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Building Hyperscale Networks
​ Zaid Ali Kahn
​ Senior Director, Infrastructure Engineering
Traffic Demands
​  High intra and inter-DC bandwidth demand due to organic growth
​  Every single byte of member activity, creates thousands bytes of east-west traffic inside data center:
​  Application Call Graph
​  Metrics, Analytics and Tracking via Kafka
​  Hadoop and Offline Jobs
​  Machine Learning
​  Data Replications
​  Search and Indexing
​  Ads, recruiting solutions, etc.
2
3
What is invisible software infrastructure?
It is ultra-simple to use
Elastic and scales automatically
No single point of failure
Highly available and self healing
4
LinkedIn Platform as a Service (LPS)
5
Key infrastructure visions
Unlimited bandwidth
Zero latency
Compute on demand
Disaggregation
Programmable datacenter
Self healing
6
Altair flagship design
10,25,50,100G capability to host
Dense compute (96 hosts/rack)
No chassis, single chip switching
200 Gb/s between cabinets
1:1 non blocking parallel fabrics
End to end subscription; < 6:1
Falco fabric based switches
7
Scaling out characteristics
Simple and minimalistic yet non-blocking IP
fabric
Multiple parallel fabrics based on Clos network
architecture
Merchant Silicon with least amount of features
Distributed control plane with some
centralized controls
Wide multi-path (ECMP)
Uniform chipset, bandwidth, and buffering
Low latency and small buffering requirements
8
Kill chassis based devices
9
Introducing parallel fabrics
1:1 oversubscribed (non-blocking fabric)
Use the minimum number of chipsets to carry east–west
traffic
Ability to support 100,000 to 200,000 bare metal servers
without adding an additional layer
Fabric should support up to 64 pods, with each pod
consisting of 32 cabinets and each cabinet, 96 bare
metal dense compute units
Fabric to be limited to three tier switching (5 stage Clos)
for the whole data center to minimize the number of
chipsets, lookups and switching latency.
Support host attachment at 10G, 25G, 50G and 100G
Ethernet
10
Datacenter fabric architecture
11
100G transformation
12
Network Operating System
 “Falco”
OpenFabric Control Plane
1
NOS	
  
Control	
  Plane	
   Distribute	
  Reachability	
  
Centralized	
  Policy	
  
Fast,	
  simple	
  distributed	
  control	
  plane	
  
No	
  tags,	
  bells,	
  or	
  whistles	
  
Auto	
  discover	
  fabric	
  locality	
  
Auto	
  discover	
  neighbors	
  
No	
  configuraCon	
  required	
  
Expresses	
  engineered	
  paths	
  
Expresses	
  filters	
  
Expresses	
  QoS	
  (where	
  needed)	
  
Minimal	
  configuraCon	
  (server	
  informaCon)	
  	
  
Use	
  deployed	
  tools	
  where	
  possible	
  (KaMa)	
  
“Standard”	
  distribuCon	
  
same	
  as	
  servers	
  +	
  packages/tools	
  
Hardware
Routing
Policy
Applications
Link Selection
Topology Discovery and Network Graph
Control
Telemetry/Visibility, Machine Learning, Prediction Engine, Self Healing, etc.
Forwarding
Merchant Silicon
Rethinking The Network Stack
1
Network Element
Management
Plane
SNMP, Syslog, etc.
System &
Environmental
Data
Packet & Flow
Data
Network Operating System
Kafka Network Agent
ASIC Drivers
Management Plane: Reducing Protocols
1
SYSLOG
SNMP
SFLOW
Kafka
16
Programmable datacenter
It is not that we see building our own
switches, servers and
data centers as a core competency,
but rather we see it as a massive
advantage
to control the destiny of our
infrastructure.
17
Building Hyperscale Networks

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Building Hyperscale Networks

  • 1. Building Hyperscale Networks ​ Zaid Ali Kahn ​ Senior Director, Infrastructure Engineering
  • 2. Traffic Demands ​  High intra and inter-DC bandwidth demand due to organic growth ​  Every single byte of member activity, creates thousands bytes of east-west traffic inside data center: ​  Application Call Graph ​  Metrics, Analytics and Tracking via Kafka ​  Hadoop and Offline Jobs ​  Machine Learning ​  Data Replications ​  Search and Indexing ​  Ads, recruiting solutions, etc. 2
  • 3. 3 What is invisible software infrastructure? It is ultra-simple to use Elastic and scales automatically No single point of failure Highly available and self healing
  • 4. 4 LinkedIn Platform as a Service (LPS)
  • 5. 5 Key infrastructure visions Unlimited bandwidth Zero latency Compute on demand Disaggregation Programmable datacenter Self healing
  • 6. 6 Altair flagship design 10,25,50,100G capability to host Dense compute (96 hosts/rack) No chassis, single chip switching 200 Gb/s between cabinets 1:1 non blocking parallel fabrics End to end subscription; < 6:1 Falco fabric based switches
  • 7. 7 Scaling out characteristics Simple and minimalistic yet non-blocking IP fabric Multiple parallel fabrics based on Clos network architecture Merchant Silicon with least amount of features Distributed control plane with some centralized controls Wide multi-path (ECMP) Uniform chipset, bandwidth, and buffering Low latency and small buffering requirements
  • 9. 9 Introducing parallel fabrics 1:1 oversubscribed (non-blocking fabric) Use the minimum number of chipsets to carry east–west traffic Ability to support 100,000 to 200,000 bare metal servers without adding an additional layer Fabric should support up to 64 pods, with each pod consisting of 32 cabinets and each cabinet, 96 bare metal dense compute units Fabric to be limited to three tier switching (5 stage Clos) for the whole data center to minimize the number of chipsets, lookups and switching latency. Support host attachment at 10G, 25G, 50G and 100G Ethernet
  • 13. OpenFabric Control Plane 1 NOS   Control  Plane   Distribute  Reachability   Centralized  Policy   Fast,  simple  distributed  control  plane   No  tags,  bells,  or  whistles   Auto  discover  fabric  locality   Auto  discover  neighbors   No  configuraCon  required   Expresses  engineered  paths   Expresses  filters   Expresses  QoS  (where  needed)   Minimal  configuraCon  (server  informaCon)     Use  deployed  tools  where  possible  (KaMa)   “Standard”  distribuCon   same  as  servers  +  packages/tools  
  • 14. Hardware Routing Policy Applications Link Selection Topology Discovery and Network Graph Control Telemetry/Visibility, Machine Learning, Prediction Engine, Self Healing, etc. Forwarding Merchant Silicon Rethinking The Network Stack 1
  • 15. Network Element Management Plane SNMP, Syslog, etc. System & Environmental Data Packet & Flow Data Network Operating System Kafka Network Agent ASIC Drivers Management Plane: Reducing Protocols 1 SYSLOG SNMP SFLOW Kafka
  • 17. It is not that we see building our own switches, servers and data centers as a core competency, but rather we see it as a massive advantage to control the destiny of our infrastructure. 17