1 theophilus benson*, aditya akella*, aman shaikh + *university of wisconsin, madison + att labs...
TRANSCRIPT
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DEMYSTIFYING CONFIGURATION CHALLENGES IN NETWORK-BASED ISP SERVICES
Theophilus Benson*, Aditya Akella*, Aman Shaikh+
*University of Wisconsin, Madison+ ATT Labs Research
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Adoption of Network-based Services
ISP Core
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Adoption of Network-based Services
“By 2015, annual global IP traffic will reach 966 exabytes” [Cisco’11]
Customers adopting new applications ISPs upgrade and purchase new equipment Best effort ineffective for some applications
2010 2011 2012 2013 2014 20150E+00
2E+05
4E+05
6E+05
8E+05
1E+06
Time (in Years)
Siz
e o
f In
tern
et
Tra
ffic
(In
PB
)
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Adoption of Network-based Services
Services are a crucial part of the Internet’s ecosystem
ISP Core
Host-based and network-based services “AT&T to spend $1 billion to ramp up enterprise services” Recover cost and improve application performance
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Goals
Vision: Improve service integration/upgrades Simplify service management
Understand impediments Service configuration files Complexity of configuration
EdgeEdge
ISP Core
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Configuration is a crucial component
Configuration determines Customer functionality ISP interactions
Configuration is complex Most time consuming task [Feamster ‘05 ]
Most error-prone > 50% customer problems due to configuration errors [Yankee Group ‘04]
OSPF
BGP
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Configuring a Service
PECEPE CE
acz
ISP Core
Control Plane
Data plane
acz
acz
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Contributions
Analyzed 2.5 years of configurations Show how complexity evolves over time
Worsens over time
Highlight the location of complexity Complexity exists at the edge
Identify the cause of complexity Due to provisioning of new customers
PEPE
ISP CoreCE
EdgeCustomersEdge
Customers
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Contributions
Identified potential ways to mitigate complexity Showed the impact of design choices on complexity
Vendor
Co
mp
lex
ity
#1 #2
Routing DesignC
om
ple
xit
y#1 #2 #3
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Outline
Motivation Background Models and Data-Set Understanding Complexity Mitigating Complexity Conclusion
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Configuring the Provider’s Edge
Complexity is due to: Dependent commands
PECEPE CE
ISP Core
Ip vrf blueRd 23234:100223Route-target import 1000:1Route-target export 1000:1!Interface ethernet1Ip address 128.105.82.66/30Ip vrf forwarding blueServices-policy output policy1!Policy-map policy1Policy 100 20 confirm-action transmit
VRF
Interface
Policy-map
a
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Configuring the Control-Plane Core
PECEPE CE
Router bgp 65000Neighbor 129.168.6.6Neighbor 129.168.2.2!
Ip vrf blueRd 23234:100223Route-target import 1000:1Route-target export 1000:1!Router bgp 65000Neighbor 129.168.2.1Neighbor 129.168.2.1
ISP Core
acz
acz
acz
Complexity is due to: Dependent commands Maintaining consistency
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Configuring the Data-Plane Core
PECEPE CE
acz
acz
Interface gigethernet1Ip address 128.105.82.66/30!Router ospf 2Network 128.105.82.0/24!
Ip vrf blueRd 23234:100223Route-target import 1000:1Route-target export 1000:1!Interface gigethernet1Ip address 128.105.82.65/30!
ISP Corea
Complexity is due to: Dependent commands Maintaining consistency
acz
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Models and Data-Set
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Requirements for Data Models
Quantify complexity of configuration Capture dependencies between commands Capture consistency across devices
Use complexity metrics [Benson ‘09] Motivated by software engineering techniques
Abstract away low level details Abstract groups of commands stanzas
15
Ip vrf blueRd 23234:100223!Interface ethernet1Ip address 128.105.82.66Ip vrf forwarding blueServices-policy input policy2!
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Data Models
Referential Graph [Benson ‘09] Syntactic dependencies operators must track Network graph of dependent stanzas Metric: size of graph Larger graph more dependencies
Templates [Benson ‘09] Clone detection used to capture uniformity
VRF
Interface
Policy-map
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Data-Set
Service % of Routers ( PE + Core)
VPN 48%
VPLS 27%
VoIP 5%
DDoS Prev. 31%
Virtual Wire 25%
Diversity allows for a comprehensive study
Collected data from tier-1 ISP for 2.5 years 5 services: VPN, VPLS, VoIP, DDoS Prev., Virtual Wire Daily snapshots of router configuration files Metadata (per router): vendor, role and location
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Understanding Complexity Provider Edge (PE) Complexity Control-Plane Core Complexity Data-Plane Core Complexity
PEPE
ISP CoreCE
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Understanding Complexity Provider Edge (PE) Complexity Control-Plane Core Complexity Data-Plane Core Complexity
PEPEISP Core CE
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PE Complexity over Time
Growth is due to worsening complexity New devices have less dependencies
Over time, configuration tasks become tricky
Dec 08
Dec 10
0E+0
2E+5
4E+5
6E+5
8E+5
1E+6
DDoS V-Wire VplsVPN VoIP
Time (in Months)
To
tal #
of
Re
f. L
ink
s
Dec 08
Dec 10
0
500
1000
1500
2000
2500
DDoS V-Wire VplsVPN VoIP
Time (in Months)
Ma
x P
E G
rap
h S
ize
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Understanding PE Complexity Which stanza contributes to VPLS growth?
Edge EdgeISP Core
VRF
Interface
Policy-map
Dec 08
Dec 10
0%20%40%60%80%
100%
Interface CoS VRF
Time (in Months)
Pe
rce
nta
ge
of
Sta
nza
s
Dec 08
Dec 10
0%20%40%60%80%
100%
Interface CoS VRF
Time (in Months)
Pe
rce
nta
ge
of
Sta
nza
s
VRF
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Understanding PE Complexity Which stanza contributes to VPN growth?
Complexity caused by customer provisioning
Edge EdgeISP Core
VRF
Interface
Policy-map
Dec 08
Dec 10
0%20%40%60%80%
100%
Interface CoS VRF
Time (in Months)
Pe
rce
nta
ge
of
Sta
nza
s
Dec 08
Dec 10
0%20%40%60%80%
100%
Interface CoS VRF
Time (in Months)
Pe
rce
nta
ge
of
Sta
nza
s
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Configuration Reuse over Time
Specialization leads to added complexity
• Reuse and specialization exists• Configuration overlap reduces over time
– Reduction due to specialized usage of service
0% 20% 40% 60% 80% 100%0
0.2
0.4
0.6
0.8
1
VPN 2008
Percentage of Reuse
CD
F o
f C
us
tom
ers
0% 20% 40% 60% 80% 100%0
0.2
0.4
0.6
0.8
1
VPN 2008 VPN 2010
Percentage of Reuse
CD
F o
f C
us
tom
ers
71%
62%88%
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Understanding Complexity
Data-Plane Core: service-agnostic and simple Control-Plane Core: distinct across services
Growing number of adjacencies with PEs
PE is the most complex
PEPE
ISP CoreCE
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Mitigating Complexity Vendor Selection
Cost
Fu
nct
ion
alit
y
Comple
xity
Time
Co
mp
lexi
ty
TimeC
om
ple
xity
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How to Compare Vendors
Different vendors different languages Language impacts complexity Difference in structure of functionality
Comparing vendor languages Configurations representing same policy Same customer same policy on all PEs
PECEPE CE
ISP Core
Vendor1Vendor2
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Vendor Selection
Graph for vendor1 is consistently larger Vendor1 requires more stanzas for same policies Operators need to track more dependencies
Choice of vendor can reduce PE complexity
1 2 3 4 5 6 70.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
Anonymized Customer ID
Ra
tio
of
Re
fere
nti
al g
rap
h(V
en
do
r1/V
en
do
r2)
1 2 3 4 5 6 70.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
Anonymized Customer ID
Ra
tio
of
Re
fere
nti
al g
rap
h(V
en
do
r1/V
en
do
r2)
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Conclusion
Studied the factors that impede services Complexity grows over time
Modifications become time consuming
Most complexity lies in configuring customers Varying requirements and specialized configuration
Framework to systematically consider complexity Choice of vendor can reduce complexity
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Thank You
Theophilus Benson ([email protected])
"Complex systems are built out of a myriad of simple components"