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From "David O'Hallaron" <>
Subject [PROPOSAL] Tashi
Date Thu, 10 Jul 2008 16:00:17 GMT
This is a  proposal to enter the incubator.

See for the most
up-to-date version.

We're looking forward to comments from the community.


-- David O'Hallaron,
-- Director, Intel Research Pittsburgh
-- Assoc Prof of CS and ECE, Carnegie Mellon University

= Tashi Proposal =

A proposal to the Apache Software Foundation Incubator PMC by

David O'Hallaron^*+^, Michael Kozuch^*^, Michael Ryan^*^, Steven
Schlosser^*^, Jim Cipar^+^, Greg Ganger^+^, Garth Gibson^+^, Julio
Lopez^+^, Michael Strouken^+^, Wittawat Tantisiriroj^+^, Doug
Cutting^#^, Jay Kistler^#^, Thomas Kwan^#^

^*^Intel Research Pittsburgh, ^+^Carnegie Mellon University, ^#^Yahoo!

July 10, 2008

== 1. Abstract ==

Tashi is a cluster management system for cloud computing on Big Data.

== 2. Proposal ==

The Tashi project aims to build a software infrastructure for cloud
computing on massive internet-scale datasets (what we call ''Big
Data''). The idea is to build a cluster management system that enables
the Big Data that are stored in a cluster/data center to be accessed,
shared, manipulated, and computed on by remote users in a convenient,
efficient, and safe manner.  The system aims to  provide the following
basic capabilities:

(a) ''On-demand provisioning of storage and compute resources.'' Users
request a number of compute nodes, which can be either virtual or
physical machines, and a set of disk images to boot up on the nodes.
In response they receive their own persistent logical cluster of
compute and storage nodes, which they can then manage and use.

(b) ''Extensible end-to-end system management.'' Tashi will define
open non-proprietary interfaces for management tasks such as
observation, inference, planning, and actuation. This will keep the
system vendor-neutral and allow different research and development
groups to plug in different implementations of different management

(c) ''Cooperative storage and compute management.''  The system will
define new non-proprietary interfaces and methods that will allow
compute and storage management to work together in concert.

(d) ''Flexible storage models.'' The system will support a range of
different storage models, such as network-attached storage, per-node
storage, and hybrids, to allow developers, researchers, and large
scale cluster/data center operators to experiment with different kinds
of file systems.

(e) ''Flexible machine models.'' The system will support different
machine models.  In particular, it will be VMM-agnostic, able to run
different virtual machine monitors such as KVM and Xen. Also, in order
to address the cluster squatting problem (when clusters are balkanized
by users who reserve and hold nodes for their exclusive use) the
system will support a novel bi-model booting capability, in which
virtual machine and physical machine instances can boot from the same
disk image.

== 3. Rationale and Approach ==

Digital media, pervasive sensing, web authoring, mobile computing,
scientific and medical instruments, physical simulations, and virtual
worlds are all delivering vast new datasets relating to every aspect
of our lives. A growing fraction of this Big Data is going unused or
being underexploited due to the overwhelming scale of the data
involved.  Effective sharing, understanding, and use of this new
wealth of raw information poses one of the great challenges for the
new century.

In order to compute on this emerging Big Data, many research and
development groups are purchasing their own racks of compute and
storage servers. The goal of the Tashi project is to develop a layer
of utility software that turns these raw racks of servers into easily
managed cloud computers that will allow remote users to share and
explore their Big Data.

To our knowledge there are no open source projects addressing cluster
management for Big Data applications. We need a project such as Tashi
for a number of reasons: (1) No cloud computing cluster management
systems have tackled the problem of having both compute and storage
management working together in concert, which we believe will be
necessary to support Big Data. (2) We need non-proprietary interfaces
for cloud computing, and open source is the way to develop these. For
example, Google's new App Engine and Amazon's web services require
people to build to proprietary API's, so that their applications are
no longer vendor neutral, but are tied to a particular service
provider. (3) We need an extensible system that can serve as a
platform to stimulate research in cluster management for cloud

The Tashi system is targeted at two (not always distinct) communities:

(1) As a production system for organizations who want to offer medium
to large scale clusters to their users. For example, many companies
and university departments are purchasing such clusters, and a system
like Tashi would help them provide their users with access to the
cycles and storage in the clusters.

(2) As an extensible research platform for distributed systems researchers.

The approach for the project is to build on existing cluster
management work pioneered by projects such as Usher (UCSD), Cluster on
Demand (Duke), and EC2/S3 (Amazon), and then develop the new
capabilities that will be required to support Big Data cloud

== 4. Need for a Community Effort ==

A number of events at Yahoo, Carnegie Mellon, and Intel Research
Pittsburgh motivated the development of Tashi and convinced us to work
together in the context of an open-source community:

(a) In 2006 the Parallel Data Lab (PDL) at Carnegie Mellon built a
cluster of 400 nodes from industry donations, with a goal of creating
a "Data Center Observatory" that would allow systems researchers to
study and monitor applications running on the cluster. This dream has
been slow to materialize because of the cost and complexity of
supporting and managing multiple applications and systems groups.

(b) In Fall 2007, Yahoo began offering access to their M45 research
cluster to researchers at Carnegie Mellon, and in order to support M45
as well as their own internal production clusters, began to develop
some cloud computing infrastructure on their own.

(c) In Fall 2007, Intel Research Pittsburgh purchased a moderate-sized
100-node cluster and made it available to applications groups at
Carnegie Mellon working on various Big Data applications such as
computational photography, machine translation, automatic speech
recognition, and event detection in spatio-temporal video streams.
Provisioning and scheduling the cluster in the face of so many
different application demands has proven to be difficult.

The difficulties of managing and provisioning these different clusters
convinced us that the problem was too big for any one of us to solve
completely on our own, and that we needed to band together create a
open-source community effort focused on developing a single software

Another important reason to develop an open-source community around
Tashi is that we need non-proprietary vendor-neutral APIs for the
emerging area of cloud computing, and open source is the best way to
achieve that.

== 5. Known Risks ==

''Commitment to future development.'' The risk of the developers
abandoning the project is small, mainly because they all own and
manage moderate to large scale clusters, and desperately need
something like Tashi to provision and manage those clusters. We also
need a system like Tashi to serve as an extensible platform for our

''Experience with open source.'' Yahoo has had a significant and
positive experience with the Apache Software Foundation (ASF) and
Hadoop. While Intel and Carnegie Mellon have developed some non-ASF
style open source projects in the past (e.g., Internet Suspend/Resume,
OpenDHT, and Open``Diamond), they have no experience with ASF-style
open source communities. However, they hope to benefit from Yahoo's
considerable experience in this area.

''Diversity of developer community.'' The initial code base for Tashi
was developed by a single research programmer, Michael Ryan, at Intel
Research Pittsburgh. An important reason for putting Tashi in the
incubator is to expand the set of developers to include programmers
from Carnegie Mellon and Yahoo, initially, and later, hopefully, from
other groups such as Usher at UCSD, cluster-on-demand from Duke
University, and the RAD Lab at Berkeley.

''Relationship to other Apache projects.'' There are no Apache
projects such as Tashi that focus on systems support for cloud
domputing. However, the Tashi project is closely related to
Hadoop/HDFS. The VM-based provisioning of Tashi will subsume the now
deprecated sub-clustering functionality of Hadoop-on-demand. The Tashi
prototype uses HDFS to host the cluster boot images. Also, we expect
that many Tashi logical clusters will run Hadoop jobs.

''Reasons that Tashi is an ASF project.'' There are three main reasons
for developing Tashi through Apache rather than, say, Source``Forge.
(1) Our Yahoo partner has had a very positive experience with the
Hadoop project. (2) We recognize the need to build a strong developer
community, and Apache is centered around building such communities.
(3) The ASF also offers substantial legal oversight that makes it
attractive for cross-organizational collaborative efforts such as
Tashi.  With Source``Forge, for example, you have few guarantee about
the title of the code.  Thus, people can easily post code they don't
own, and/or change the license terms of other open source code that
they include in their projects.  So users of code from Source``Forge
must be wary.  On the other hand, Apache vets all contributions,
keeping signed documents from every committer on file, etc.

== 6. Related Work ==

A small sampling of some closely related work:

[1] M. Mc``Nett, D. Gupta, A. Bahdat, G. Voelker, "Usher: An
Extensible Framework for Managing Clusters of Virtual Machines",
Proceedings of the 21st Large Installation System Administration
Conference (LISA 07), 2007.

[2] D. Irwin, J. Chase, L. Grit, A. Yumerefendi, D. Becker, "Sharing
Networked Resources with Brokered Leases", Usenix, 2006.

[3] J. Chase, D. Irwin, L. Grit, J. Moore, S. Sprenkle, "Dynamic
Virtual Clusters in a Grid Site Manager", HPDC, 2003.

[4] S. Garfinkel, "An Evaluation of Amazon's Grid Computing Services:
EC2, S3, and SQS", Tech Report TR-08-07, School for Engineering and
Applied Sciences, Harvard University, 2007.

[5] Red``Hat oVirt System,, 2008

== 7. Source ==

We have working code, a pre-alpha proof-of-concept prototype that was
developed by Michael Ryan at Intel Research Pittsburgh. The prototype
is currently running on the 100-node cluster there. We will enter the
incubator with clean code, developed entirely by Michael Ryan, that is
unencumbered by any licensing issues.

== 8. Required Resources  ==

(a) Proposed Mailing lists:

 * tashi-private (with moderated subscriptions)
 * tashi-dev
 * tashi-commits
 * tashi-user

(b) Subversion directory


(c) Issue tracking:

 * Tashi will use JIRA for bug tracking.

== 9. Initial Committers ==

Initially, we plan to start with one committer each from Carnegie
Mellon and Intel Research, with a Yahoo committer to be determined

 * Michael Stroucken (
 * Michael Ryan (

== 10. Sponsors ==

 * ''Champion:'' Doug Cutting (
 * ''Sponsoring entity:'' Apache Incubator PMC

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