mobile cloud computing - aalto university · centralized centralized service model scaling model hw...
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1 Copyright © Nokia Siemens Networks 2012 Document classification
Mobile Cloud Computing Aalto University 2012-11-21 T-110.5121
Markku Lepistö Principal Cloud Architect
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2 Copyright © Nokia Siemens Networks 2012
“Physical infrastructure, controlled programmatically through API calls” - Programmable Datacenter
Cloud Computing Principle
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3 Copyright © Nokia Siemens Networks 2012
Cloud Computing is an IT Transformation
Extreme uptime
(99.999%)
Designed for Failover (99.9%)
Designed for Failure
(Always on) SLA Model
Vertical Scaling
Expensive custom
hardware
Hardware HA
Centralized
Centralized Service Model
Scaling Model
HW platform
HA model
SW deployment model
Consumption model
Shared Service Model
Self Service Model
Decentralized Distributed
Software HA
Expensive “commodity” HW
Cheap “commodity” HW
Horizontal Scaling
Mainframe Enterprise Cloud
http://www.cloudscaling.com/blog/cloud-computing/the-evolution-of-it-towards-cloud-computing-vmworld/
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4 Copyright © Nokia Siemens Networks 2012
Traditional stack
From Traditional through Virtualization to Cloud Datacenters
Virtualization != Cloud Virtualization < Cloud
Virtualization stack
HW
APP APP APP
Virtualization Layer Virtualization
CAPEX Savings Through Server Consolidation
APP APP APP
HW HW HW
Cloud Stack
HW
APP APP APP
Cloud Layer Operations Platform Services Infrastructure Services
Virtualization Layer Automation
OPEX Savings & Efficiency through Automation, Standardization and Scale
Re-architecture for Design for Failure, Automation, IaaS / PaaS
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5 Copyright © Nokia Siemens Networks 2012
Jevon’s Paradox “Increasing efficiency of a resource increases its consumption”
Cost Reduction and Right-sizing
Business Agility
hour day week month
Traditional
Virtualized
Cloud
Service Deployment Time TCO
20%
40%
60%
100%
Innovation
Revenue Generating Services
80%
Public cloud
Private cloud
Traditional IT
Create more
..thus you consume more
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6 Copyright © Nokia Siemens Networks 2012
Potential On/Off-premise Evolution for SW Runtime Env’s - for overall IT, not Telco-specific
% of IT
Legacy Physical Dedicated HW on-premise
Virtualized Infrastructure on-premise
Time
IaaS Private Cloud on-premise
PaaS Private Cloud on-premise
PaaS Public Cloud off-premise
IaaS Public Cloud off-premise
Today
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7 Copyright © Nokia Siemens Networks 2012
Enterprise vs Utility Clouds - SLA Assurance & Cost
http://samj.net/2012/03/simplifying-cloud-reliability.html
Enterprise Computing Utility Computing
Reliable SW Reliable Infra
> 100 USD / VM / mth
Reliable SW Unreliable Infra
< 20 USD / VM / mth
Unreliable SW Reliable Infra
Legacy Starting Point
Unreliable SW Unreliable Infra
Service Failure
ROI, Service Margin from VM’s
Infrastructure TCO per VM
SW
re-a
rchi
tect
ure
cost
s ‘D
esig
n fo
r Fai
lure
’
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8 Copyright © Nokia Siemens Networks 2012
Data Layer Evolution 1) – Storage towards Distributed SW on COTS
Enterprise SAN
or NAS
Vertically scaling Forklift upgrades Fiber-Channel, iSCSI, NFS Expensive Appliances 2 heads’ limit for I/O paths and performance
x86 Storage Node x86 Storage Node x86 Storage Node
COTS HW, SW-defined Distributed Block Storage
+
x86 Storage Node x86 Storage Node x86 Storage Node
COTS HW, SW-defined Distributed Object Store
+
From.. x86 Compute Node x86 Compute Node x86 Compute Node
COTS HW, Ephemeral VM-local DAS Storage
..To
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Data Layer Evolution 2) – Databases towards Distributed SW on COTS
A-F G-O P-Z
SQL RDBMS Sharding
Clone (async)
Master
SQL RDBMS Write Master, Read Clones
Clone (async)
R R W W R R
Limited Scalability and Data Redundancy No or small changes to legacy apps Reliable Servers & Storage Expected
A’-Z’ A’-Z’ A’-Z’
Eventually Consistent NoSQL
Large horizontal scalability Distributed redundancy New apps or major re-write
*
*) Depending on needs, NoSQL can be a RDBMS replacement or an additional DB-like service
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Scalability & Fault Isolation Examples • DNS Round-Robin of Elastic IP’s for multiple Elastic Load Balancers • Memcached Front-End VMs • Asynchronous Message Queue, Event-driven Processing
• Scale out/in worker nodes based on queue length, execution time • Avoid dependencies – workers do not rely on, or wait for other VMs
• Use Vertical scalability, reboot VM with bigger instance type • Use Horizontal scale-out & in of VMs based on load, business rules • NoSQL or SQL DB replicated across multiple Availability Zones
Availability Zone 1
Availability Zone 2
ID
Object Store
Message Queue
ELB Load Balancers
DNS Load Balancing of Elastic IP’s of ELB’s
Data Tier multi-AZ NoSQL ring
FE/Cache App
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Small, Frequent Releases Reduce Risk
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Agile Development, Continuous Integration & Continuous Deployment (DevOps Principle)
Agile R&D Sprints
Automated Unit Tests per developer Automated Integration & Staging Tests
• Infrastructure as Code - Agile datacenter • Provision build farm on cloud, compile new packages • Provision App VMs on cloud, Orchestrate from new packages • Deploy test tool VMs on cloud • Run, Monitor, Report
(SaaS only) Manually Triggered, Automated Push to Production • Introduce frequent, small updates to production • Test on a subset of customers first • Automated regularly practiced rollbacks
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NSN Cloud Solution Example for Mobile Broadband
Usage Peak QoE Risk
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Teleoperator Radio Access & Core
Experience Mgmt, Self-Organizing Networks
SaaS Web & iPad QoE Insights & Actions
Data collection, obfuscation, compression, encryption, upload
NSN Analytics
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Teleoperator Radio Access & Core
Experience Mgmt, Self-Organizing Networks
Teleoperator Datacenter
HW
NSN Cloud Platform
IaaS
NS
N Infra, A
pp &
License Mgm
t
NSN Analytics
On-Premise Option QoE Insights & Actions
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Teleoperator Radio Access & Core
Experience Mgmt, Self-Organizing Networks
Teleoperator Datacenter
HW
NSN Analytics
NSN Cloud Platform
NS
N Infra, A
pp &
License Mgm
t
IaaS
NSN Analytics
Active Antenna Beam Forming
Handover
Wifi Offload
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Demo
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