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From Niclas Hedhman <nic...@hedhman.org>
Subject Re: [VOTE] accept Tashi into the Incubator
Date Fri, 08 Aug 2008 08:08:22 GMT
On Friday 08 August 2008 06:00:57 Doug Cutting wrote:
> Niclas Hedhman wrote:
> > On Tuesday 05 August 2008 01:48:13 Doug Cutting wrote:
> >
> > -1. You get my +1 vote when the proposal text is part of the [VOTE]
> > thread. ;-)
>
> See below.

+1 for incubation.


Cheers
Niclas

> = 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 modules.
>
> (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 computing.
>
> 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 computing.
>
> == 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
> system.
>
> 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 research.
>
> ''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, Eucalyptus from UCSB, Cluster-on-Demand
> from Duke University, and the RAD Lab at University of California,
> Berkeley.
>
> ''Relationship to other Apache projects.'' There are no Apache projects
> such as Tashi that focus on systems support for cloud computing.
> 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, http://ovirt.org, 2008
>
> [6] Eucalyptus, Rich Wolski, http://eucalyptus.cs.ucsb.edu
>
> == 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
>
>   * http://svn.apache.org/repos/asf/incubator/tashi
>
> (c) Issue tracking:
>
>   * Tashi will use JIRA for bug tracking.
>
> == 9. Initial Committers ==
>
> Initially, there will be one committer each from Carnegie Mellon and
> Intel Research:
>
>   * Michael Stroucken (mxs@cmu.edu)
>   * Michael Ryan (michael.p.ryan@intel.com)
>
>
> == 10. Sponsors ==
>
>   * ''Champion:'' Doug Cutting (cutting@apache.org)
>   * ''Nominated mentors:'' Matthieu Riou <matthieu@offthelip.org>
>   * ''Sponsoring entity:'' Apache Incubator PMC
> = 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 modules.
>
> (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 computing.
>
> 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 computing.
>
> == 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
> system.
>
> 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 research.
>
> ''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, Eucalyptus from UCSB, Cluster-on-Demand
> from Duke University, and the RAD Lab at University of California,
> Berkeley.
>
> ''Relationship to other Apache projects.'' There are no Apache projects
> such as Tashi that focus on systems support for cloud computing.
> 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, http://ovirt.org, 2008
>
> [6] Eucalyptus, Rich Wolski, http://eucalyptus.cs.ucsb.edu
>
> == 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
>
>   * http://svn.apache.org/repos/asf/incubator/tashi
>
> (c) Issue tracking:
>
>   * Tashi will use JIRA for bug tracking.
>
> == 9. Initial Committers ==
>
> Initially, there will be one committer each from Carnegie Mellon and
> Intel Research:
>
>   * Michael Stroucken (mxs@cmu.edu)
>   * Michael Ryan (michael.p.ryan@intel.com)
>
>
> == 10. Sponsors ==
>
>   * ''Champion:'' Doug Cutting (cutting@apache.org)
>   * ''Nominated mentors:'' Matthieu Riou <matthieu@offthelip.org>
>   * ''Sponsoring entity:'' Apache Incubator PMC
>
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-- 
Niclas Hedhman, Software Developer

I  live here; http://tinyurl.com/2qq9er
I  work here; http://tinyurl.com/2ymelc
I relax here; http://tinyurl.com/2cgsug

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