The document discusses various distributed file systems (DFS) such as OpenAFS, GlusterFS, HDFS, and Ceph, detailing their features, use cases, and performance characteristics. It explores the challenges of storage in modern data centers and offers case studies showing implementations of these systems to address specific problems. The conclusion presents insights on factors such as bandwidth, data replication, and requirements for managing large-scale storage systems.

1. Use Distributed File system as a Storage Tier
FabrizioManfred Furuholmen

2. Agenda
 Introduction
 Next Generation Data Center
 Distributed File system
 Distributed File system
 OpenAFS
 GlusterFS
 HDFS
 Ceph
 Case Studies
 Conclusion
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3. Class Exam
 What do you know about DFS ?
 How can you create a Petabyte
storage ?
 How can you make a centralized
system log ?
 How can you allocate space for your
user or system, when you have a
thousands of users/systems ?
 How can you retrieve data from
everywhere ?
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4. Introduction
Next Generation Data Center: the ―FABRIC‖
Key categories:
 Continuous data protection and disaster
recovery
 File and block data migration across
heterogeneous environments
 Server and storage virtualization
 Encryption for data in-flight and at-rest
In other words: Cloud data center
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5. Introduction
Storage Tier in the ―FABRIC‖
 High Performance
 Scalability
 Simplified Management
 Security
 High Availability
Solutions
 Storage Area Network
 Network Attached Storage
 Distributed file system
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6. Introduction
What is a Distributed File system ?
“A distributed file system takes advantage of the
interconnected nature of the network by storing
files on more than one computer in the network
and making them accessible to all of them..”
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7. Introduction
What do you expected from a distributed file system ?
• Uniform Access: file names global support
• Security: to provide a global authentication/authorization
• Reliability: the elimination of each single point of failure
• Availability: administrators perform routine maintenance while the file
server is in operation, without disrupting the user’s routines
• Scalability: Handle terabytes of data
• Standard conformance: some IEEE POSIX file system semantics standard
• Performance: high performance
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8. Part II
Implementations
How many DFS do you know ?
8

9. OpenAFS: introduction
is theopen sourceimplementation of
AndrewFile system of IBM
Key ideas:
 Make clients do work whenever possible.
 Cache whenever possible.
 Exploit file usage properties. Understand them. One-third of Unix
files are temporary.
 Minimize system-wide knowledge and change. Do not hardwire
locations.
 Trust the fewest possible entities. Do not trust workstations.
 Batch if possible to group operations.
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10. OpenAFS: design
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11. OpenAFS: components
Cell
•Cell is collection of file servers and
workstation
•The directories under /afs are
cells, unique tree
•Fileserver contains volumes
Volumes
•Volumes are "containers" or sets of
related files and directories
•Have size limit
•3 type rw, ro, backup
Mount Point Directory
Server A
•Access to a volume is provided through
a mount point Server C
•A mount point is just like a static
directory Server A+B
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12. OpenAFS: performances
OpenAFS OpenAFS OSD 2 Servers
write
40000
35000
30000
35000-40000
25000 30000-35000
20000 25000-30000
20000-25000
15000
15000-20000
10000 10000-15000
16384 5000-10000
5000
1024 0-5000
0 block
64
64
256
1024
4096
16384
4
65536
262144
kb
read
90000
80000
70000
80000-90000
60000 70000-80000
50000 60000-70000
50000-60000
40000
40000-50000
30000
30000-40000
20000 20000-30000
10000 10000-20000
131072 0-10000
0
16384 43
4
16
64
256
1024
2048
4096
16384
a

13. OpenAFS: features
 Uniform name space: same path on all
workstations
 Security: base to krb4/krb5, extended ACL,
traffic encryption
 Reliability: read-only replication, HA
database, read/write replica in OSD version
 Availability: maintenance tasks without
stopping the service
 Scalability: server aggregation
 Administration: administration delegation
 Performance: client side disk base persistent
cache, big rate client per Server
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14. openAFS: who uses it ?
Morgan Stanley IT
• Internal usage
• Storage: 450 TB (ro)+ 15 TB (rw)
• Client: 22.000
Pictage, Inc
• Online picture album
• Storage: 265TB ( planned growth to 425TB in twelve months)
• Volumes: 800,000.
• Files: 200 000 000.
Embian
• Internet Shared folder
• Storage: 500TB
• Server: 200 Storage server
• 300 App server
RZH
•Internal usage 210TB
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15. OpenAFS: good for ...
Good
• Wide Area Network
• Heterogeneous System
• Read operation > write operation
• Large number of clients/systems
• Usage directly by end-users
• Federation
Bad
• Locking
• Database
• Unicode
• Large File
• Some limitations on ..
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16. GlusterFS
“Gluster can manage data in a
single global namespace on
commodity hardware..‖
Keys:
 Lower Storage Cost—Open source software runs on commodity
hardware
 Scalability—Linearly scales to hundreds of Petabytes
 Performance—No metadata server means no bottlenecks
 High Availability—Data mirroring and real time self-healing
 Virtual Storage for Virtual Servers—Simplifies storage and keeps VMs
always-on
 Simplicity—Complete web based management suite
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17. GlusterFS: design
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18. GlusterFS: components
Volume
volume posix1
•Volume is the basic element for data type storage/posix
export option directory /home/export1
•The volumes can be stacked for end-volume
extension
Capabilities
volume brick1
•Specific options (features) can be type features/posix-locks
enabled for each volume (cache, pre option mandatory
fetch, etc.) subvolumes posix1
•Simple creation for custom extensions end-volume
with api interface
Services volume server
type protocol/server
•Access to a volume is provided through option transport-type tcp
services like tcp, unix socket, option transport.socket.listen-port 6996
infiniband subvolumes brick1
option auth.addr.brick1.allow *
end-volume
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19. Gluster: components
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20. Gluster: performance
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21. Gluster: carateristics
 Uniform name space: same path on all
workstation
 Reliability: read-1 replication, asynchronous
replication for disaster recovery
 Availability: No system downtime for
maintenance (better in the next release)
 Scalability: Truly linear scalability
 Administration: Self Healing, Centralized logging
and reporting, Appliance version
 Performance: Stripe files across dozens of
storage blocks, Automatic load balancing, per
volume i/o tuning
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22. Gluster: who uses it ?
 Avail TVN (USA)
400TB for Video on demand, video
storage
 Fido Film (Sweden)
visual FX and Animation studio
 University of Minnesota (USA)
142TB Supercomputing
 Partners Healthcare (USA)
336TB Integrated health system
Origo(Switzerland)
open source software development
and collaboration platform
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23. Gluster: good for ...
Good
• Large amount of data
• Access with different protocols
• Directly access from applications
(api layer)
• Disaster recover (better in the
next release)
• SAN replacement, vm storage
Bad
• User-space
• Low granularity in security setting
• High volumes of operations on
same file
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24. Implementations
Implementations
Old way
 Metadata and data in the same place
 Single stream per file
New way
 Multiple streams are parallel channels
through which data can flow
 Files are striped across a set of nodes in
order to facilitate parallel access
 OSD Separation of file metadata
management (MDS) from the storage of
file data
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25. HDFS: Hadoop
HDFS is part of the Apache
Hadoopproject which develops
open-source software for
reliable, scalable, distributed
computing.
Hadoop was inspired by Google’s
MapReduce and Google File
system
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26. HDFS: Google File System
― Design of a file systems for a different environment
where assumptions of a general purpose file system
do not hold—interesting to see how new assumptions
lead to a different type of system…‖
Key ideas:
 Component failures are the norm.
 Huge files (not just the occasional file)
 Append rather than overwrite is typical
 Co-design of application and file system API—specialization.
For example can have relaxed consistency.
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27. HDFS: MapReduce
“Moving Computation is Cheaper than Moving Data”
Map
• Split and mapped in key-
value pairs
Combine
• For efficiency reasons, the
combiner works directly to map
operation outputs .
Reduce
• The files are then
merged, sorted and reduced
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28. HDFS: goals
Scalable: can reliably store and
process petabytes.
Economical: It distributes the data and
processing across clusters of
commonly available computers.
Goals
Efficient: can process data in parallel
on the nodes where the data is
located.
Reliable: automatically maintains
multiple copies of data and
automatically redeploys computing
tasks based on failures.
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29. HDFS: design
29

30. HDFS: components
Namenode
• An HDFS cluster consists of a single
NameNode
• It is a master server that manages
the file system namespace and
regulates access to files by clients.
Datanodes
• Datanode manage storage attached
to the system it run on
• Applay the map rule of MapReduce
Blocks
• File is split into one or more blocks
and these blocks are stored in a set
of DataNodes
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31. HDFS: features
 Uniform name space: same path on all
workstations
 Reliability: rw replication, re-balancing, copy
in different locations
 Availability: hot deploy
 Scalability: server aggregation
 Administration: HOD
 Performance: “grid” computation, parallel
transfer
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32. HDFS: who uses it ?
Yahoo!
A9.com
AOL
Booz Allen Hamilton
EHarmony
Facebook
Freebase
Fox Interactive Media
IBM
ImageShack
ISI
Major players Joost
Last.fm
LinkedIn
Metaweb
Meebo
Ning
Powerset (now part of Microsoft)
Proteus Technologies
The New York Times
Rackspace
Veoh
Twitter
…
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33. HDFS: good for ...
Good
• Task distribution (Basic GRID
infrastructure)
• Distribution of content (High
throughput of data access )
• Archiving
• Etherogenous envirorment
Bad
• Not General purpose File system
• Not Posix Compliant
• Low granularity in security setting
• Java
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34. Ceph
“Ceph is designed to handle workloads
in which tens thousands of clients or
more simultaneously access the same
file orwrite to the same directory–
usage scenarios that bring typical
enterprise storage systems to their
knees.‖
Keys:
 Seamless scaling — The file system can be seamlessly expanded by simply
adding storage nodes (OSDs). However, unlike most existing file systems, Ceph
proactively migrates data onto new devices in order to maintain a balanced
distribution of data.
 Strong reliability and fast recovery — All data is replicated across multiple
OSDs. If any OSD fails, data is automatically re-replicated to other devices.
 Adaptive MDS — The Ceph metadata server (MDS) is designed to dynamically
adapt its behavior to the current workload.
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35. Ceph: design
• Client
• Metadat
OSD a Cluster
• Object
Storage
Cluster
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36. Ceph: features
Dynamic Distributed Metadata
• Metadata Storage
• Dynamic Subtree Partitioning
• Traffic Control
Reliable Autonomic Distributed Object
Storage
• Data Distribution
• Replication
• Data Safety
• Failure Detection
• Recovery and Cluster Updates
36

37. Ceph: features
Pseudo-random data distribution function (CRUSH)
Reliable object storage service (RADOS)
Extent B-tree object File System (today btrfs)
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38. Ceph: features
Splay Replication
• Only after it has been safely committed to disk is a final commit
notification sent to the client.
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39. Ceph: good for …
Good
• Scientific application, High
throughput of data access
• Heavy Read / Write operations
• It is the most advance distributed
file system
Bad
• Young (Linux 2.6.34)
• Linux only
• Complex
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40. Others
Lustre PVFS MooseFS
Cloudstore
PNFS …
(kosmos)
Search
XtreemFS Tahoe-LAFS
Wikipedia..
40

41. Part III
Case Studies
41

42. Class Exam
 What can DFS do for you ?
 How can you create a Petabyte
storage ?
 How can you make a centralized
system log ?
 How can you allocate space for your
user or system, when you have a
thousands of users/systems ?
 How can you retrieve data from
everywhere ?
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43. File sharing
Problem
•Share Documents across a wide
network area
•Share home folder across different
Terminal servers
Solution
•OpenAFS
•Samba
Results
•Single ID, Kerberos/ldap
•Single file system
Usage
•800 users
•15 branch offices
•File sharing /home dir
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44. Web Service
Problem
• Big Storage on a little budget
Solution
• Gluster
Results
• High Availability data storage
• Low price
Usage
• 100 TB image archive
• Multimedia content for web site
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45. Internet Disk: myS3
Problems
•Data from everywhere
•Disaster Recover
Solution
•myS3
•Hadoop / OpenAFS
Results
•High Availability
•Access through HTTP protocol (REST
Interface)
•Disaster Recovery
Usage
•Users backup
•Application backend
•200 Users
•6 TB
45

46. Log concentrator
Problem
• Log concentrator
Solution
• Hadoop cluster
• Syslog-NG
Results
• High availability
• Fast search
• “Storage without limits”
Usage
• Security audit and access control
46

47. Private cloud
Problems
• Low cost VM storage
• VM self provisioning
Solution
• GlusterFS
• openAFS
• Custom provisioning
Rresults
• Auto provisioning
• Low cost
• Flexible solution
Usage
• Development env
• Production env

48. Conclusion: problems
Do you have enough bandwidth ?
 Failure
For 10 PB of storage, you will have an
average of22consumer-grade SATA drives
failing per day.
 Read/write time
Each of the 2TB drives takes approximately
best case 24,390 seconds to be read and
written over the network.
 Data Replication
Data replication is the number of the disk
drives, plus difference.
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49. Conclusion
Environment Analysis
• No true Generic DFS
• Not simple move 800TB btw different solutions
Dimension
• Start with the right size
• Servers number is related to speed needed and number of clients
• Network for Replication
Divide system in Class of Service
• Different disk Type
• Different Computer Type
System Management
• Monitoring Tools
• System/Software Deploy Tools
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50. Conclusion: next step
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51. Links
OpenAFS Gluster Hadoop Ceph
• www.openafs.org • www.gluster.org • Hadoop.apache.org • ceph.newdream.n
• www.beolink.org • Isabel Drost et
• Publication
• Mailing list
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52. I look forwardto meeting you…
XVII European AFS meeting 2010
PILSEN - CZECH REPUBLIC
September 13-15
Who should attend:
 Everyone interested in deploying a globally accessible
file system
 Everyone interested in learning more about real
world usage of Kerberos authentication in single
realm and federated single sign-on environments
 Everyone who wants to share their knowledge and
experience with other members of the AFS and
Kerberos communities
 Everyone who wants to find out the latest
developments affecting AFS and Kerberos
More Info: http://afs2010.civ.zcu.cz/
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53. Thankyou
manfred@zeropiu.com