emerging architecture for cloud computing · tunis, tunisia, 18-19 june 2012 emerging architecture...

Tunis, Tunisia, 18-19 June 2012

Emerging Architecture for Cloud Computing

Monique Jeanne Morrow Distinguished Engineer and CTO

Asia-Pac mmorrow@cisco.com

ITU Workshop on “Cloud Computing”

(Tunis, Tunisia, 18-19 June 2012)

My Co-Authors

Masum Z. Hasan,Sree Gudreddi, Edgar Magana and Lewis Tucker

Cisco CTO Office

Remember: Network Factored Cloud?

App Tiers in a Typical DC

Web Tier

App Tier

DB Tier

Storage Tier

Dept/Customer 1 Dept/Customer 2

Dept 2 Dept 1

App 6 App 1

Access

DB 2

SAN

DB 1

Outsource to Cloud

Aggregation

Distribution

Core

DC

MAN/WAN/SP Net Internet

Branch Branch

DMZ

Tiered Network: §  Storage §  SAN/NAS §  Access: App tiers reside here §  Aggregation, distribution, core

(part of app tiers may reside here) §  DMZ §  Campus core/MAN/WAN edges

WAN Network

Func%onal  Servers  

WAN  Edge  

Data  Center  Core/  Gateway    

Customer  Edge  

L2  Aggregator    

Server  Rack  

Virtual  Server  

ApplicaBon  

VM/Server  Control    

Server  

Hypervisor  

Virtual  Subnet/VLAN  1  

Virtual  Subnet/VLAN  2  

Data  Center  A  

ApplicaBon  

Virtual  Machine  (VM)  

ApplicaBon  

Virtual  Machine  (VM)  

ApplicaBon  

Virtual  Machine  (VM)  

ApplicaBon  

Virtual  Machine  (VM)  

ApplicaBon  

Virtual  Machine  (VM)  

ApplicaBon  

Virtual  Machine  (VM)  

ApplicaBon  

Virtual  Machine  (VM)  

ApplicaBon  

Virtual  Machine  (VM)  

Provisioning,  Billing,  Security,  Load  Balancing,  Monitoring,  AudiBng,    Logging,  and  ETC.  

Func%onal  Servers  

Generic Data Center and Network Drawing

<TELSTRA DOCUMENT ID>

Workloads categorisation (and generalisations)

Type of Workload Example Implication

Stateful Shopping cart, collaboration services Synchronisation

Stateless HTTP (without cookies) No synchronisation required

Live Mission-critical ERP, hosted UC&C services Performance, distance, application tolerances

Offline Document management, archives -

Bursty Voting system, VoD, ticket booking Capacity management

Non-bursty Data analysis

Time dependent (predictability)

Desktop as a Service (during business hours vs. non-business hours)

‘Follow the moon’ migration

Shared Utility hosting (SaaS) -

Grid Grand challenge problems – derivatives analysis at NAB, SETI

Higher utilisation possible – requires HPC environments

Transactional Billing system Local storage & compute

Batch Payroll Storage & compute can be remote

One or more DC Cloud Service Provider #1

Public / Community Clouds

One or more DC

Cloud

Service Consumer

Enterprise IT Cloud Service

Provider

Intranet

Internet /

SP Private MAN/WAN (IP/

MPLS/ Optical)

Seamless Extension

Tenant Private Cloud / Intranet

Seamless Execution and management as if all resources are on Intranet

Enterprise Users, Departments

One or more DC

Cloud Service

Provider #K

Internet / SP Private MAN/WAN

Putting it All Together: Seamless Cloud

Seamless Cloud: covers Private, Hybrid, Multi-SP Inter-Cloud

VM13 DB1 OS1

vNIC2

VM55 App1 OS2

vNIC5

One or more DC

Cloud Service

Provider #K

Internet / SP Private MAN/WAN

SCL Service

Use case: Distributed Applications on Seamless [Hybrid/Inter] Cloud

Cloud Provider’s DC

Enterprise (on-premises)

Cloud Network

Example: Hadoop MapReduce

Launch Map/

Reduce

Get processed Data

(HTTP)

Get processed Data

(HTTP)

Load Data in DFS nodes

Data Block Info (RPC)

CSP Cloud Management Framework (CCMF)

Network Compute/VMM Storage Physical Compute/Storage/Network Element or Infra Layer

Network

Cloud Resource/Service CRUD Realization Layer

Compute/VM Storage

Cloud Services Layer Cloud Services API Engine IaaS

PaaS

SaaS

Cloud Abstraction Compute/VM Storage Network

(Abstract) Cloud Resource Management

CCMF/CSP Internal or CSPßàCSP

Internal Interfaces or Protocols CLI, XML-I, SNMP, etc.)

§  Cloud Service and Resource Management §  Cloud Abstraction §  Cloud service interfaces to Cloud Service Consumers à  Software :Examples: vCloud Director, Amazon AWS, OpenStack (Cloud Abstraction) Compute, Storage, Network abstraction & Management (config / provisioning / monitoring), Orchestration and Automation à Software Example: NMS/EMS, Orchestrator/Management Systems, Libvirt API, OpenStack NACI for Inter-Cloud, DQCS Embedded Management, Control in devices à Software and Hardware

Cloud Service Consumer (User / Admin/ Tool / Program)

SP Private MAN/WAN / Internet

Tenant ßà CSP Interfaces

SCL

Network Abstraction for Cloud Interfaces (NACI)

Cloud Management Framework Architecture

RFC 4954 Service Class based DQCS

"   Application or Service class based

"   T2CSP: specify service class (such as Multimedia Streaming) when acquiring compute/storage resource

"   CSP-I/NACI: Realize_QoS (DSCP, BW, …, points_in_network)

"   CSP-CSP "   Delegate T2CSP

request

ITU Y.1541

•  IPTD: one way •  Y.1541 defines IP Delay Variation in terms of the difference between the minimum and maximum transmission delays during some time interval.

•  IPTDmin = Minimum IP transmission delay

•  IPTDupper = 99.9% percentile of IP transmission delay

•  IPDV = IPTDupper – IPTDmin

RFC 4594, Y.1540/1 and other Recommendations

ITU Y.1540/1

Class 3

Class 0

Class 3

Class 0

Class 0

Class 4

Class 1

Class 3

Class 4

Class 4

Class 5

Class 5

------------------------------------------------------------------- |Service Class | | Tolerance to | | Name | Traffic Characteristics | Loss |Delay |Jitter| |===============+==============================+======+======+======| | Network |Variable size packets, mostly | | | | | Control |inelastic short messages, but | Low | Low | Yes | | | traffic can also burst (BGP) | | | | |---------------+------------------------------+------+------+------| | | Fixed-size small packets, | Very | Very | Very | | Telephony | constant emission rate, | Low | Low | Low | | | inelastic and low-rate flows | | | | |---------------+------------------------------+------+------+------| | Signaling | Variable size packets, some | Low | Low | Yes | | | what bursty short-lived flows| | | | |---------------+------------------------------+------+------+------| | Multimedia | Variable size packets, | Low | Very | | | Conferencing | constant transmit interval, | - | Low | Low | | |rate adaptive, reacts to loss |Medium| | | |---------------+------------------------------+------+------+------| | Real-Time | RTP/UDP streams, inelastic, | Low | Very | Low | | Interactive | mostly variable rate | | Low | | |---------------+------------------------------+------+------+------| | Multimedia | Variable size packets, |Low - |Medium| Yes | | Streaming | elastic with variable rate |Medium| | | |---------------+------------------------------+------+------+------| | Broadcast | Constant and variable rate, | Very |Medium| Low | | Video | inelastic, non-bursty flows | Low | | | |---------------+------------------------------+------+------+------| | Low-Latency | Variable rate, bursty short- | Low |Low - | Yes | | Data | lived elastic flows | |Medium| | |---------------+------------------------------+------+------+------| | OAM | Variable size packets, | Low |Medium| Yes | | | elastic & inelastic flows | | | | |---------------+------------------------------+------+------+------| |High-Throughput| Variable rate, bursty long- | Low |Medium| Yes | | Data | lived elastic flows | |- High| | |---------------+------------------------------+------+------+------| | Standard | A bit of everything | Not Specified | |---------------+------------------------------+------+------+------| | Low-Priority | Non-real-time and elastic | High | High | Yes | | Data | | | | | -------------------------------------------------------------------

Other recommendations: Streaming video: Loss: 2% (2 loss every 100) Delay: 5s Jitter: Unspecified Video Conferencing: Loss: 1% (1 loss every 100) Delay: One-way 200ms Jitter: Average 30ms Bandwidth: Extra 20% for burst Voice: Loss: <=1% Delay: One-way 200ms Jitter: Average 30ms Bandwidth per call: 21-106 kbps based on sampling rate, codec, frame/packet overhead

IPLR/IPTD/IPDV Loss/Delay/Jitter Ignore IPER (BER) Class 0: .001/100ms/50ms Class 1: .001/400ms/50ms Class 2 .001/100/U Class 3: .001/400ms/U Class 4: .001/1s/U Class 5: U/U/U

Conclusions and Recommendations

"   Now looking at offering Differentiated Cloud Services

"   Inter-Cloud and so called Federated Constructs now

"   Prototyping Service capabilities in progress

"   Cloud Standards Activities very active