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Inter-Domain Traffic

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Title: Inter-Domain Traffic Engineering Author: Josh Wepman and Joe Abley Last modified by: Joe Abley Created Date: 1/28/2002 2:36:16 AM Document presentation format – PowerPoint PPT presentation

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Title: Inter-Domain Traffic


1
Inter-Domain Traffic Engineering
Principles, Applications and Case Studies
2
Who We Are
  • Josh Wepman
  • Applications Engineer/Snake Oil Salesman
  • Ixia NetOps
  • jaw_at_ixiacom.com
  • Joe Abley
  • Toolmaker/Engineer/Token Canadian
  • MFN PAIX
  • jabley_at_mfnx.net

3
What We Are Talking About
  • Inter-domain Measurement, Analysis and Control
  • Improving Connectivity
  • With whom?
  • Where?
  • At what speed?

4
What we are NOT talking about
  • MPLS
  • DiffServ
  • RSVP
  • CR-LDP
  • All sorts of other words with lots of capital
    letters that have become associated with traffic
    engineering

5
Goals For The Afternoon
  • Methods and Concepts on how to "improve"
    inter-domain connectivity
  • Depending on who YOU are, "improve" will have
    different meanings
  • Finding ways to reduce impact of failure in peer
    or transit networks
  • a.k.a. "increasing reliability
  • WARNING Some operational complexity may arise!
  • Put on your peril-sensitive glasses...

6
Presentation Outline
  • Inter-Domain TE Goals Definition
  • Inter-domain TE Measurement
  • Applying Data to Address Your Goals
  • Eliciting Control and the Feedback-Loop
  • Conceptual Examples
  • Who is Doing This Stuff?
  • Real_Live_Network Examples
  • No Questions? Good!

7
Inter-Domain TE Goals Definition
  • Iteration-1 Conceptual
  • Define Goals, Measure, Analyze, Refine Goals,
    Action
  • What is it you need to accomplish?

8
Examples of Goals
  • Need to offload my "NSFnet" peering links
    outbound (congestion management)
  • Need to expand my inter-domain peering links
    cluefully (growth)
  • Need to find some people to provide my services
    to (sales)
  • That's right, I said itsell stuff!!!

9
Adjusting Your Assumptions
  • Be prepared to adjust your assumptions based on
    measured data!
  • What you planned to do, and what you end up doing
    may change substantially.
  • Do not fear - this is real network data!
  • Clue should increase as valid network data
    becomes available and consulted

10
Data Needs
  • What data sets are required?
  • Flow-export data
  • BGP routing data
  • Active measurement data
  • SNMP
  • Some public tools available (cflowd, zebra, ping,
    scotty, etc)
  • Some commercial products available

11
Inter-domain TE Measurement
  • Also Known As
  • Getting good, problem/goal specific data!

12
Assumed Network Model
  • Hierarchical Network Model
  • Ingress/Egress Network services are separated
    from Transit Services
  • Works in other network models (as we will show),
    but this is what we are focusing on...

13
Hierarchical Network Model
Core Network Services
Core1
Core2
Peer1
Peer2
LocalASN
RemoteASN
AS2
AS3
AS3
AS4
AS9
14
Types of Data to Measure
  • Routing Data
  • Focus here is BGP
  • Traffic Data
  • Flow-export V5 is the focus here
  • Active Measurement Performance Data
  • Ping/Traceroute/One-way delay/Jitter

15
Routing Data
  • Routers generally do this well
  • Core competency by design (Routers route...)
  • Different data sets are available for
    measurement
  • IBGP (Good if you are looking at the whole
    system, looking outbound or using a flat network
    model)
  • Route-Reflection (Often needed for inbound
    analysis, can create some complexity in flat
    netowrk models)
  • EBGP (Good for seeing your neighbor's view of
    you)
  • Choose the right one to measure based on your
    needs/goals

16
Routing Data In/Outbound
Core Network Services
IBGP vs. Route-Reflection
Core1
Core2
Collector
Peer1
Peer2
Data
LocalASN
RemoteASN
AS2
AS3
AS3
AS4
Routes
AS9
17
Routing Data In/Outbound
  • When your goal is outbound characterization, and
    your measurement point is the exit point for
    traffic, IBGP is your guy/girl/other.
  • Routes are always external, and thus always
    propagated (sans election and policy of course)
  • Protocols hate being anthropomorphized
  • When your goal is inbound characterization, and
    your measurement point is the entry point for
    traffic, Route-Reflection must be used.
  • Only way to get internal routes cleanly

18
Route Data Full Mesh (tangent)
  • Value of full mesh monitoring
  • Historical route tracking
  • Policy benchmarking
  • Tracking med-selection issue
  • Identifying disasters the FIRST time cluefully
  • Dont just wait for it to happen again!
  • PLEASE! For everyones sake!
  • Slightly off topic, but pretty darn important!

19
Route Data Full Mesh (pic)
Core1
Core2
Core2
Core1
Core1
Core2
Collector
Core2
Core1
Core1
Core2
Core2
Core1
20
Traffic Accounting Data
  • Also Known As
  • Flow-export
  • NetFlow
  • Cflow
  • A MAJOR pain in the AS!

21
The Quick Skinny on Flow
  • Packet and Byte counters per unique set of
    traffic attributes
  • Measured from strategic routers per input
    interface
  • Which interfaces depends on your defined
    goals/needs...
  • Come a long way in the last few years
  • In some respects ?

22
Flow Data Inbound - Easy
Core Network Services
Core1
Core2
Collector
Peer1
Peer2
Data
LocalASN
RemoteASN
AS2
AS3
AS3
AS4
Routes
AS9
23
Flow Data Outbound - Easy
Core Network Services
Core1
Core2
Collector
Peer1
Peer2
Data
LocalASN
RemoteASN
AS2
AS3
AS3
AS4
Routes
AS9
24
Flow Data Outbound - Harder
AS2
AS4
Core
Core
AS6
Core
Core
Core
AS3
25
Flow Data Outbound - Harder
  • Since flow-export data is inbound only, all
    potential feeder links in a non-hierarchical,
    mixed services device must be accounted for in
    order to catch all traffic outbound
  • Issue How do you know what data coming in core
    link4 is bound for the local external link? Route
    Reflection is bad here! Can double-count!
  • Problem exacerbated by complex policy

26
18 Words or less on flow data
  • Micro-management of networks based on flows
    BAD
  • Macro-management of networks based on flows
    GOOD

27
Operational Challenges (1)
  • Keep this in mind!
  • Gilbs Law
  • Anything can be measured in a way that is
    superior to not measuring it at all.

28
Operational Challenges (2)
  • ACLs vs. data-export in the great beast!
  • Sampled NetFlow on the GSR is usually distributed
    to the LCs
  • ACL gt SNF gt PIRC gt IP Coloring gt BGP Policy
    accounting gt FR Traffic policing which is not FR
    traffic shaping
  • Apparently this changes in 12.0(18)S

29
Operational Challenges (3)
  • Some releases of JUNOS have bugs where only flow
    data from the highest-numbered ifIndex gets
    exported
  • Check for PR20159

30
Operational Challenges (4)
  • On high-speed interfaces, the best you can
    realistically do is sample at some ratio lt 11
  • If you need to count bytes, this will introduce
    errors
  • If you need to compare samples, make sure the
    samples are normalized
  • This does NOT mean multiply by interval!
  • Lack of current research on statistical validity
    of flow data based on samples
  • Last research circa 1993
  • Research predates substantial HTTP traffic

31
Operational Challenges (5)
  • The Gilb-Wepman Construct
  • The total P.I.T.A. factor experienced through
    the process of network measurement is far less
    than the total P.I.T.A factor experienced through
    planning and engineering a network without
    network measurements.
  • P.I.T.A Pain In The Ass
  • those without customers may be unfamiliar with
    this term

32
Performance Data
  • Active measurement
  • Round-trip vs. one-way
  • mrtg and link utilization
  • Important, but not part of our examples
  • Short on time sadly
  • Helps in goal selection and re-selection
  • Bottom line is it better or worse?

33
Applying Data to your Goals
  • What to do with all this data?
  • Traffic Accounting Data applied to Routing data?
  • Traffic Load per ltsomethinggt
  • attribute or route
  • The focus here is on traffic stats (byte and
    packet rates) per AS-PATH

34
AS-PATH / Traffic-data tables
  • Traffic load per AS-PATH creates a tree of
    traffic relationships
  • (101) X-bits/sec
  • (101,1234) Y-bits/sec
  • (101,1234,9995) Z-bits/sec
  • 101 -gt 1234 -gt 9995
  • XYZ -gt YZ -gt Z
  • Addresses the middle mile ASs instead of
    traditional first or last ASN.
  • Allows "TO (source/sink) and "THROUGH (transit)
    values instead of just "TO" values.

35
Data Aggregation - Time
  • Aggregate data over timeframes (macro-level view)
  • Long term averages
  • Short term benchmarks
  • Of course, short term means long term.
  • Micro-management of networks based on flows
  • BAD!

36
Data Aggregation - Interfaces
  • Aggregate across the set of interfaces that
    represent your problem statement
  • What interfaces am I interested in?
  • Can be interface specific (one)
  • Can be router specific (many)
  • Can be domain wide (all)
  • Can be N of M interfaces (some)
  • Pretty common

37
What to do with all this?
  • What does one do once they have all this data?

38
Eliciting Control and The Feedback Loop
  • Sit down, Josh
  • Begone with your Snake Oil
  • Its time to beat on some routers

39
Assumptions about your Routing Architecture
  • Routes to external networks are in BGP
  • Your IGP tells you how to find the NEXT_HOP
    addresses in BGP
  • We select exit points for traffic based on BGP
    path selection, not some other weird thing
  • If your routing policy differs significantly from
    this, you have more problems than measurement can
    solve

40
Fixing Outbound Traffic
  • Mark policy on BGP routes at the place where you
    learn them
  • General policy -- prefer peering links over
    expensive transit links, prefer private peering
    links over public peering links
  • Specific policy -- temporarily avoid NAP X for
    traffic to AS Y, prefer AS C to reach remote
    network D

41
Tweakable Knobs
  • LOCAL_PREF
  • MED
  • AS_PATH
  • Check your vendors BGP path selection tiebreaker
    list, and chose a set of knobs that gives you the
    kind of control your policy dictates

42
Control of Outbound Traffic
  • Danger, Will Robinson!
  • Helpdesk phone may ring
  • Small change, pause, check, log, pause, breathe,
    repeat
  • Exit selection is a reasonably precise science

43
Fixing Inbound Traffic
  • Controlling inbound traffic flow is all about
    trying to influence the BGP path selection
    decisions which happens in networks you dont
    control
  • Some of those networks you pay money to. Money is
    sometimes an appropriate weapon
  • Its nice to buy people drinks at NANOG

44
Tweakable Knobs
  • Provider-specific knobs
  • whois -h whois.ra.net as1755
  • CIDR abuse
  • Cheap trick
  • Longest prefix wins
  • AS_PATH stuffing
  • AS_PATH pollution
  • Another cheap trick

45
Responsible Citizenship
  • Some tweakable knobs have an unwelcome impact on
    the networks of others
  • Have you met my friend, MED?
  • Your relationship with your target networks is
    symbiotic
  • It is inappropriate to make demands of someone
    elses routing policy, but asking nicely is OK

46
Conceptual Examples (1)
  • Who are the top consumers of my network
    resources?
  • Top sources of traffic
  • Top sinks of traffic
  • Asymmetry

47
Conceptual Examples (2)
  • Traffic Aggregation Points and Peering
    Optimisation
  • Appropriate network expansion
  • Offloading the expensive peer
  • Mitigating settlement fees and traffic ratios
  • Mitigating congestion
  • Do it without MED selection issues
  • Maximize route availibility (Ngt1 copies, not 1 or
    0)

48
Conceptual Examples (3)
  • Theft-over-IP (how to know when peers are
    stealing from you)
  • Peers dumping traffic at you for routes you
    didnt send them
  • Rather rude
  • Catch them in the act

49
Who is doing this stuff?
  • Yahoo! - Jeffrey Papen (TUNDRA Tool)
  • Peering Analysis, Capacity Planning, Performance
    Analysis
  • Features
  • Custom macros for AS analysis
  • Source and Destination AS bandwidth details
  • Transit AS (hop counts) bandwidth summary data
  • Bandwidth forecasting peering merit analysis
  • Billing formulas for cost/benefit budget analysis
  • Also
  • Analyze internal usage for Charge Back Billing
  • POP-to-POP Network Performance Analysis (latency
    / loss)
  • DOS attack detection

50
Destination vs. Transit Traffic UUNet (Yahoo
TUNDRA Output)
51
Who is doing this stuff?
  • MFN
  • Lots of people, we think
  • Not enough people, we think

52
Real Live Network Examples 1
  • We peer with a particular large regional ISP in
    several places. Due to various familiar reasons,
    the demands on the peering circuits approach
    supply
  • Who are the top talkers and top listeners that we
    reach via this peer?
  • Maybe we can peer with them directly
  • Not just sinks, but traffic aggregation points
    (middle mile)

53
Network Facts
  • Topology is not pure core/edge in some locations,
    so we might expect some complexities
  • All peering routers happen to be GSR12000s
  • Peering circuits are all OC12
  • Backbone links are mostly OC48

54
Data Collection
  • Relative traffic volumes
  • Low NetFlow sample ratio is OK
  • Turning on ip route-cache flow sampled seems
    like it can cause traffic belches
  • Turn off all inbound ACLs on peering interfaces
  • Turn off all outbound ACLs on peering routers
  • Drink from the Hose
  • Take off every /var

55
Analysis of Data
  • Relative byte count through and to networks
    reached through the peer in question
  • Ranked list of peering candidates
  • Absolute numbers dont really matter we have a
    list of people we should be talking to, in order
    of how useful they would be to peer with

56
SeeASP Output
57
Real Live Network Examples 2
  • AS R wants to peer
  • Thats fine, well public peer with anybody.
    Were easy.
  • AS R wants to private peer right away, since they
    say we send them 140M of traffic already
  • Can we confirm those numbers before we dedicate a
    port to them?

58
Network Facts
  • We currently reach AS R through AS T
  • We peer with AS T in six places
  • One of the peering routers is a 7500, which
    doesnt do SNF
  • One of the peering routers is a router which is
    also being used to collect data to answer the
    previous question

59
More Network Facts
  • Topology is not edge/core everywhere
  • We want numbers out of this, so we need to manage
    the SNF ratios
  • K1dd13s keep attacking the routers
  • Ops folk attack K1dd13s with ACLs
  • The ACL attacks the SNF
  • The SNF dies!

60
Analysis
  • We only have traffic samples, but we want
    absolute numbers
  • We have interface byte and packet counters
  • We can take AS R traffic as a proportion of all
    AS T traffic, and divide up the mrtg/duck data in
    proportion

61
Summary
  • What did we talk about?
  • Answering specific, ad-hoc questions by attacking
    them with numbers
  • Inter-Domain Traffic Engineering is an Iterative
    process (lather, rinse, repeat)
  • What didnt we talk about?
  • Experience exporting from Juniper (and other
    non-cisco) routers
  • Construction of a full-time, general-purpose
    measurement infrastructure
  • What if my vendor does not support flow-export
    and traffic accounting?
  • Questions?
  • No? Good.
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