1. Monitoring 10Gbps and beyond
Les Cottrell,
LHC Tier0, Tier1 Network meeting, CERN July 2005
What we need to know is to understand how to monitor an optical private network, what are the best approaches and what should we watch out for. Ideally, how should it be implemented in order to be manageable.
Partially funded by DOE/MICS for Internet End-to-end Performance Monitoring (IEPM)

2. Outline Why do we need monitoring? Active E2E measurements Passive
Netflow,
SNMP,
Packet capture
Conclusions
Main focus on E2E, little emphasis on layer 1.

3. Uses of Measurements
Automated problem identification & trouble shooting:
Alerts for network administrators, e.g.
Bandwidth changes in time-series, iperf, SNMP
Alerts for systems people
OS/Host metrics
Forecasts for Grid Middleware, e.g. replica manager, data placement
Engineering, planning, SLA (set & verify)
Security: spot anomalies, intrusion detection
Accounting

4. Active E2E Monitoring
Layer 3 or 4. Layers 1 and 2 are less well exploited/understood/related to apps. Also lots of instances: FC, FICON, 10GE, SONET, OC192, SDH …
Check vendor specs. E.g. Cisco, Juniper etc.
SONET monitoring (from Endace):
The PHYMON occupies 1U (OC3/12) or 2U (OC48/192) of vertical rack space and is equipped with two 10/100/1000 copper Ethernet interfaces for control and reporting via LAN.
Key Features
Monitors up to two OC3/OC12/OC48/OC192 network links Detects link-layer failures: LOS-S, LOF-S, AIS-L, REI-L, RDI-L, AIS-P, LOP_P, UNEQ-P, REI-P, RDI-P Derive errors: CV, ES, ESA, ESB, SES and UAS according to Bellcore GR-253, Issue 2 Rev 2 standard Sends SNMP traps for all failures and error thresholds according to user configuration Reports current status in real time via telnet, ssh or serial connection Reports accumulated status for 15m, 1h, 8h, 24h, 7d intervals Retains historical data for 35 days Supplies all the underlying data for SNMP SONET MIB (RFC2558)
Techniques:
Loop back, test patterns (BERT), e.g. ones & zeroes, various ITU-T specs, Loss of Signal, out of Frame, loss of frame, errored seconds, code violations, unavailable seconds, alarms, near & far end, how often, history

5. Using Active IEPM-BW measurements
Focus on high performance for a few hosts needing to send data to a small number of collaborator sites, e.g. HEP tiered model
Makes regular measurements
Ping (RTT, connectivity), traceroute
pathchirp, ABwE (packet pair dispersion)
iperf (single & multi-stream), thrulay,
Bbftp (file transfer application)
Looking at GridFTP but complex requiring renewing certificates
Lots of analysis and visualization
Running at CERN, SLAC, FNAL, BNL, Caltech to about 40 remote sites

6. Ping/traceroute Ping still useful (plus ca reste …) OWAMP similar
Is path connected?
RTT, loss, jitter
Blocking unlikely
OWAMP similar
But needs server installed at other end
Traceroute
Little use for dedicated λ
However still want to know topology of paths

7. Packet Pair Dispersion
Bottleneck
Min spacing
At bottleneck
Spacing preserved
On higher speed links
Send packets with known separation
See how separation changes due to bottleneck
Can be low network intrusive, e.g. ABwE only 20 packets/direction, also fast < 1 sec
From PAM paper, pathchirp more accurate than ABwE, but
Ten times as long (10s vs 1s)
More network traffic (~factor of 10)
Pathload factor of 10 again more
IEPM-BW now supports ABwE, Pathchirp, Pathload

8. BUT…
Packet pair dispersion relies on accurate timing of inter packet separation
At > 1Gbps this is getting beyond resolution of Unix clocks
AND 10GE NICs are offloading function
Coalescing interrupts, Large Send & Receive Offload, TOE
Need to work with TOE vendors
Turn off offload (Neterion supports multiple channels, can eliminate offload to get more accurate timing in host)
Do timing in NICs
No standards for interfaces

9. Achievable Throughput
Use TCP or UDP to end as much data as can memory to memory from source to destination
Tools iperf, netperf, thrulay
Bbcp and GridFTP have memory to memory mode

10. Iperf vs thrulay Iperf has multi streams
Maximum RTT
Iperf has multi streams
Thrulay more manageable & gives RTT
They agree well
Throughput ~ 1/avg(RTT)
Average RTT
RTT ms
Minimum RTT
Achievable throughput Mbits/s

11. Forecasting Over-provisioned paths should be pretty flat time series
Short/local term smoothing
Long term linear trends
Seasonal smoothing
But seasonal trends (diurnal, weekly need to be accounted for)
Use Holt-Winters triple exponential weighted moving averages
Predicting how long a file transfer will take, requires forecasting network and application performance. However, such forecasting is beset with problems. These include seasonal (e.g. diurnal) variations in the measurements, the increasing difficulty of making accurate active low network intrusiveness measurements especially on high speed (>1 Gbits/s) networks and with Network Interface Card (NIC) offloading, the intrusivenss of making more realistic active measurements on the network, the differences in network and large file transfer performance, and the difficulty of getting sufficient relevant passive measurements to enable forecasting. We will discuss each of these problems, compare and contrast the effectiveness of various solutions, look at how some of the methods may be combined, and identify practical ways to move forward.

12. BUT…
At 10Gbits/s on transatlantic path Slow start takes over 6 seconds
To get 90% of measurement in congestion avoidance need to measure for 1 minute (5.25 GBytes at 7Gbits/s (today’s typical performance)
Needs scheduling to scale, even then …
It’s not disk-to-disk
So use bbcp, bbftp, or GridFTP

13. Passive - Netflow

14. Netflow et. al. Switch identifies flow by sce/dst ports, protocol
Cuts record for each flow:
Sce, dst, ports, protocol, TOS, start, end time
Collect records and analyze
Can be a lot of data to collect each day, needs lot cpu
Hundreds of Mbytes to GBytes
No intrusion, real traffic, real collaborators
No accounts/pwds/certs/keys
Characterize traffic: top talkers, applications, flow lengths etc.
Internet 2 backbone
SLAC:
NetraMet, SCAMPI are a couple of non-commercial flow projects. IPFIX is an IETF standardization effort for Netflow type passive monitoring.

15. Top talkers by application/port
Hostname 1
100
10000
Volume dominated by single
Application - bbcp
MBytes/day (log scale)

16. Flow sizes SNMP Real A/V AFS file server
60% of TCP flows less than 1 second
Would expect TCP streams longer lived
But 60% of UDP flows over 10 seconds, maybe due to heavy use of AFS
Heavy tailed, in ~ out, UDP flows shorter than TCP, packet~bytes
75% TCP-in < 5kBytes, 75% TCP-out < 1.5kBytes (<10pkts)
UDP 80% < 600Bytes (75% < 3 pkts), ~10 * more TCP than UDP
Top UDP = AFS (>55%), Real(~25%), SNMP(~1.4%)

17. Forecasting? Use Netflow records at border
Collect records for several weeks
Filter 40 major collaborator sites, big (> 100KBytes) flows, bulk transport apps/ports (bbcp, bbftp, iperf, thrulay …)
Divide by remote site, add parallel streams
Fold data onto one week, see bands at known capacities and RTTs
~ 500K flows

18. Netflow et. al. Peaks at known capacities and RTTs
RTTs suggest windows not optimized

19. How many sites have enough flows?
In May ’05 found 15 sites with > 1440 (1/30 mins) flows
Enough for time series forecasting for seasonal effects
Three sites (Caltech, BNL, CERN) were actively monitored
Rest were “free”
Only 10% sites have big seasonal effects
Remainder need fewer flows
So promising

20. Compare active with passive
Predict flow throughputs from Netflow data for SLAC to Padova for May ’05
Compare with E2E active ABwE measurements

21. Netflow limitations Use of dynamic ports.
GridFTP, bbcp, bbftp can use fixed ports
P2P often uses dynamic ports
Discriminate type of flow based on headers (not relying on ports)
Types: bulk data, interactive …
Discriminators: inter-arrival time, length of flow, packet length, volume of flow
Use machine learning/neural nets to cluster flows
E.g.
SCAMPI/FFPF/MAPI allows more flexible flow definition
See
Use application logs (OK if small number)
For FTP port 21 only used as a control channel.

22. Passive SNMP MIBs

23. Apply forecasts to Network device utilizations to find bottlenecks
Get measurements from Internet2/ESnet/Geant SONAR project
ISP reads MIBs saves in RRD database
Make RRD info available via web services
Save as time series, forecast for each interface
For given path and duration forecast most probable bottlenecks
Use MPLS to apply QoS at bottlenecks (rather than for the entire path) for selected applications
NSF proposal
SONET monitoring (from Endace):
The PHYMON occupies 1U (OC3/12) or 2U (OC48/192) of vertical rack space and is equipped with two 10/100/1000 copper Ethernet interfaces for control and reporting via LAN.
Key Features
Monitors up to two OC3/OC12/OC48/OC192 network links Detects link-layer failures: LOS-S, LOF-S, AIS-L, REI-L, RDI-L, AIS-P, LOP_P, UNEQ-P, REI-P, RDI-P Derive errors: CV, ES, ESA, ESB, SES and UAS according to Bellcore GR-253, Issue 2 Rev 2 standard Sends SNMP traps for all failures and error thresholds according to user configuration Reports current status in real time via telnet, ssh or serial connection Reports accumulated status for 15m, 1h, 8h, 24h, 7d intervals Retains historical data for 35 days Supplies all the underlying data for SNMP SONET MIB (RFC2558)

24. Passive – Packet capture

25. 10G Passive capture
Endace ( ): OC192 Network Measurement Cards = DAG 6 (offload vs NIC)
Commercial OC192Mon, non-commercial SCAMPI
Line rate, capture up to >~ 1Gbps
Expensive, massive data capture (e.g. PB/week) tap insertion
D.I.Y. with NICs instead of NMC DAGs
Need PCI-E or PCI-2DDR, powerful multi CPU host
Apply sampling
See
Also have tcpdump/libpcap to capture
CoralReef captures and analyzes packets
NetraMet/Flowscan, latter analyzes and reports
MAPI/FFPF with Intel IXP1200, plus LOBSTER
Endace Key features
Endace DAGMON 3U rackmount server system Pair of Single Channel DAG6.2SE OC192c Network Measurement Cards CPU, memory and disks according to configuration options Linux and DAG device drivers preinstalled, FreeBSD available Conditioned clock with 1PPS input and local synchronization capability Captures up to 1.064GBps of network traffic
Applications
Network monitoring systems Traffic characterization and delay measurement Packet header capture Network delay measurements Network security applications, such as Intrusion Detection Systems
DAG card capable of full-packet capture, uses zero copy (shared memory, reduces interrupts), has high precision time stamp, large static circular buffer
DAGs expensive (list for 10GE NMC ~ $50K)
Intel Pro 1GE NIC in dual 1.8GHz AMD 700Mbits/s ~ 50 loss free flows can be captured with libpcap
Over DAG ~ 100

26. LambdaMon / Joerg Micheel NLANR
Tap G709 signals in DWDM equipment
Filter required wavelength
Can monitor multiple λ‘s sequentially
2 tunable filters

27. LambdaMon Place at PoP, add switch to monitor many fibers
More cost effective
Multiple G.709 transponders for 10G
Low level signals, amplification expensive
Even more costly, funding/loans ended …

28. Conclusions Traceroute probably dead Some things continue to work
Ping, owamp
Iperf, thrulay, bbftp … but
Packet pair dispersion needs work, its time may be over
Passive looks promising with Netflow
SNMP needs AS to make accessible
Capture expensive
~$100K (Joerg Micheel) for OC192Mon

29. More information Comparisons of Active Infrastructures:
Some active public measurement infrastructures:
www-iepm.slac.stanford.edu/
e2epi.internet2.edu/owamp/
amp.nlanr.net/
www-iepm.slac.stanford.edu/pinger/
Capture
(DAG),
(also MAPI, FFPF),
Monitoring tools