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Hanoch Haim – Principal Engineer
- Overview
- Stateless
- Advance Stateful
Agenda
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Realistic Traffic Generator Hanoch Haim Principal Engineer Agenda - - PowerPoint PPT Presentation
Realistic Traffic Generator Hanoch Haim Principal Engineer Agenda - - PowerPoint PPT Presentation
Realistic Traffic Generator Hanoch Haim Principal Engineer Agenda Overview Stateless Advance Stateful 2 TRex Results Open Source Cisco Customers 3 TRex Usa sage ge Ana nalyti ytics cs mont nthl hly y repo
SLIDE 2
SLIDE 3
TRex – Results
- Open Source
- Cisco Customers
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TRex Usa sage ge Ana nalyti ytics cs mont nthl hly y repo port t (*)
(**) Users are distinct (*) ~1200 0 distinct return rnin ing users,
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SLIDE 5
TRex models of operation
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- L7, DUT terminate
TCP/SSL, flow based
- DUT inspect L7.
does not change
- TCP. Flow based
- DUT L2/L3 Switch ,
packet based
SLIDE 6
What Problem is Being Solved?
- Networks include complex L4-7 features, such as
- Load Balancer, DPI/AVC, Firewall, NAT
- Requires testing with stateful and realistic traffic mix
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Firewall, NAT DPI/AVC LB
SLIDE 7
What Problem is Being Solved?
- Traffic generators for realistic traffic are
- Expensive ~$100-500K
- Not scalable for high rates
- Not flexible
- Implication
- Limited and late testing
- Different benchmarks and test methodologies
- Real life bottlenecks and design issues
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SLIDE 8
What is TRex?
- Linux user-space application uses DPDK library
- Stateless
ss: Stream based uses Scapy
- Stateful: flow based
Generates, manipulates and amplifies based on templates of real, captured flows (W/O TCP stack)
- High perform
- rmance
ance: up to 200 Gb/sec
- Low cost: Standard server hardware
- Flexible and Open Software
- Virtualization
- Easy installation and deployment
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Stateless
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Stateless High level functionality
- High scale – ~10M-35MPPS/core
- Profile can support multiple streams, scalable to 20K parallel streams
- Interactive support – GUI/TUI
- Statistic per port/ stream (e.g. latency/ Jitter)
- Python automation support
- Multi-user support
- Capture to Wireshark
- Scalable services using plugins (e.g. DHCP,IPv6)
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Traffic Profile Example
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Control plane High level
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One stream with two directions
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Python Automation example
SLIDE 16
link
Performance XL710 MPPS/Core
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Advanced Stateful
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Use ser sp space ce TCP P st stack ck
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TRex ASTF fe feature ures
- High scale
- TCP is the core component
- Can be tuned MSS/initwnd/delay-ack
- TCP is based on BSD with acceleration
- Interactive
- Accurate latency measurement – usec
- Simulation of latency/jitter/drop in high rate
- OpenSSL integration
- L7 emulation layer
- Emulate application using “micro-instructions”
- Field engine
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L7 7 Emul ulati tion n layer er
Client side Server side
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HTTP P si simpl ple pr profi file le
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Client ent si side de ps pseud udo co code de
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Server r si side de ps pseud udo co code de
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Pr Profi file e with h two templ plat ate
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Statis isti tic c
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Und nder the he ho hood
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TCP P st stack ck – Flow Sca cale -TX TX
10M flows 320GByte 320M mbuf =10GB
0.01GB
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TCP P st stack ck – Flow Sca cale iss ssue ue - RX RX
10M flows 320GByte 3-50GB for 1%
drop rate
0.01GB
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SLIDE 29
TCP sta tack k – Delay/Ji /Jitte tter/ r/Dro Drop sim imulat ation ion
100MPPS *100msec =10MPPS in Queue 100MPPS *100msec =10*16MPPS=0.16G B
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SLIDE 30
TRex vs NGINX
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SLIDE 31
Performance setup #2
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SLIDE 32
Performance numbers
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https://trex-tgn.cisco.com/trex/doc/trex_astf_vs_nginx.html
x80 faster x2000 less memory