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Software Defined Infrastructure
Mark Burgess Professor, PhD, BSc
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Trends and solutions for networks in an NFV/SDN era
• O - Operation, • M - Maintenance, • P - Provisioning
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• PhD theoretical physics • Professor of Network and System Administration • EMANICS network of excellence • CFEngine founder, computer immunology, promise theory • Industry advisor, researcher, working with SDN leaders • Web: http://markburgess.org
About me …
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Some conclusions
• Multi-tenant — self-service systems, built on fabrics
• Fixed and stable infrastructure fabrics
(net+compute+storage)
• Dynamic, virtualized names and services on top
• Get rid of middle-boxes (load-balancers, firewalls)
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There are no simple answers:
Technology is easy, people are difficult!
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Table of contents
I. The business challenge
II. The cultural challenge
III.The technical challenge
IV. Infrastructure fabrics
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I. The business challenge
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An on-going business transformation
( )
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Hypothesis driven deployment in a world of smart infrastructure
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Paris
Paris
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“Continuous improvement of software as a stream of releases, always ready for use…”
Continuous delivery is ...
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Irregular and high riskRegular and low risk
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What story are you trying to tell?
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II. The cultural challenge:
getting unstuck
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Infrastructure culture
AddressabilityLatencyConnectednessGarbage collectionNormalization
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Engineering focus
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Town planning
Business focus
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CADCAM
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Stylesheets for infrastructure
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“Functional” systems have two aspects
Semantics ( )
and
Dynamics ( )
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DevOps
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Semantics ( ) and Dynamics ( ) Desired-state and actual behaviour Dev + Ops What you intend + What actually happens
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Convergence
Infrastructure(ops)
Intent/function(dev)
Configuration driftPrep/runtime“Consensus”
Unintended changeEmergent side effects
Semantics ( )
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Continuity
Availability(ops)
History(dev)
Geography (space)Latency (time)
Usability (consistent)CompatibilityPersistence of worlds
Dynamics ( )
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• Convergence ( )
• to a desired end-state / promised outcome
• Divergence (branching decisions) ( )
• intentionally and unintentionally diverging
Competing forces
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Controlled and uncontrolled
• Diverging chain reactions ( )
• (branching, many-worlds)
• Convergence to a target ( )
• (possibly parallel sinks)
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Deployment or change management?Divergent ( )
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“Continuous delivery requires continuous automation ... not power-assisted intervention”
Intervention vs automation
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Technology should be simplicity
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Significant innovation doesn’t happen until humans change their habits, or get out of the way …
Human Identity inertia ( )
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III. The technical challenges
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Technical challenges
1.Scale
2.Complexity
3.Knowledge
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Atoms ( )
local information, autonomous
Autonomy ( )
freedom to act without dependency
Promises converge ( )
Modelling intent (semantics)
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Thinking in promises versus impositions
Impose:unpredictable
Promise:predictable policy
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Many parts with
STRONG COUPLING
increases complexity!
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Coupling - ecosystem
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Don´t confuse tidiness with resilience
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Don´t confuse untidiness with disorder
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Organization is optimization with constraints
Autonomous agents that keep promises
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1. Scaling
Vertical
Horizontal
Simple
Complex
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2. Complexity
Weak coupling, and clear relationships
EncapsulationTunnelsVxLANGREEVPN
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Centralized(Vertical)
HumanizedPoints of serviceIdentitiesHomeLocalIntentional
Decentralized(Horizontal)
DehumanizedLogisticsReplicasStorageNon-localEmergent
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Central BRAIN … (vertical scaling, strong coupling)
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Decentralized Society ….(horizontal scaling, weak coupling)
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3. Knowledge
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Parallel
Serial
The story …
SSH
cron jobscontainers
hands-on
3. Knowledge
Semantics ()
Dynamics (
)
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IV. Infrastructure fabrics
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Network designed for low density end-points
• New reality:
• High density datacenter (North-South, East-West)
• Internet of Things
• Push networking (UDP)
• TCP brings more security
• Built on top of Ethernet (bus arch)
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Scaling network communication
• Read/retrieve/service portal (promises) • Client-server, anycast
• Publish-subscribe (streaming)
• Caching/CDN: fixed addresses not that important
• Signalling (impositions) • Scales vertically (brute force)
• Fixed addressing important
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Summary: From impositions to promise thinking
1. Every processing entity in an infrastructure MUST be individually
addressable (SCALE)
2. Remove middle-boxes (COMPLEXITY)
3. Instead of uninvited impositions, get clients to establish a bond
with a service point (KNOWLEDGE)
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Sharing resources
How does workload affect the needs for resource sharing?
Where to put workloads and data to best tell the business story?
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The failures of vertical network scaling
• Address scaling -> NAT • NAT -> private addressing • private addressing -> L2 /LAN thinking • L2 focus -> tunnels to extend LANs • tunnels -> dynamic address rewriting • dynamic addresses -> collapse under complexity
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SDN is fixated on LAN
• IPv4 a flawed model of LAN/WAN • WAN/(LAN x 2) + ARP • Routing AND L2 tunnels
• IPV6• Peer discovery• L3 Index service
•Hint (CDN)
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Bad semantics ( ) L3 subnets confused with host groups
Scalabilty
Summarization
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Why LAN doesn’t scale, and why tunnels don’t help
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Bad dynamics ( ) Abusing L2 tunnelling
Can’t extend a broadcast group indefinitely
Tunnels don’t really simplify navigation, just make it someone else’s problem
Tunnels: VxLAN, EVPN (MPLS/BGP)
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High density workloads
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Middle-boxes, “network functionality”
Load balancers —> Firewall
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Designed for a sparse hierarchical network
• Designed for North-South traffic model
• Pile weight into single point of failure
• Break end-to-end principle
• Addresses don’t match geography
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Load balancing by cooperation
Imposition —> Promises
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Firewall by cooperation
Imposition —> Promises
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Microservices
Autonomous tenants .. many autonomous agents rather than a top down control
Strong vertical integration for human ownership
Weak horizontal integration for scale
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We have to separate end-point names/addresses from transport mechanisms
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Namespaces ( )
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Technology should be simplicity
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Tenant networks
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Clos non-blocking fabrics (I)
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Pattern based provisioning (e.g. CFEngine)
bundle agent clos { vars:
# Generate the interface lists used on the routers
"spine" slist => expandrange("swp[1-5]", "1"); # point to 5 leafsw "leaves" slist => expandrange("swp[1-2]", "1"); # point to 2 spinesw
interfaces:
spine::
"$(spine)" link_services => ibgp_reflector("server");
ToR::
"$(leaves)" link_services => ibgp_reflector("client"); }
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Complexity (strong coupling) means cost
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Clos non-blocking fabrics (II)
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Cable-Free Clos non-blocking fabrics (III) ?
Weak coupling
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Addresses that reflect location
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3d printed datacenter
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Balance exploration against simple targeted outcomes Automate documentation of intent: policy converges ( )
Watch out for the human storyline ( )
Delegate for tidiness with weak coupling ( )
The future
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Join the discussion …