Detecting Peering Infrastructure Outages in the Wild Vasileios - - PowerPoint PPT Presentation

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Detecting Peering Infrastructure Outages in the Wild Vasileios - - PowerPoint PPT Presentation

Apr 29, 2023 478 likes •1.07k views

Detecting Peering Infrastructure Outages in the Wild Vasileios Giotsas , Christoph Dietzel , Georgios Smaragdakis , Anja Feldmann , Arthur Berger , Emile Aben # TU Berlin CAIDA DE-CIX MIT Akamai

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Detecting Peering Infrastructure Outages in the Wild

Vasileios Giotsas †∗, Christoph Dietzel † §, Georgios Smaragdakis ‡ †, Anja Feldmann †, Arthur Berger ¶ ‡, Emile Aben #

†TU Berlin ∗CAIDA §DE-CIX ‡MIT ¶Akamai #RIPE NCC

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Peering Infrastructures are critical part of the interconnection ecosystem

Internet Exchange Points (IXPs) provide a shared switching fabric for layer-2 bilateral and multilateral peering.

○ Largest IXPs support > 100 K of peerings, > 5 Tbps peak traffic ○ Typical SLA 99.99% (~52 min. downtime/year)1

Carrier-neutral co-location facilities (CFs) provide infrastructure for physical co-location and cross-connect interconnections.

○ Largest facilities support > 170 K of interconnections ○ Typical SLA 99.999% (~5 min. downtime/year)2

1 https://ams-ix.net/services-pricing/service-level-agreement 2http://www.telehouse.net/london-colocation/

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Outages in peering infrastructures can severely disrupt critical services and applications

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Outages in peering infrastructures can severely disrupt critical services and applications

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Outage detection crucial to improve situational awareness, risk assessment and transparency.

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Current practice: “Is anyone else having issues?”

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  • ASes try to crowd-source the detection and localization of outages.
  • Inadequate transparency/responsiveness from infrastructure operators.
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Symbiotic and interdependent infrastructures

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https://www.franceix.net/en/technical/infrastructure/

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Remote peering extends the reach of IXPs and CFs beyond their local market

Global footprint of AMS-IX

https://ams-ix.net/connect-to-ams-ix/peering-around-the-globe

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Our Research Goals

  • 1. Outage detection:

○ Timely, at the finest granularity possible

  • 2. Outage localization:

○ Distinguish cascading effects from outage source

  • 3. Outage tracking:

○ Determine duration, shifts in routing paths, geographic spread

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Challenges in detecting infrastructure outages

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Actual incident

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Challenges in detecting infrastructure outages

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Before

  • utage

VP Actual incident Observed paths

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Challenges in detecting infrastructure outages

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Before

  • utage

VP Actual incident Observed paths

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Challenges in detecting infrastructure outages

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Before

  • utage

During

  • utage

VP Actual incident Observed paths

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Challenges in detecting infrastructure outages

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AS path does not change!

Before

  • utage

During

  • utage
  • 1. Capturing the infrastructure-level hops between ASes

VP Actual incident Observed paths

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Challenges in detecting infrastructure outages

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Before

  • utage

During

  • utage

IXP or Facility 2 failed

  • 1. Capturing the infrastructure-level hops between ASes

VP Actual incident Observed paths

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Challenges in detecting infrastructure outages

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IXP is still active

Before

  • utage

During

  • utage

IXP or Facility 2 failed

During

  • utage
  • 1. Capturing the infrastructure-level hops between ASes
  • 2. Correlating the paths from multiple vantage points

VP VP Actual incident Observed paths

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Challenges in detecting infrastructure outages

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  • 1. Capturing the infrastructure-level hops between ASes
  • 2. Correlating the paths from multiple vantage points
  • 3. Continuous monitoring of the routing system

Before

  • utage

During

  • utage

During

  • utage

VP VP

No hop changes The initial hops changed

Actual incident Observed paths

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Challenges in detecting infrastructure outages

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  • 1. Capturing the infrastructure-level hops between ASes
  • 2. Correlating the paths from multiple vantage points
  • 3. Continuous monitoring of the routing system

France-IX topology

Djibouti Telecom Telkom Indonesi a

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Challenges in detecting infrastructure outages

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  • 1. Capturing the infrastructure-level hops between ASes
  • 2. Correlating the paths from multiple vantage points
  • 3. Continuous monitoring of the routing system

BGP measurement BGP BGP BGP

Djibouti Telecom Telkom Indonesi a

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Challenges in detecting infrastructure outages

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  • 1. Capturing the infrastructure-level hops between ASes
  • 2. Correlating the paths from multiple vantage points
  • 3. Continuous monitoring of the routing system

BGP BGP BGP Traceroute measurement

149.6.154.14 2 37.49.237.126

Telkom Indonesi a

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Challenges in detecting infrastructure outages

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  • 1. Capturing the infrastructure-level hops between ASes
  • 2. Correlating the paths from multiple vantage points
  • 3. Continuous monitoring of the routing system

BGP BGP BGP Traceroute measurement Traceroute Traceroute Traceroute

149.6.154.14 2 37.49.237.126

3 Giotsas, Vasileios, et al. "Mapping peering interconnections to a facility", CoNEXT 2015 4 Motamedi, Reza, et al. “On the Geography of X-Connects”, Technical Report CIS-TR-2014-02. University of Oregon, 2014 5 Nomikos, George, et al. "traIXroute: Detecting IXPs in traceroute paths.". PAM 2016

Telkom Indonesi a

IP-to-Facility3,4 and IP-to-IXP5 mapping possible but expensive!

Djibouti Telecom

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Challenges in detecting infrastructure outages

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  • 1. Capturing the infrastructure-level hops between ASes
  • 2. Correlating the paths from multiple vantage points
  • 3. Continuous monitoring of the routing system

BGP BGP BGP Traceroute Traceroute Traceroute

Can we combine continuous passive measurements with fine- grained topology discover?

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Challenges in detecting infrastructure outages

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  • 1. Capturing the infrastructure-level hops between ASes
  • 2. Correlating the paths from multiple vantage points
  • 3. Continuous monitoring of the routing system

BGP BGP BGP Traceroute Traceroute Traceroute

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Deciphering location metadata in BGP

PREFIX: 1.0.0.0/24 ASPATH: 2 1 0 COMMUNITY: 2:200

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Deciphering location metadata in BGP

PREFIX: 1.0.0.0/24 ASPATH: 2 1 0 COMMUNITY: 2:200

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BGP Communities:

  • Optional attribute
  • 32-bit numerical values
  • Encodes arbitrary

metadata

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Deciphering location metadata in BGP

PREFIX: 1.0.0.0/24 ASPATH: 2 1 0 COMMUNITY: 2:200

Top 16 bits: ASN that sets the community. Bottom 16 bits: Numerical value that encodes the actual meaning.

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Deciphering location metadata in BGP

PREFIX: 1.0.0.0/24 ASPATH: 2 1 0 COMMUNITY: 2:200

The BGP Community 2:200 is used to tag routes received at Facility 2

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Deciphering location metadata in BGP

PREFIX: 3.3.3.3/24 ASPATH: 4 3 COMMUNITY: 4:8714 4:400 PREFIX: 2.2.2.2/24 ASPATH: 4 2 COMMUNITY: 4:8714 4:400 PREFIX: 1.0.0.0/24 ASPATH: 2 1 0 COMMUNITY: 2:200

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Deciphering location metadata in BGP

PREFIX: 3.3.3.3/24 ASPATH: 4 3 COMMUNITY: 4:8714 4:400 PREFIX: 2.2.2.2/24 ASPATH: 4 2 COMMUNITY: 4:8714 4:400 PREFIX: 1.0.0.0/24 ASPATH: 2 1 0 COMMUNITY: 2:200

Multiple communities can tag different types

  • f ingress points.

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Deciphering location metadata in BGP

PREFIX: 3.3.3.3/24 ASPATH: 4 3 COMMUNITY: 4:400 PREFIX: 2.2.2.2/24 ASPATH: 4 2 COMMUNITY: 4:8714 4:400 PREFIX: 1.0.0.0/24 ASPATH: 2 1 0 COMMUNITY: 2:100

When a route changes ingress point, the community values will be update to reflect the change.

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Interpreting BGP Communities

  • Community values not

standardized.

  • Documentation in public data

sources:

○ WHOIS, NOCs websites

  • 3,049 communities by 468 ASes

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Topological coverage

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  • ~50% of IPv4 and ~30% of IPv6

paths annotated with at least one Community in our dictionary.

  • 24% of the facilities in PeeringDB,

98% of the facilities with at least 20 members.

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Passive outage detection: Initialization

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For each vantage point (VP) collect all the stable BGP routes tagged with the communities of the target facility (Facility 2)

Time

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Passive outage detection: Initialization

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For each vantage point (VP) collect all the stable BGP routes tagged with the communities of the target facility (Facility 2)

AS_PATH: 1 x COMM: 1:FAC2 AS_PATH: 2 1 0 COMM: 2:FAC2 AS_PATH: 4 x COMM: 4:FAC2 Time

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Passive outage detection: Monitoring

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Track the BGP updates of the stable paths for changes in the communities values that indicate ingress point change.

Time

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Passive outage detection: Monitoring

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AS_PATH: 2 1 0 COMM: 2:FAC1

We don’t care about AS-level path changes if the ingress-tagging communities remain the same.

Time

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Passive outage detection: Outage signal

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AS_PATH: 2 1 0 COMM: 2:FAC1 AS_PATH: 1 x COMM: 1:FAC1 AS_PATH: 4 x COMM: 4:FAC4 4:IXP

  • Concurrent changes of communities values for the same facility.
  • Indication of outage but not final inference yet!

Time

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Passive outage detection: Outage signal

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AS_PATH: 2 1 0 COMM: 2:FAC1 AS_PATH: 1 x COMM: 1:FAC1 AS_PATH: 4 x COMM: 4:FAC4 4:IXP

  • Concurrent changes of communities values for the same facility.
  • Indication of outage but not final inference yet!

Partial outage Time

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Passive outage detection: Outage signal

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AS_PATH: 2 1 0 COMM: 2:FAC1 AS_PATH: 1 x COMM: 1:FAC1 AS_PATH: 4 x COMM: 4:FAC4 4:IXP

  • Concurrent changes of communities values for the same facility.
  • Indication of outage but not final inference yet!

Partial outage? De-peering of large ASes? Major routing policy change? Time

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Passive outage detection: Outage signal

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AS_PATH: 2 1 0 COMM: 2:FAC1 AS_PATH: 1 x COMM: 1:FAC1 AS_PATH: 4 x COMM: 4:FAC4 4:IXP

Signal investigation:

  • Targeted active measurements.
  • How disjoint are the affected paths?
  • How many ASes and links have been affected?

Partial outage? De-peering of large ASes? Major routing policy change? Time

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Passive outage detection: Outage tracking

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AS_PATH: 1 x COMM: 1:FAC2 AS_PATH: 2 1 0 COMM: 2:FAC2

End of outage inferred when the majority

  • f paths return to the original facility.

Time

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De-noising of BGP routing activity

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The aggregated activity of BGP messages (updates, withdrawals, states) provides no outage indication.

Time Number of BGP messages (log)

105 103 101

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De-noising of BGP routing activity

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The aggregated activity of BGP messages (updates, withdrawals, states) provides no outage indication. The BGP activity filtered using communities provides strong

  • utage signal.

Time Number of BGP messages (log)

105 103 101

Time Number of BGP messages (log)

105 103 101 1.0 0.4 0.2 0.6 0.8

Fraction of infrastructure paths

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  • The location of community values that trigger outage signals

may not be the outage source!

  • Communities encode the ingress point closest to our VPs

(near-end infrastructure)

○ ASes may be interconnected over multiple intermediate infrastructures ○ Failures in intermediate infrastructures may affect the near-end infrastructure paths

Outage localization is more complicated!

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Outage localization is more complicated!

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Time

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Outage localization is more complicated!

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Time

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Outage localization is more complicated!

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Outage in Facility 2 causes drop in the paths of Facility 4!

Time

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Outage localization is more complicated!

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Time

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Outage localization is more complicated!

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Outage in Facility 3 causes drop in the paths of Facility 4!

Time

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Outage source disambiguation and localization

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  • Create high-resolution co-location maps:

○ AS to Facilities, AS to IXPs, IXPs to Facilities ○ Sources: PeeringDB, DataCenterMap, operator websites

  • Decorrelate the behaviour of affected ASes based on their

infrastructure colocation.

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Outage localization is more complicated!

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Far-end ASes colocated in Facility 2

Time

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Outage localization is more complicated!

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Far-end ASes colocated in Facility 3

Time

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Outage source disambiguation and localization

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Paths not investigated in aggregated manner, but at the granularity of separate (AS, Facility) co-locations.

London Telecity HE8/9 outage London Telehouse North outage

Time

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Outage source disambiguation and localization

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London Telecity HE8/9 outage London Telehouse North outage London Telecity HE8/9 outage London Telehouse North outage

Paths not investigated in aggregated manner, but at the granularity of separate (AS, Facility) co-locations.

Time

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Detecting peering infrastructure outages in the wild

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  • 159 outages in 5 years of BGP data

○ 76% of the outages not reported in popular mailing lists/websites

  • Validation through status reports, direct feedback, social media

○ 90% accuracy, 93% precision (for trackable PoPs)

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Effect of outages on Service Level Agreements

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~70% of failed facilities below 99.999% uptime ~50% of failed IXPs below 99.99% uptime 5% of failed infrastructures below 99.9% uptime!

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Measuring the impact of outages

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> 56 % of the affected links in different country, > 20% in different continent! Median RTT rises by > 100 ms for rerouted paths during AMS-IX

  • utage.

Number of affected links (log)

105 103 101

CDF

1.0 0.4 0.2 0.6 0.8 0.44

Distance from outage source (km)

12K 8K 10K 6K 4K 2K

Fraction of paths RTT (ms)

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Conclusions

  • Timely and accurate infrastructure-level outage detection through

passive BGP monitoring

  • Majority of outages not (widely) reported
  • Remote peering and infrastructure interdependencies amplify the

impact of local incidents

  • Hard evidence on outages can improve accountability,

transparency and resilience strategies

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Thank you!

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