 'logical extents' and &#x201c;slabs&#x201d;. Each region includes one or more logical extents. Allocated to each logical extent is at least part of one or more slabs allocated to the region that includes the extent. Each slab is a set of blocks of storage from one or more physical storage devices. The slabs can be defined from a heterogeneous pool of physical storage. The system also maintains multiple &#x201c;volumes&#x201d; above the region layer. Each volume includes one or more logical extents from one or more regions. Layouts of the extents within the regions are not visible to any of the volumes.

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Cambridge, MA, United States of America

Keith Arnold Smith