Transcript OpenFlow Switch

GENI and InstaGENI:
An Architecture for the
Intercloud
Rick McGeer
HP Labs
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Outline
The Need for an Intercloud Architecture
The GENI Initiative: from Testbed to Architecture
The ProtoGENI MetaCloud
The InstaGENI Distributed Cloud
The InstaGENI Rack: The Apple-II of Clouds
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The World is Closing In On Us
Big Data dominates both scientific and social computing
Astronomical Imagery
Collider events
Genomic data
Environmental Sensing (e.g., CASA networked weather radar)
Large social graphs (1012 nodes and beyond)
Getting rid of the clusters-in-the-basement
Consolidation into the “condo-of-condos”
New demands on the network…
Disaster Response, social media,….
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Mixing the Operational and Advanced Networks
New network requirements mean new network demands
Big data, high QoS on operational network
SLAs for “condo of condos”
Movement of Big Data
Across campus networks
Between campuses
Between campus and sensor sites
Programmability at network collection site
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Solution
Compute where the data is
Ubiquitous computation
Cloud that can be instantiated anywhere
Advanced Networking to move the data to where the compute is
Customizable virtual networks
Layer-2 end-to-end
QoS guarantees
Programmable networking
Custom, app-specific protocols
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But it can’t compete with Production Traffic
Right
Solution: customizable virtual networks
Isolation at the level of a flow
Guaranteed network properties: virtual network per flow
Offers the prospect of
Routing
Bandwidth Limits
On a per-flow basis
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HP, Internet2, GENI, US-Ignite – Working to Advance
Internet Technology for Research & Local Communities
Internet2
HP
Advanced network
infrastructure
GENI
HP InstaGENI rack – GENI
cluster deployment in-abox, ready out of the box
Next-gen network apps
for public benefit
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Collaborative platform to
build the next-gen Internet
US-Ignite
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GENI
Ubiquitous cloud with deeply-programmable networking
Ubiquitous Cloud
Abstracted API that can be implemented by any popular cluster manager (Slice Federation
Architecture)
Designed for federation
Certificate-based access control (No need for single sign-on, common AUP)
Implementations with fine and deep control of resources (ProtoGENI)
Deeply Programmable Network
Open Flow native
Layer 2 backbone
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GENI
Each facility implements Slice-Based Federation
Interface
Standard, unified means of allocating
Virtual machines at each layer of the stack (“slivers”)
Networks/sets of virtual machines (“slices”)
Already supported by PlanetLab, ORCA, ProtoGENI
Now supported by Eucalyptus and OpenStack (our
contribution)
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GENI Mesoscale
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GENI Mesoscale Deployment
Putting the backbone in GENI
47 sites with GENI racks
33 InstaGENI racks
14 ExoGENI racks
Fully Interoperable
Interoperable with existing GENI aggregates
Extensible to new campuses
OpenFlow-enabled Layer 2 connectivity between campuses
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GENI And NSFNet: Back to the Future
GENI today is NSFNet circa 1985
GENI and the SFA: Set of standards (e.g., TCP/IP)
Mesoscale: Equivalent to NSF Backbone
InstaGENI: Hardware/software instantiation of standards that sites can
deploy instantly
Equivalent to VAX 11 running Berkeley Unix
InstaGENI cluster running ProtoGENI and OpenFlow
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What About IGNITE?
Application suite
Analog here is to the Web, and web applications
In other words, no one can predict this
Did you predict Google?
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Foundational Technologies
Software-defined networking
OpenFlow
Highly-Flexible Clouds
MetaCloud (ProtoGENI)
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Traditional Switch
Apps
Apps
Management
Control Plane
Data Plane
•Traditional switches integrate
control plane (policy) and data
plane (forwarding)
•Only way to introduce new apps
is to integrate with switch
•Slow, expensive
•Sole knob is configuration
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OpenFlow approach: Factor control plane to offswitch controller SW •Off-switch controller offers programmability, visitbility
Apps
Apps
Management
Control Plane
•Off-switch controller offers programmability of whole
network simultaneously
•can directly manage global properties without
multiple layers
•Enforces isolation by manipulating FIB on control
plane stubs
Control Plane Stub
Management SW
Data Plane
Simplified switch
Control Plane Stub
Data Plane
Simplified switch
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Control Plane Stub
Data Plane
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Simplified switch
OpenFlow Basics
Flow Table Entries
Rule
Action
Stats
Packet + byte counters
1.
2.
3.
4.
5.
Switch VLAN
Port
ID
Forward packet to port(s)
Encapsulate and forward to controller
Drop packet
Send to normal processing pipeline
Modify Fields
MAC
src
MAC
dst
Eth
type
IP
Src
IP
Dst
+ mask what fields to match
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IP
Prot
TCP
sport
TCP
dport
OpenFlow Usage
Dedicated OpenFlow Network
OpenFlow
Rule
Action
Switch
Controller
Aaron’s code
PC
Statistics
OpenFlow
Protocol
OpenFlow
Rule
Action
Switch
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Statistics
RuleOpenFlow
Action
Statistics
Switch
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OpenFlowSwitch.org
HP is The OpenFlow Technology Leader
HP & Stanford
collaborate on
Ethane
HP demos
OpenFlow-enabled
switch
Growth in
Customer
Deployments
HP helps establish
InCNTRE
HP will extend OpenFlow
across the FlexNetwork
architecture
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40
20
10
2007
2008
HP Labs forms
OpenFlow research
team
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2009
HP early-release
OpenFlow software
to researchers
2010
2011
HP is founding
member of ONF
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2012
2013
HP makes
OpenFlow software
generally available
HP Labs Contributions to OpenFlow
•OpenFlow
•
QoS controller
ToS support, priority queuing, rate limiters
•Improved Support for research multi-pathing solutions:
–SPAIN (Smart Path Assignment In Networks / NSDI 2010)
–HBR (Hash-Based Routing / ICC 2010, ANCS 2010)
•Improved Deployment Scalability
–DevoFlow (SIGCOMM 2011)
–TCAM Synthesis (INFOCOMM 2009)
•Verification of OpenFlow Networks (SDN 2012)
•OpenFlow™ deployment
–Defined GENI deployment strategy with Stanford Univ
–OpenFlow™ deployment testing with Stanford Univ
–Contributions to OpenFlow™ test suite
–OpenvSwitch contributions
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HP Labs OpenFlow Research (sample)
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•
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“DevoFlow: Cost-Effective Flow Management for High Performance
Enterprise Networks,”, HotNets, October 2010, SIGCOMM 2011
“Network Integrated Transparent TCP Accelerator,” AINA, April 2010
"ElasticTree: Saving Energy in Datacenter Networks,” NSDI,
April 2010
"Automated and Scalable QoS Control for Network Convergence,"
WREN/INM 2010 Workshop, held in conjunction with NSDI, April
2010.
“API Design Challenges for Open Router Platforms on Proprietary
Hardware,” HotNets, October 2008
“Verification of Switching Network Properties Using
Satisfiability”, SDN, 2012
“A Safe Update Protocol for OpenFlow Networks”, HOT SDN,
2012
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OpenFlow/SDN: A New Way to Build & Manage
Networks
•Enables
a scalable control plane to
deliver
virtual service networks
Rapid, service-oriented provisioning
 Fine-grain policy control, integrated security
 Service-focused monitoring

•
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Use models across service provider,
data center, campus, and branch
networks
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The MetaCloud (ProtoGENI)
Multiple Cloud Infrastructures offering different services and interfaces
Hardware as a service
VM’s as a Service
Containers as a service
Threads as a service
MapReduce as a service
Platform as a service
Multiple tools and interfaces
Nova, euca2ools, Keystone,…
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Problem
Different users want different clouds!
Varying behavior of various platforms
Different toolsets to create, manipulate, manage virtual resources
Much of code base replicated
All systems involve allocation of physical resources
All systems require image store, image load, persistent store…
All systems allocate x86 nodes…
Problems
Currently, cloud systems persistent across hardware base (can’t reuse hardware base
between different cloud managers)
Have to rebuild common functionality to do new managers
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Solution: MetaCloud
Underlying API that supports cluster/cloud managers
Hardware as a Service
Resource Allocation and Specification API
Underlying key/authentication solution
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The MetaCloud
ProtoGENI
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The Instageni rack
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Designed for GENI Meso-scale deployment
Eight 2012 deployments, 24 2013 deployments
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ProtoGENI and FOAM as native Aggregate Managers
and Control Frameworks
Boots to ProtoGENI instance with OpenFlow switch
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Designed for wide-area PlanetLab federation
PlanetLab image provided with boot
InstaGENI PlanetLab Central stood up
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Designed for expandability
Approx 30U free in rack
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Understanding the instageni rack
•Two big things:
IT’S JUST ProtoGENI
It’s this thing
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It’s just protogeni
•Key Design criterion behind the InstaGENI rack
Reliable, proven control framework
Familiar UI to GENI experimenters and administrators
Well-understood support and administrative model
•We’re not inventing new Control Frameworks, we’re deploying Control
Frameworks and Aggregate Managers you understand and know how to
use
Network of baby ProtoGENI’s, with SDN native to the racks
•Allocation of resources with familiar tools
Flack...
•Easy distribution and proven ability to run many images
•Support model well-understood
If something goes wrong, we know how to fix it...
•PlanetLab and OpenFlow integration out-of-the-box
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The “Apple-II of Clouds”
•Key insight: the Apple II wasn’t the first mass market computer because it
was innovative, but because it was packaged
•Pre Apple-II, computers were all hobbyist kit
“Much Assembly, Configuration, Software Writing, Installation required”
•But the Apple-II worked out of the box
Plug it in and turn it on
And that’s what made a revolution
•Same Idea
Plug in the InstaGENI Rack
Put in the wide-area network connection
Rob will install the software and bring it up over the net
You’re on the Mesoscale!
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The InstaGENI rack
•Designed for easy deployability
Power: 220V L6-20 receptacle (or two 110V)
Network: 10/100/1000 Base-T
•Pre-wired from the factory
•On the Mesoscale
Network connections pre-allocated
VLANs and connectivity pre-wired before the rack arrives
•Designed for Remote Management
HP iLO on each node
•Designed for flexible networking
4 1G NICs/node, 20 1G NICs, v2 linecards OpenFlow switch
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Instageni rack hardware
•Control Node for ProtoGENI Boss, ProtoGENI users, FOAM Controller,
Image storage…
HP ProLiant DL 360G7, quad-core, single-socket, dual NIC (1 Gb/sec), 12GB RAM,
4TB Disk (RAID), iLO
•Five Experiment Nodes
HP ProLiant DL 360G7, six-core, dual-socket, quad NIC (1 Gb/sec), 48GB RAM, 1TB
Disk, iLO
•OpenFlow Switch
HP E 5406, 20 1 Gb/s, v2 linecards
Hybrid mode
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Instageni planned deployment
• GENI funding
8 sites in Year 1
24 sites in Year 2
All in USA
• Other Racks
US Public Sector except Federal Government: Special HP
program
• Contact Michaela Mezo, HP SLED
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Instageni year 1 sites
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Instageni rack diagram
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Instageni rack topology
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instageni photo
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Instageni software architecture
InstaGENI
PLC
GENI L2/L3
Slice
Layer 2 and 3 connectivity
PlanetLab
Image
ProtoGENI
Image
ProtoGENI
Image
ProtoGENI (Hardware as a Service,
Infrastructure as a Service)
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FOAM (Networks as a
Service)
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Control Infrastructure
Control / External switch
Control Node: Xen Hypervisor
ProtoGENI “boss”
FOAM
ProtoGENI “ops”
FlowVisor
Data Plane Switch
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(rE)Provisioning Nodes
ProtoGENI
Shared
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PlanetLab
Shared
ProtoGENI
Exclusive
ProtoGENI
Exclusive
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ProtoGENI
Exclusive
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Selected Other Interconnections
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Thanks!
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The “Grand Challenge” Phase of Research
Transition from individual experimenter to institution or multi-institution
team
Typically necessitated because problems go beyond the scale of an
individual research group
Investigation of new phenomena required dramatic resources
Ex: particle physics 1928-1932
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Experimental Physics Before 1928
Dominated by tabletop apparatus
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•
•
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Ex: Rutherford’s discovery of
the nucleus, 1910
Done with tabletop apparatus,
shown here
Major complication: had to
observe in darkened room
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Example: Chadwick and the Neutron
Chadwick used high-energy particles
from polonium to bombard nucleus
Neutron only method to account for
high-energy radiation from
bombardment
Key apparatus “leftover plumbing” –
pipe used to focus radiation beam
Date: February, 1932
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Entry of Institutional Physics
Nuclear Fission, Cockcroft
and Walton, April, 1932
Key: needed high voltages
(est 250,000+ volts) to split
nucleus
Room(!) to hold apparatus
major constraint
Needed major industrial
help (Metropolitan-Vickers)
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What a difference two months makes..
Chadwick, 2/32
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Cockcroft/Walton, 4/32
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Since Then…
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Key Differences
Apparatus now takes many years to construct, costs billions
Requires multi-national consortia
Discoveries made by large teams of scientists
Hundreds on the Top Quark team\
Thousands on the Higgs Team
Experiments last for 30+ years
Ex: ALICE at LHC, Babar at SLAC
Experimental devices measured by energies of collisions produced
Driven by cost and complexity of apparatus
Cockcroft and Walton heralded era of institutional Grand Challenge
physics
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The era of institutional systems research
Computer Systems Research, 1980-2010
Dominated by desktop-scale systems
1980-~1995: The desktop was the experimental system
Ex: Original URL of Yahoo! was akebono.cs.stanford.edu/yahoo.html
Akebono was Jerry Yang’s Sun workstation!
• Named for a prominent American Sumo wrestler – Jerry had spent a term in Kyoto in 1992
Sometimes “servers” used to offload desktops
But rarely: “Server” ca. 1990 was a VAX 11, less powerful than a SUN or DEC workstation
~1995-~2005: Used servers primarily because desktop OS unsuitable for
serious work
~2005-: Need clusters (and more) for any reasonable experiment
The Era of Institutional Systems Research has begun
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Why?
Activity in 21st Century Systems Research focused on massively parallel,
loosely-coupled, distributed computing
Content Distribution Networks
Key-Value Stores
Cloud Resource Allocation and Management
Wide-Area Redundant Stores
Fault Recovery and Robust Protocols
End-system multicast
Multicast messaging
Key Problem: Emergent Behavior at Scale
Can’t anticipate phenomena at scale from small-scale behavior
Hence: Moderate-to-large scale testbeds:
G-Lab, PlanetLab, OneLab,…
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What we need, what we don’t
What we need
Method of creating slices on clouds and distributed infrastructures
Method of communicating between clouds and distributed infrastructures
Method of interslice communication between clouds
What we don’t
Single sign-on!
Single AUP
Single resource allocation policy or procedure
Unified security policy
Principle of Minimal Agreement
What is the minimum set of standards we can agree on to make this happen?
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What do we need from the clouds
Building Blocks
Eucalyptus: Open-source clone of EC-2
OpenStack: Open-source
Widespread developer mindshare (easy to use, familiar)
What we want: Slice-Based Federation Architecture
Means of creating/allocating slices
Authorization by Attribute-Based Access Control (ABAC)
Delegation primitive
Explicit costs/resource allocation primitives
• Need to be able to control costs for the developer
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Why GENICloud?
Minimal set of facilities to permit seamless interconnection without trust
Motivation: the Web
Web sites mutually untrusting
Key facilities: DNS, HTTP. HTML
What are the equivalents for Clouds?
Our cut: Slices, ABAC, DNS conventions
<instancename>.<sitename>.<slicename>.<authorityname>.transcloud.net
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Introduction – TransCloud
TransCloud = A Cloud Where Services Migrate, Anytime, Anywhere In a World
Where Distance Is Eliminated
Joint Project Between GENICloud, iGENI, G-Lab
GENICloud Provides Seamless Interoperation of Cloud Resources Across N-Sites, NAdministrative Domains
iGENI Optimizes Private Networks of Intelligent Devices
G-Lab contributes networking and advanced cloud resources
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Seamless Computation Services Available
Anytime, Anywhere
“The Cloud” offers the prospect of ubiquitous information
and services…BUT…
Performance of Cloud services Highly Dependent On Location
• Of End-User, Applications, Middle Processes, Network Topology
• Of Cloud Data, Compute Processes, Storage, etc
Why?
Performance of Legacy Protocols Highly Dependent on Latency
Therefore:
Want to compute anywhere convenient
Want to be able to compute everywhere
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What do we need to make this work?
Ability to instantiate and run a program anywhere
Common API at each level of the stack
IaaS/NaaS (VM/VN Creation)
PaaS (guaranteed OS/Progamming environment)
OaaS (Standard Query/Data Management API)
Easy, Standard Naming Scheme
I need to know the name of my VM’s, logins, store etc without asking
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Solution – TransCloud
Introducing TransCloud Prototype
An Early Instantiation of the Architecture
A Distributed Environment That Enables Component and Interoperability Evaluation
A Testbed On Which Early Experimental Research Can Be Conducted
An Environment That Can Be Used To Explain/Showcase New Innovative
Architecture/Concepts Through Demonstrations
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DEMO
What is the World’s Greenest City?
Answering this question through analysis of landsat data
Perfect job for distributed cloud
Currently running on HP Labs GENICloud
But we can distribute it anywhere…
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TransCloud Today
Approx 40 nodes at 4 sites, 10 Gb/s connectivity
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