Abstract: Techniques are provided for dynamically implementing quality of service policies for a distributed storage system based upon resources saturation. A quality of service policy is defined for throttling I/O operations received by a node of the distributed storage system based upon whether resources of the node have become saturated. The quality of service policy is dynamically implemented based upon ever changing resource utilization and saturation. Dynamically implementing the quality of service policy improves the ability to efficiently utilize resources of the node compared to conventional static polices that cannot adequately react to such changing considerations and resource utilization/saturation. With conventional static policies, an administrator manually defines a minimum amount of guaranteed resources and/or a maximum resource usage cap that could be set to values that result in inefficient operation and resource starvation.

Abstract: Techniques are provided for dynamically implementing quality of service policies using a configurable quality of service provider pipeline. A quality of service policy is defined for throttling I/O operations received by a node based upon whether resources of the node have become over utilized. The quality of service policy is used to dynamically construct a quality of service provider pipeline with select quality of service providers that improve the ability to efficiently utilize resources compared to conventional static polices that cannot adequately react to changing considerations and resource utilization/saturation. With conventional static policies, an administrator manually defines a minimum amount of guaranteed resources and/or a maximum resource usage cap that could be set to values that result in inefficient operation and resource starvation. Dynamically constructing and utilizing the quality of service provider pipeline results in more efficient operation and mitigates resource starvation.

Abstract: Techniques are provided for dynamically implementing quality of service policies for a distributed storage system based upon resources saturation. A quality of service policy is defined for throttling I/O operations received by a node of the distributed storage system based upon whether resources of the node have become saturated. The quality of service policy is dynamically implemented based upon ever changing resource utilization and saturation. Dynamically implementing the quality of service policy improves the ability to efficiently utilize resources of the node compared to conventional static polices that cannot adequately react to such changing considerations and resource utilization/saturation. With conventional static policies, an administrator manually defines a minimum amount of guaranteed resources and/or a maximum resource usage cap that could be set to values that result in inefficient operation and resource starvation.

Abstract: Techniques are provided for dynamically implementing quality of service policies using a configurable quality of service provider pipeline. A quality of service policy is defined for throttling I/O operations received by a node based upon whether resources of the node have become over utilized. The quality of service policy is used to dynamically construct a quality of service provider pipeline with select quality of service providers that improve the ability to efficiently utilize resources compared to conventional static polices that cannot adequately react to changing considerations and resource utilization/saturation. With conventional static policies, an administrator manually defines a minimum amount of guaranteed resources and/or a maximum resource usage cap that could be set to values that result in inefficient operation and resource starvation. Dynamically constructing and utilizing the quality of service provider pipeline results in more efficient operation and mitigates resource starvation.

Abstract: Techniques are provided for dynamically implementing quality of service policies for a distributed storage system based upon resources saturation. A quality of service policy is defined for throttling I/O operations received by a node of the distributed storage system based upon whether resources of the node have become saturated. The quality of service policy is dynamically implemented based upon ever changing resource utilization and saturation. Dynamically implementing the quality of service policy improves the ability to efficiently utilize resources of the node compared to conventional static polices that cannot adequately react to such changing considerations and resource utilization/saturation. With conventional static policies, an administrator manually defines a minimum amount of guaranteed resources and/or a maximum resource usage cap that could be set to values that result in inefficient operation and resource starvation.

Abstract: Techniques are provided for dynamically implementing quality of service policies using a configurable quality of service provider pipeline. A quality of service policy is defined for throttling I/O operations received by a node based upon whether resources of the node have become over utilized. The quality of service policy is used to dynamically construct a quality of service provider pipeline with select quality of service providers that improve the ability to efficiently utilize resources compared to conventional static polices that cannot adequately react to changing considerations and resource utilization/saturation. With conventional static policies, an administrator manually defines a minimum amount of guaranteed resources and/or a maximum resource usage cap that could be set to values that result in inefficient operation and resource starvation. Dynamically constructing and utilizing the quality of service provider pipeline results in more efficient operation and mitigates resource starvation.

Abstract: 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.

Abstract: Techniques are provided for upgrading an external distributed storage layer that provides storage services to containerized applications hosted within a container hosting platform. An operator within the container hosting platform is custom configured to orchestrate, from within the container hosting platform, the upgrade for the external distributed storage layer. Because the external distributed storage layer and the container hosting platform are separate computing environment that utilize different namespaces, semantics, operating states, and/or application programming interfaces, a cluster controller within the container hosting platform is custom configured to reformat/translate commands between the external distributed storage layer and the container hosting platform for performing the upgrade.

Abstract: 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.

Abstract: 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.

Abstract: A technique organizes storage nodes of a cluster into failure domains logically organized vertically as protection domains of the cluster and stores replicas (i.e., one or more copies) of data (e.g., data block) on separate protection domains to ensure a replicated data layout such that a plurality of copies of a data block are resident at least on two or more different failure domains of nodes. An enhancement to the technique extends the layout of replicated data to include consideration of additional failure domains logically organized horizontally as replication zones of nodes storing the data. Each row (i.e., horizontal failure domain) is illustratively embodied as a “replication zone” that contains all replicas of the data block such that the blocks remain within the replication zone, i.e., no copies or replicas of data blocks are made between different replication zones.