fabien hermenier a.k.a guillaume urvoy-keller …..starting ...urvoy/docs/vicc/vicc-introduction...
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Cloud computing101
Fabien Hermenier a.k.a Guillaume Urvoy-Keller
…..starting from 2017
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Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction.
2011
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1 self-provisioning,no human intervention
On-demand self-services
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2availability over the
networkstandard mechanisms
broad network access
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3multi-tenant
virtual or physical resourceson-demand allocation
location independance
resource pooling
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reserved instances (yearly based)on-demand instances (hourly based)
hotspot instances (market based)7
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Amazon EC2HotSpot instances
bid over the market price to get the instance8
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4fast (de-)allocation of resourcesscale to infinity
rapid elasticity
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verti
cal
elas
ticity
Tiers 1
Tiers 2
Tiers 3
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horizontal elasticity
Tiers 1
Tiers 2
Tiers 3
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5 metering capabilitiestransparent reporting
measured service
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and I will call it cloud computing
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Cloud Computingorigins
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If computers of the kind I have advocated become the computers of the future, then computing may someday be organized as a public utility just as the telephone system is a public utility... The computer utility could become the basis of a new and important industry.
John McCarthy, 1961
“”
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cluster computing
loosely coupled co-located serverssingle tenant
non-interactive workload rigid jobs
80s17
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Clo
ud o
r no
t ? on demand self-services
broad network access
resource pooling
rapid elasticity
measured service18
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Clo
ud o
r no
t ? on demand self-services
broad network access
resource pooling
rapid elasticity
measured service19
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ApplicationService
Provider
service oriented
pay as you go
95+1
Client2
Client3
Client
remote access todedicated applications
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Clo
ud o
r no
t ? on demand self-services
broad network access
resource pooling
rapid elasticity
measured service21
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Clo
ud o
r no
t ?
on demand self-services
broad network access
resource pooling(not real hw resources)
rapid elasticity
measured service22
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computers on demand.2002Deploy full custom stacks (OS to applications)
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to (re)deploy reproduciblenetwork experiments
multi-tenant,(limited on purpose) resource pooling
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to (re)deploy reproduciblenetwork experiments
100Mb/s10ms
10ms50ms,
5% loss
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Clo
ud o
r no
t ? on demand self-services
broad network access
resource pooling
rapid elasticity
measured service26
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Clo
ud o
r no
t ? on demand self-services
broad network access
resource pooling
rapid elasticity
measured service27
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S O Aervice
orientedrchitecture
2001+
composable unassociated, loosely coupled units
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exponential grows since 2001 private and public services to support its
growth
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800 x
tons of API, mini-services devoted to automation, flexibility, on-demand services for public and private use
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2006
scalable web services for other websites or client-
side applications31
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SOAP & REST over HTTPpay as you goelastic *-oriented services
*data, network or computation32
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Clo
ud !
on demand self-services
broad network access
resource pooling
rapid elasticity
measured service33
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?aaS34
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web access to commercial sw.“one to many” model
customers don’t handle upgradesAPI for integration
Softwareas a ServiceS
aaS
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jailed runtime available to host applicationsgeneric or provider-specific APIsno control over the environment
Platformas a ServiceP
aaS
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$ heroku login…
$ git clone https://github.com/heroku/java-getting-started.git$ cd java-getting-started
$ heroku createCreating warm-eyrie-9006... done, stack is cedar-14http://warm-eyrie-9006.herokuapp.com/ | [email protected]:warm-eyrie-9006.gitGit remote heroku added
$ git push heroku master… http://warm-eyrie-9006.herokuapp.com/ deployed to Heroku
$ heroku ps:scale web=1
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Infrastructureas a Service
low-level resources to deploy arbitrary software stackscomplete control over its network, storage and OS
IaaS
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Things will crash. Deal with it!
Assume you could start with super reliable servers (MTBF of 30 years)Build computing system with 10 thousand of thoseWatch one fail per day
Dean Keynote, LADIS 2009
“
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~0.5 overheating (power down most machines in <5 mins, ~1-2 days to recover)~1 PDU failure (~500-1000 machines suddenly disappear, ~6 hours to come back)~1 rack-move (plenty of warning, ~500-1000 machines powered down, ~6 hours)~1 network rewiring (rolling ~5% of machines down over 2-day span)~20 rack failures (40-80 machines instantly disappear, 1-6 hours to get back)~5 racks go wonky (40-80 machines see 50% packetloss)~8 network maintenances (4 might cause ~30-minute random connectivity losses)~12 router reloads (takes out DNS and external vips for a couple minutes)~3 router failures (have to immediately pull traffic for an hour)~dozens of minor 30-second blips for dns~1000 individual machine failures~thousands of hard drive failuresslow disks, bad memory, misconfigured machines, flaky machines, etc.Long distance links: wild dogs, sharks, dead horses, drunken hunters, etc.
Typical first year for a new google cluster
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Building fault tolerant
services
deal with failuresdeal with inconsistency
be pessimistic
at every level
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October, 21th 2016: dynDNS targeted by a DDoS
Affected services:
1.2 Tb/s of DNSlookups
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applicationsruntimes
integration/security
databaseservers
virtualisationserver HW
storagenetwork
you
man
age
ol’school IT
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SaaSapplications
runtimesintegration/security
databaseservers
virtualisationserver HW
storagenetwork
man
aged
by
vend
or
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PaaSapplications
runtimesintegration/security
databaseservers
virtualisationserver HW
storagenetwork
you manage
man
aged
by
vend
or
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Open-source PaaS stacks
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IaaSapplications
runtimesintegration/security
databaseservers
virtualisationserver HW
storagenetwork
you
man
age
man
aged
by
vend
or
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Open-source IaaS stacks
(2008+)
cloudstack
(2008+)
(2010+) (2012+)
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vendor lock-in
IaaS PaaS SaaS
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Deployment models
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public cloudgeneral availability to
everyone
the “real” cloudreduced coststrust issues ?
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Trust in megive me your code & data
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private cloudself hosted cloudworldcompany SA
might reduce TCOstronger trust
better manageability
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worldcompany SA hybrid cloud
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multi-cloudsyou spread your application
avoid Single Point of Failures*take the benefits of each cloud
LB
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