Amazon Technologies, Inc.

Jacob A Strauss

Michael Robert Frasca

Matteo Frigo

Neal John Charbonneau

Pradeep Vincent

Matti Juhani Oikarinen

Peter Croft Jones

Jacob David Luszcz

Wayne William Duso

Daniel Nussbaum

Xiaobin Wu

John McClain

Alex Haugland

Joshua Samuel Hendrickson

Mukarram Ahmad Tahir

Rahul Shah

Mark Allen Fogleman

Akshay Kumar Saxena

Jacob Luszcz

Edward William Naim

Gerardus Theodorus Jansen

Jocob David Luszcz

Journaling for files in a distributed file system may be dynamically changed. A write request for a file in a distributed file system may be received. An evaluation of the file may be performed with respect to a journaling type change criteria. If the evaluating indicates a change to journaling type, then the write request may be performed according to a different type of journaling than was applied to prior write request. If the evaluating does not indicate a change, then a current journaling type may be applied to perform the write request.

Dynamically changing journaling types for files in a distributed file system

Methods and apparatus for identifying consistent snapshot points for file systems in a distributed storage service in which a client may access a file system in backend storage via two or more access nodes. A snapshot coordinator initiates a two-phase commit to perform a snapshot epoch transition. The coordinator sends prepare messages to the nodes. In response, a node sends a response to the coordinator, stops issuing writes to the file system, sets a timer, and waits for a commit message. Upon receiving a response from all nodes, the coordinator sends a commit message. Upon receiving the commit or the timer expiring, the nodes increment an epoch counter and begin issuing writes to the file system tagged with the new epoch and indicating that a copy-on-write operation be performed. The transition is successful if all nodes respond to the request message; otherwise, the two-phase commit is retried.

Consistent snapshot points in a distributed storage service

An LL server (LLS) may process metadata requests for a file system in LL mode in a distributed file storage services (DFSS). For requests that require allocating blocks to file system objects in the backing store, instead of relying on distributed transactions used for file systems in high throughput (HT) mode, a pool of blocks may be pre-allocated for the LL file system in the backing store, and a free block list may be maintained in local memory of the LLS. When a metadata operation requires blocks to be allocated, the blocks are assigned to the respective object from the blocks in the pool. A background process may allocate new blocks in the pool upon the number of blocks dropping below a threshold, or upon block allocation rate for the file system increasing.

Block allocation for low latency file systems

Techniques described and suggested include systems and processes for handling data and client lock management in multi-tenant storage systems, such as distributed storage systems. In some embodiments, data lock and client lock records are stored in connection with a plurality of data stores on which client data resides. In some embodiments, a storage hub operably connected to the data stores determines and retain client lease information. In some embodiments, the client lease information is used in conjunction with the data lock and client lock records to effect and determine the validity of locks on various data elements.

Data locking and state management on distributed storage systems

A distributed file storage services (DFSS) that provides low latency (LL) and high throughput (HT) modes for file systems. A HT metadata subsystem (HTMS) may use a distributed transaction system for data and metadata reads and writes for file systems in HT mode. A LL metadata subsystem (LLMS) may process metadata requests for file systems in LL mode. For metadata read requests, the LLMS may locally cache at least some of the file system metadata. For metadata write requests, the LLMS may write entries to a journal and notify the access node after the entries are committed to the journal. Data reads and writes for file systems in LL mode may be handled similarly to data reads and writes for file systems in HT mode. A file system may be converted from LL to HT mode, or from HT to LL mode.

File system mode switching in a distributed storage service

A computing resource service provider may operate a data storage service configured to provide data storage for one or more customers of the computing resource service provider. The data storage service may store customer data in one or more replicated state machines, where the replicated state machines comprise a plurality of replicated state machine-shards. The replicated state machine-shards may cause the computer system hosting the replicated state machine-shard to transmit a consensus message to other computer system. The consensus message may include utilization information corresponding to the other computer system. The utilization information may be used to calculate a utilization rate for the replicated state machine usable in block allocation operations.

Block allocation based on server utilization

An access node of a distributed service collects workload data pertaining to at least one peer group of access nodes established for handling client requests. During a particular load shedding analysis, the access node uses the collected metrics to detect that a triggering condition for load shedding with respect to a set of persistent client connections has been met. Each persistent client connection is set up to be usable for a plurality of client requests. The access node initiates a phased termination of at least one selected persistent client connection. The phased termination comprises allowing completion of in-flight requests on the connection and rejecting new requests on the connection.

Load shedding techniques for distributed services with persistent client connections to ensure quality of service

A low latency metadata subsystem for file systems in low latency (LL) mode in a distributed file storage service (DFSS). An LL server (LLS) may receive metadata requests from an access node of the DFSS. For read operations, the LLS may check a local cache of metadata and, for cache hits, retrieve the metadata from the cache. For cache misses, the metadata may be fetched from the storage subsystem of the DFSS and cached. For write operations, the LLS may write entries into a journal for the file system and notify the access node after the journal entries are committed to the journal; the journal entries are asynchronously committed in the storage subsystem. The access node may communicate with the storage subsystem to perform data reads and writes for the LL file system.

Low latency distributed storage service

A computing resource service provider may operate a data storage service configured to provide data storage for one or more customers of the computing resource service provider. The data storage service may store customer data in one or more replicated state machines, where the replicated state machines comprise a plurality of replicated state machines-shards. The replicated state machines-shards may cause the computer system hosting the replicated state machine-shard to transmit a consensus message to other computer system. The consensus message may include utilization information corresponding to the other computer system. The utilization information may be used to calculate a utilization rate for the replicated state machine useable in block allocation operations.

A node of a distributed storage service receives a read request from a client, directed to a particular physical page storing at least a portion of a file store object. The node transmits, to the client, a particular operation sequence number (OSN), obtained from a replicated state machine, indicative of an order in which the read request was processed at the node relative to other requests directed to the file store object. The node receives a write request from the client directed to the page. The write request includes the particular OSN. The node determines whether the page has been modified after the particular OSN was obtained. If the page has not been modified since the OSN was obtained, a modification indicated in the write request is performed; otherwise, the write request is rejected.

Conditional writes at distributed storage services

A node of a storage service is selected as a coordinator of a distributed transaction involving multiple page-level modifications. The coordinator identifies other nodes as members of a node chain collectively storing physical data pages at which proposed modifications are to be performed, including a decider node responsible for a decision to commit the transaction. The coordinator generates a transaction preparation message comprising a representation of an order of respective commit decisions associated with the proposed modifications, and transmits the message to a selected node of the chain for a sequential propagation along the chain. Each chain node performs a local commit analysis for its changes and stores a record of its intent to commit. If a decision to commit is reached at the decider, the proposed modifications are completed.

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Boston, MA, United States of America

Jacob A Strauss