Transcript Distributing Caching on Large IP Networks Adrian Chadd & Andrew Khoo Versatel Telecom – Amsterdam NL NANOG17 – Distributed Caching in Large IP Environments Adrian.

Distributing Caching on
Large IP Networks
Adrian Chadd & Andrew Khoo
Versatel Telecom – Amsterdam NL
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
Why Cache?
• Average client bandwidth growth is exceeding backbone
capacity growth
• The internet is the ‘unknown’ factor – congestion problems
outside your control
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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Caching Problems Today
• Bad server implementations of HTTP/1.1
• Bad implementation of dynamic content timeouts
• Some websites use client IP as part of authentication
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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Inter-cache communication
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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ICP
• Very basic method of inter-cache communication
• Only HIT/MISS information is propagated between caches
• Connectionless (UDP) based
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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Cache Digests
• Utilizes a ‘bloom filter’ to determine caches with higher
probabilities of having given objects
• Periodic exchanges of digests between caches
• Not Exact! Miss = 0% chance of having object, Hit =
>95% chance of having object
• Work ‘in progress’
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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Caching a large network
- a case study
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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Cache Objectives
• Primary goal: Improve client response times
• Secondary goal: Reduce bandwidth usage
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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Backbone Europe
LHR
155Mbps
level3
LINX
155+155
L3
FRA
622
VT
Amsterdam
2x100
M2
100
155
DCIX
PARIX
622
AMSIX
100
T3-ATM
155
CDG
100
BRU
100
SFINX
622
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
B-NIX
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Backbone US
45Mbps
AADS
ORD
155Mbps
PAIX
100T
100Mbps
PAIX
FDDI
MAE
West
155Mbps
100Mbps
Backup
transit to
“Internet”
155Mbps
NYC
AMS
155Mbps
100Mbps
DC
FDDI
100T
CIX
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
MAE
East
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Cache Backbone
United States
Europe
London
2 x OC3/STM-1
New York
OC3/STM-1
Amsterdam
OC3/
STM-1
OC3/STM-1
Paris
Each POP has a
single cache cluster
OC12/
STM-4
Frankfurt
Brussels
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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Backbone POP Design
Cisco GSR12008
Core Router
155Mbps POS
Juniper M40
Core Router
155Mbps POS
Cisco 7206vxr
Aggregator #1
Cisco 7206vxr
Aggregator #2
100baseT
Cisco 2948
100T cust attach
Routing Path #1
155Mbps POS
100baseT
100baseT
Cisco Cat5505
100T cust attach
Routing Path #2
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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NL Core Network Topology
155Mbps to NYC
AMS-IX #2
AMS-IX #1
VERSATOWER
Gigabit
Ethernet
100bT to Carrier1
100bT
7204
NIKHEF
Business Internet
(via ATM)
7206vxr
SARA
100bT
45Mbps
100bT
100bT
155Mbps
M40
7206vxr
7202
100bT
4-way 155Mbps
router mesh
155Mbps
155Mbps
Dial Access
Platform
GSR
100bT
GSR
7206vxr
Data Operations
155Mbps to
Svianed #1
155Mbps to
Svianed #2
MATRIX-2
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
7202
Free Internet/ISP Platform
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Single Cache Cluster
Clients
Frontend 1
Frontend 2
Frontend 3
Backend 1
Backend 2
Backend 3
Internet
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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Single Cache Cluster (2)
•
•
•
•
•
Frontends handle client requests
Backends handle server requests
Frontends ICP each other
Each backend exports a cache digest to each frontend
Backends do NOT communicate
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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Hierarchy construction
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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Problems with conventional
hierarchies
• Conventional hierarchies use static or domain based
parent/peer selection
• Network/server failures can affect client response times
• Limited network topology intelligence through a ‘whois’
interface
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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How to ‘route’ cache peer
selection
• Using transparent redirection at each border, let your
network route requests for you
• Network failures are handled correctly
• Method is performance-friendly, but not optimally
bandwidth-friendly
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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Cache pre-population
• Cache prepopulation WORKS !
• Parsing ‘friendly’ provider logs from timezones before your
own
• Walk ‘popular’ websites before sunlight
• Parsing your own logs and issuing IMS requests
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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Melting squid caches
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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Melting squid caches –
filesystem performance
• Directory seek overhead
• No concept of object relationships / locality, defeating
‘read-ahead’
• Current implementation uses threads to fake async file
access
• Disks are still linear :-)
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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Melting squid caches - IFS
• IFS – “inode filesystem”
• Exporting flat inode namespace to squid
• Not optimal by far, but relaxes disk seek and memory
usage
• Integration into squid is under way
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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Melting squid caches – poor
network performance
• Using larger buffer sizes on outgoing requests
• Reduce the TIME_WAIT period to cycle through sockets
quicker
• QoS on your internal network
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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Melting squid caches – ICP
•
•
•
•
Dropped ICP packets result in noticeable client delays
ICP not suitable for busy WAN links
Cache digests are a ‘solution in progress’
Cache the ICP replies
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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Melting squid caches – other
problems
• Proprietary protocols (eg WEBDAV)
• Some browsers (MSIE) have a habit of issuing non-cache
friendly requests
• Issues with transparent redirection – eg MTU Path
Discovery, IP-based authentication
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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Caching – the next level
• True object-based caching, instead of HTTP/FTP only
• True clustering support, providing a single logical cache to
the network
• Smart ‘predictive’ caches adapting to client usage patterns
• Video/Audio stream caching
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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Questions and Answers
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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The End
[email protected]
[email protected]
NANOG17 – Distributed Caching in Large IP Environments
Adrian Chadd & Andrew Khoo - 10th October 1999
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