aistore

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 Go to latest Published: Oct 6, 2024 License: MIT

README

AIStore is a lightweight object storage system with the capability to linearly scale out with each added storage node and a special focus on petascale deep learning.

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AIStore (AIS for short) is a built-from-scratch, lightweight storage stack tailored for AI apps. It's an elastic cluster that can grow and shrink at runtime and can be ad-hoc deployed, with or without Kubernetes, anywhere from a single Linux machine to a bare-metal cluster of any size.

AIS consistently shows balanced I/O distribution and linear scalability across arbitrary numbers of clustered nodes. The ability to scale linearly with each added disk was, and remains, one of the main incentives. Much of the initial design was also driven by the ideas to offload custom dataset transformations (often referred to as ETL). And finally, since AIS is a software system that aggregates Linux machines to provide storage for user data, there's the requirement number one: reliability and data protection.

Features

  • Deploys anywhere. AIStore deploys immediately and anywhere, from an all-in-one ready-to-use docker container and Google Colab notebook, on the one hand, to multi-petabyte Kubernetes clusters at NVIDIA data centers, on the other. There are no limitations - the system will run on any Linux machine, virtual or physical.
  • Highly available control and data planes, end-to-end data protection, self-healing, n-way mirroring, erasure coding, and arbitrary number of extremely lightweight access points.
  • REST API. Comprehensive native HTTP-based API, as well as compliant Amazon S3 API to run unmodified S3 clients and apps.
  • Unified namespace across multiple remote backends including Amazon S3, Google Cloud, and Microsoft Azure.
  • Network of clusters. Any AIS cluster can attach any other AIS cluster, thus gaining immediate visibility and fast access to the respective hosted datasets.
  • Turn-key cache. Can be used as a standalone highly-available protected storage and/or LRU-based fast cache. Eviction watermarks, as well as numerous other management policies, are per-bucket configurable.
  • ETL offload. The capability to run I/O intensive custom data transformations close to data - offline (dataset to dataset) and inline (on-the-fly).
  • File datasets. AIS can be immediately populated from any file-based data source (local or remote, ad-hoc/on-demand or via asynchronus batch).
  • Read-after-write consistency. Reading and writing (as well as all other control and data plane operations) can be performed via any (random, selected, or load-balanced) AIS gateway (a.k.a. "proxy"). Once the first replica of an object is written and finalized subsequent reads are guaranteed to view the same content. Additional copies and/or EC slices, if configured, are added asynchronously via put-copies and ec-put jobs, respectively.
  • Write-through. In presence of any remote backend, AIS executes remote write (e.g., using vendor's SDK) as part of the transaction that places and finalizes the first replica.
  • Small file datasets. To serialize small files and facilitate batch processing, AIS supports TAR, TAR.GZ (or TGZ), ZIP, and TAR.LZ4 formatted objects (often called shards). Resharding (for optimal sorting and sizing), listing contained files (samples), appending to existing shards, and generating new ones from existing objects and/or client-side files - is also fully supported.
  • Kubernetes. Provides for easy Kubernetes deployment via a separate GitHub repo and AIS/K8s Operator.
  • Access control. For security and fine-grained access control, AIS includes OAuth 2.0 compliant Authentication Server (AuthN). A single AuthN instance executes CLI requests over HTTPS and can serve multiple clusters.
  • Distributed shuffle extension for massively parallel resharding of very large datasets.
  • Batch jobs. APIs and CLI to start, stop, and monitor documented batch operations, such as prefetch, download, copy or transform datasets, and many more.

For easy usage, management, and monitoring, there's also:

  • Integrated easy-to-use CLI, with top-level commands including:
$ ais <TAB-TAB>

bucket           job              storage          remote-cluster   prefetch         evict            create
object           auth             archive          alias            put              rmo              dsort
cluster          show             log              ls               start            wait             search
config           help             tls              stop             get              blob-download
etl              advanced         performance      download         rmb              cp

AIS runs natively on Kubernetes and features open format - thus, the freedom to copy or move your data from AIS at any time using the familiar Linux tar(1), scp(1), rsync(1) and similar.

For developers and data scientists, there's also:

For the original AIStore white paper and design philosophy, for introduction to large-scale deep learning and the most recently added features, please see AIStore Overview (where you can also find six alternative ways to work with existing datasets). Videos and animated presentations can be found at videos.

Finally, getting started with AIS takes only a few minutes.

Deployment options

AIS deployment options, as well as intended (development vs. production vs. first-time) usages, are all summarized here.

Since prerequisites boil down to, essentially, having Linux with a disk the deployment options range from all-in-one container to a petascale bare-metal cluster of any size, and from a single VM to multiple racks of high-end servers. But practical use cases require, of course, further consideration and may include:

Option Objective
Local playground AIS developers or first-time users, Linux or Mac OS; to get started, run make kill cli aisloader deploy <<< $'N\nM', where N is a number of targets, M - gateways
Minimal production-ready deployment This option utilizes preinstalled docker image and is targeting first-time users or researchers (who could immediately start training their models on smaller datasets)
Easy automated GCP/GKE deployment Developers, first-time users, AI researchers
Large-scale production deployment Requires Kubernetes and is provided via a separate repository: ais-k8s

Further, there's the capability referred to as global namespace: given HTTP(S) connectivity, AIS clusters can be easily interconnected to "see" each other's datasets. Hence, the idea to start "small" to gradually and incrementally build high-performance shared capacity.

For detailed discussion on supported deployments, please refer to Getting Started.

For performance tuning and preparing AIS nodes for bare-metal deployment, see performance.

Existing datasets

AIStore supports multiple ways to populate itself with existing datasets, including (but not limited to):

  • on demand, often during the first epoch;
  • copy entire bucket or its selected virtual subdirectories;
  • copy multiple matching objects;
  • archive multiple objects
  • prefetch remote bucket or parts of thereof;
  • download raw http(s) addressable directories, including (but not limited to) Cloud storages;
  • promote NFS or SMB shares accessible by one or multiple (or all) AIS target nodes;

The on-demand "way" is maybe the most popular, whereby users just start running their workloads against a remote bucket with AIS cluster positioned as an intermediate fast tier.

But there's more. In v3.22, we introduce blob downloader, a special facility to download very large remote objects (BLOBs). And in v3.23, there's a new capability, dubbed bucket inventory, to list very large S3 buckets fast.

Installing from release binaries

Generally, AIStore (cluster) requires at least some sort of deployment procedure. There are standalone binaries, though, that can be built from source or installed directly from GitHub:

$ ./scripts/install_from_binaries.sh --help

The script installs aisloader and CLI from the most recent, or the previous, GitHub release. For CLI, it'll also enable auto-completions (which is strongly recommended).

PyTorch integration

PyTorch integration is a growing set of datasets (both iterable and map-style), samplers, and dataloaders:

Since AIS natively supports remote backends, you can also use (PyTorch + AIS) to iterate over Amazon S3, GCS and Azure buckets, and more.

Guides and References

License

MIT

Author

Alex Aizman (NVIDIA)

Directories

Path Synopsis
3rdparty
golang/mux
ais
Package ais provides core functionality for the AIStore object storage.
 Package ais provides core functionality for the AIStore object storage.
backend
Package backend contains implementation of various backend providers.
 Package backend contains implementation of various backend providers.
s3
Package s3 provides Amazon S3 compatibility layer
 Package s3 provides Amazon S3 compatibility layer
api
Package api provides native Go-based API/SDK over HTTP(S).
 Package api provides native Go-based API/SDK over HTTP(S).
apc
Package apc: API control messages and constants
 Package apc: API control messages and constants
authn
Package authn provides AuthN API over HTTP(S)
 Package authn provides AuthN API over HTTP(S)
env
Package env contains environment variables
 Package env contains environment variables
bench
microbenchmarks/disk/compare
Package main
 Package main
microbenchmarks/hrw
Package hrw provides a way to benchmark different HRW variants.
 Package hrw provides a way to benchmark different HRW variants.
microbenchmarks/http2
Package http2 puts a given number of files with a given size into AIStore.
 Package http2 puts a given number of files with a given size into AIStore.
microbenchmarks/map
Package main
 Package main
microbenchmarks/nstlvl
Package nstlvl is intended to measure impact (or lack of thereof) of POSIX directory nesting on random read performance.
 Package nstlvl is intended to measure impact (or lack of thereof) of POSIX directory nesting on random read performance.
tools/aisloader
Package aisloader
 Package aisloader
tools/aisloader/namegetter
Package namegetter is utility to generate filenames for aisloader PUT requests
 Package namegetter is utility to generate filenames for aisloader PUT requests
tools/aisloader/stats
Package stats provides various structs for collecting stats
 Package stats provides various structs for collecting stats
tools/frandread
Package frandread is a file-reading benchmark that makes a special effort to visit the files randomly and equally.
 Package frandread is a file-reading benchmark that makes a special effort to visit the files randomly and equally.
cmd
aisloader
Package main for the `aisloader` executable.
 Package main for the `aisloader` executable.
aisnode
Package main for the AIS node executable.
 Package main for the AIS node executable.
aisnodeprofile
Package main for the AIS node executable.
 Package main for the AIS node executable.
authn
Package authn is authentication server for AIStore.
 Package authn is authentication server for AIStore.
authn/tok
Package tok provides AuthN token (structure and methods) for validation by AIS gateways
 Package tok provides AuthN token (structure and methods) for validation by AIS gateways
xmeta
Package xmeta provides low-level tools to format or extract into plain text some of the AIS control structures.
 Package xmeta provides low-level tools to format or extract into plain text some of the AIS control structures.
aisfs Module
cli Module
ishard Module
cmn
Package cmn provides common constants, types, and utilities for AIS clients and AIStore.
 Package cmn provides common constants, types, and utilities for AIS clients and AIStore.
archive
Package archive: write, read, copy, append, list primitives across all supported formats
 Package archive: write, read, copy, append, list primitives across all supported formats
atomic
Package atomic provides simple wrappers around numerics to enforce atomic access.
 Package atomic provides simple wrappers around numerics to enforce atomic access.
certloader
Package certloader loads and reloads X.509 certs.
 Package certloader loads and reloads X.509 certs.
cos
Package cos provides common low-level types and utilities for all aistore projects.
 Package cos provides common low-level types and utilities for all aistore projects.
debug
Package provides debug utilities
 Package provides debug utilities
feat
Package feat: global runtime-configurable feature flags
 Package feat: global runtime-configurable feature flags
fname
Package fname contains filename constants and common system directories
 Package fname contains filename constants and common system directories
jsp
Package jsp (JSON persistence) provides utilities to store and load arbitrary JSON-encoded structures with optional checksumming and compression.
 Package jsp (JSON persistence) provides utilities to store and load arbitrary JSON-encoded structures with optional checksumming and compression.
k8s
Package k8s: initialization, client, and misc.
 Package k8s: initialization, client, and misc.
kvdb
Package kvdb provides a local key/value database server for AIS.
 Package kvdb provides a local key/value database server for AIS.
mono
Package mono provides low-level monotonic time
 Package mono provides low-level monotonic time
nlog
Package nlog - aistore logger, provides buffering, timestamping, writing, and flushing/syncing/rotating
 Package nlog - aistore logger, provides buffering, timestamping, writing, and flushing/syncing/rotating
prob
Package prob implements fully features dynamic probabilistic filter.
 Package prob implements fully features dynamic probabilistic filter.
xoshiro256
Package xoshiro256 implements the xoshiro256** RNG no-copyright
 Package xoshiro256 implements the xoshiro256** RNG no-copyright
Package core provides core metadata and in-cluster API
 Package core provides core metadata and in-cluster API
meta
Package meta: cluster-level metadata
 Package meta: cluster-level metadata
mock
Package mock provides a variety of mock implementations used for testing.
 Package mock provides a variety of mock implementations used for testing.
Package ec provides erasure coding (EC) based data protection for AIStore.
 Package ec provides erasure coding (EC) based data protection for AIStore.
ext
dload
Package dload implements functionality to download resources into AIS cluster from external source.
 Package dload implements functionality to download resources into AIS cluster from external source.
dsort
Package dsort provides distributed massively parallel resharding for very large datasets.
 Package dsort provides distributed massively parallel resharding for very large datasets.
dsort/ct
Package ct provides additional dsort-specific content types
 Package ct provides additional dsort-specific content types
dsort/shard
Package shard provides Extract(shard), Create(shard), and associated methods across all suppported archival formats (see cmn/archive/mime.go)
 Package shard provides Extract(shard), Create(shard), and associated methods across all suppported archival formats (see cmn/archive/mime.go)
etl
Package etl provides utilities to initialize and use transformation pods.
 Package etl provides utilities to initialize and use transformation pods.
etl/runtime
Package runtime provides skeletons and static specifications for building ETL from scratch.
 Package runtime provides skeletons and static specifications for building ETL from scratch.
fs
Package fs provides mountpath and FQN abstractions and methods to resolve/map stored content
 Package fs provides mountpath and FQN abstractions and methods to resolve/map stored content
health
Package health is a basic mountpath health monitor.
 Package health is a basic mountpath health monitor.
mpather
Package mpather provides per-mountpath concepts.
 Package mpather provides per-mountpath concepts.
Package hk provides mechanism for registering cleanup functions which are invoked at specified intervals.
 Package hk provides mechanism for registering cleanup functions which are invoked at specified intervals.
Package ios is a collection of interfaces to the local storage subsystem; the package includes OS-dependent implementations for those interfaces.
 Package ios is a collection of interfaces to the local storage subsystem; the package includes OS-dependent implementations for those interfaces.
Package memsys provides memory management and slab/SGL allocation with io.Reader and io.Writer interfaces on top of scatter-gather lists of reusable buffers.
 Package memsys provides memory management and slab/SGL allocation with io.Reader and io.Writer interfaces on top of scatter-gather lists of reusable buffers.
Package mirror provides local mirroring and replica management
 Package mirror provides local mirroring and replica management
Package notifications provides interfaces for AIStore notifications
 Package notifications provides interfaces for AIStore notifications
Package reb provides global cluster-wide rebalance upon adding/removing storage nodes.
 Package reb provides global cluster-wide rebalance upon adding/removing storage nodes.
Package res provides local volume resilvering upon mountpath-attach and similar
 Package res provides local volume resilvering upon mountpath-attach and similar
Package space provides storage cleanup and eviction functionality (the latter based on the least recently used cache replacement).
 Package space provides storage cleanup and eviction functionality (the latter based on the least recently used cache replacement).
Package stats provides methods and functionality to register, track, log, and StatsD-notify statistics that, for the most part, include "counter" and "latency" kinds.
 Package stats provides methods and functionality to register, track, log, and StatsD-notify statistics that, for the most part, include "counter" and "latency" kinds.
statsd
Package statsd provides a client to send basic statd metrics (timer, counter and gauge) to listening UDP StatsD server.
 Package statsd provides a client to send basic statd metrics (timer, counter and gauge) to listening UDP StatsD server.
Package sys provides methods to read system information
 Package sys provides methods to read system information
Package tools provides common tools and utilities for all unit and integration tests
 Package tools provides common tools and utilities for all unit and integration tests
docker
Packager docker provides common utilities for managing containerized AIS deployments
 Packager docker provides common utilities for managing containerized AIS deployments
readers
Package readers provides implementation for common reader types
 Package readers provides implementation for common reader types
tarch
Package archive provides common low-level utilities for testing archives
 Package archive provides common low-level utilities for testing archives
tassert
Package tassert provides common asserts for tests
 Package tassert provides common asserts for tests
tetl
Package tetl provides helpers for ETL.
 Package tetl provides helpers for ETL.
tlog
Package tlog provides common logf and logln primitives for dev tools
 Package tlog provides common logf and logln primitives for dev tools
trand
Package trand provides random string for dev tools and tests
 Package trand provides random string for dev tools and tests
Package transport provides long-lived http/tcp connections for intra-cluster communications (see README for details and usage example).
 Package transport provides long-lived http/tcp connections for intra-cluster communications (see README for details and usage example).
bundle
Package bundle provides multi-streaming transport with the functionality to dynamically (un)register receive endpoints, establish long-lived flows, and more.
 Package bundle provides multi-streaming transport with the functionality to dynamically (un)register receive endpoints, establish long-lived flows, and more.
Package volume provides volume (a.k.a.
 Package volume provides volume (a.k.a.
Package xact provides core functionality for the AIStore eXtended Actions (xactions).
 Package xact provides core functionality for the AIStore eXtended Actions (xactions).
xreg
Package xreg provides registry and (renew, find) functions for AIS eXtended Actions (xactions).
 Package xreg provides registry and (renew, find) functions for AIS eXtended Actions (xactions).
xs
Package xs is a collection of eXtended actions (xactions), including multi-object operations, list-objects, (cluster) rebalance and (target) resilver, ETL, and more.
 Package xs is a collection of eXtended actions (xactions), including multi-object operations, list-objects, (cluster) rebalance and (target) resilver, ETL, and more.

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