Arvados

h1. Introduction to Arvados

h2. Overview

Arvados is a platform for storing, organizing, processing, and sharing genomic and other big data. The platform is designed to make it easier for data scientists to develop analyses, developers to create genomic web applications and IT administers to manage large-scale compute and storage genomic resources. The platform is designed to run in the cloud or on your own hardware.

h2. Why Arvados 

A set of relatively low-level compute and data management functions are consistent across a wide range of analysis workflows and applications that are being built for genomic data. Unfortunately, every organization working with these data has been forced to build their own custom systems for these low level functions. At the same time, there are proprietary platforms emerging that seek to solve these same problems. Arvados was created to provide a common solution across a wide range of applications that would be free and open source. 

h2. Benefits

The Arvados platform seeks to solve a set of common problems faced by informaticians and IT Organizations: 

Benefits to informaticians: 

* Make authoring analyses and running workflows in "Common Workflow Language":https://commonwl.org as efficient as possible

* Provide an environment that can run open source and commercial tools (e.g. Galaxy, GATK, etc.) 

* Enable deep provenance and reproducibility across all workflows by running all workflow components inside Docker containers 

* Provide a way to flexibly organize data and ensure data integrity 

* Make queries of variant and other compact genome data very high-performance

* Create a simple way to run distributed batch processing jobs 

* Enable the secure sharing of data sets from small to very large 

* Provide a set of common APIs that enable application and workflow portability across Arvados installations

* Offer a reference environment for implementation of standards 

* Standardize file format translation

Benefits to IT organizations: 

* Low total cost of ownership 

* Eliminate unnecessary data duplication 

* Ability to create private, on-premise clouds

* Self-service provisioning of resources

* Ability to utilize low-cost off the shelf hardware

* Easy-to-manage horizontally scaling architecture

* Straight-forward browser-based administration

* Provide facilities for hybrid (public and private) clouds 

* Ensure full compliance with security and regulatory standards

* Support data sets from tens of terabytes to exabytes

h2. Functional Capabilities 

Functionally, Arvados has two major sets of capabilities: (a) data management and (b) compute management.

h3. Data Management

The data management services are designed to handle all of the challenges associated with storing and organizing large omic data sets. The heart of theses services is [[Keep]], the Arvados storage layer. The data management system is designed to handle the following needs: 

* Store files (e.g. BAM, FASTQ, VCF, etc.) reliably

* Store metadata about files for a wide variety of organizational schema

* Create collections (sets of files) that can be used in analyses 

* Ensure files are not unnecessarily duplicated

* Track provenance (sources and methods used to produce data)

* Control who can access which files

* Offer reliable distributed storage using inexpensive commodity disks

* Control storage redundancy based on importance of datasets

h3. Container Orchestration

Arvados contains a robust container orchestration system named [[Crunch]], which designed to handle the challenges associated with creating and running workflows as large scale distributed processing jobs.

* Enable a common way to represent workflows in "Common Workflow Language":https://commonwl.org

* Scale compute resources dynamically in supported cloud environments (AWS, Azure, GCP)

* Support the use of any workflow creation tool

* Optionally, store all workflows in a revision control system (git repository)

* Easily and reliably retrieve workflow outputs

* Store a record of every workflow that is run

* Eliminate the need to re-run workflow components that have already been run

* Easily and reliably re-run and verify historical workflow

* Easily share results, workflows, and applications between systems 

* [future] Create a straightforward way to author web applications that use underlying data and workflows

* [future] Run distributed computations across clusters in different data centers to make use of very large data sets 

The compute management system also includes a sub-component for doing tertiary analysis. This component provides an in-memory database for very high-performance queries of a compact representation of a genome that includes variants and other relevant data needed for tertiary analysis. This component, named Lightning, is in the prototype stage.

h2. Virtual Machines 

Arvados works best in an environment where informaticians receive access to virtual machines (VMs) on a private or public cloud. This approach eliminates the need to manage separate physical servers for different projects, significantly increasing the utilization of underlying hardware resources. It also gives informaticians a great deal of freedom to choose the best operating systems and tools for their work. With virtual machines, each informatician or project team has full isolation, security, autonomy, and privacy for their work. 

The Arvados platform provides shared common services that can be used from within a virtual machine. All of the Arvados services are accessible through APIs.

h2. APIs and SDKs 

Arvados is designed so all of the data management and compute management services can be accessed through a set of a consistent APIs and interfaces. All functionality is represented in a set of REST APIs. Arvados provides SDKs for popular languages (Python, Go, Perl, Ruby, R, and Java) as well as a standalone tool for command line use.

h2. Workbench

Arvados includes a browser-based UI which provides a convenient way to do common browsing and searching tasks. Workbench also serves as an application portal, providing a point of access to applications running on Arvados.

h2. History

The core technology was prototyped at Harvard Medical School (see [[history]]). Arvados is a modern rewrite of the original code, with refactored APIs and significant new capabilities.  

h2. Related Articles 

[[Technical Architecture]] showing key components