Arvados

h1. Keep

Keep is a distributed content-addressable storage system designed for high performance in I/O-bound cluster environments.

Notable design goals and features include:

* High scalability

* Node-level redundancy

* Maximum overall throughput in a busy cluster environment

* Maximum data bandwidth from client to disk

* Minimum transaction overhead

* Elimination of disk thrashing (commonly caused by multiple simultaneous readers)

* Client-controlled redundancy

h2. Design

The above goals are accomplished by the following design features.

* Data is transferred directly between the client and the physical node where the disk is installed.

* Data collections are encoded in large (≤64 MiB) blocks to minimize short read/write operations.

* Each disk accepts only one block-read/write operation at a time. This prevents disk thrashing and maximizes total throughput when many clients compete for a disk.

* Storage redundancy is directly controlled, and can be easily verified, by the client simply by reading or writing a block of data on multiple nodes.

* Data block distribution is computed based on the MD5 digest of the data block being stored or retrieved. This eliminates the need for a central or synchronized database of block storage locations.

h2. Components

The Keep storage system consists of data block read/write services, SDKs, and management agents.

The responsibilities of the Keep service are:

* Write data blocks

* When writing: ensure data integrity by comparing client-supplied MD5 digest to client-supplied data

* Read data blocks (subject to permission, which is determined by the system/metadata DB)

* Send read/write/error event logs to management agents

The responsibilities of the SDK are:

* When writing: split data into ≤64 MiB chunks

* When writing: encode directory trees as manifests

* When writing: write data to the desired number of nodes to achieve storage redundancy

* After writing: register a collection with Arvados

* When reading: parse manifests

* When reading: verify data integrity by comparing locator to MD5 digest of retrieved data