Blueprinting solutions for cloud computing

Prof. Mike P. Papazoglou

Executive Director - ERISS Tilburg University, The Netherlands

email: [email protected], http://www.eriss.org

BLUEPRINTING SOLUTIONS for

CLOUD COMPUTING

European Research Institute in Service Science

•  The ERISS vision focuses on how emerging technologies will impact organizations & society and provide critical insights to influence policy makers & businesses

Vision

Scientific Conferences, Programs & Summer Schools

•  Founders of the flagship International Conference on Service Oriented Computing (ICSOC)

•  Founders of the International Master in Service Engineering (IMSE)

•  Joint founders of the highly successful Service and Software Architectures, Infrastructures and Engineering (SSAI&E) Summer School – supported by the EU FP-7 IST SSAI&E unit

Collaborative Research

•  Joint research conducted with top research institutes in Europe, N. America, Australia & East Asia (China & Japan)

Expertise • Dedicated highly-qualified R&D team working at the intersection of business and technology

• Builds on a proven track record of envisioning the future, inventing and delivering the next wave of cutting-edge research solutions

Service Oriented Computing

Business Process Management

Cloud Computing

Research Expertise

Multidisciplinary

Research M

ethods

AGENDA

 Overview, Vision & Aim   Brief Introduc7on to Cloud Compu7ng  The Cloud Delivery Model Landscape  Managing the Cloud   Blueprint Example: Interac7ve Telco Services  Final Remarks

Michael P. Papazoglou © Keynote: “Australian Symposium on Services Innovation”, 21-22 November, Wollongong, Australia. 3

Overview, Vision & Aim

Vision: Smart Cloud Services

Smart traffic systems

Smart water management

Smart healthcare

Smart food systems

Smart supply chains

Smart cities

Smart business systems

Smart telephony

The world needs to get smarter – more instrumented, interconnected & lead to beLer decision making. Smarter Service & Cloud technologies are central to this vision.

(Process-‐intensive & event-‐driven applica3ons)

5 Michael P. Papazoglou © Keynote: “Australian Symposium on Services Innovation”, 21-22 November, Wollongong, Australia.

Aim of Talk

Describe an approach that supports the effec7ve deployment of global-‐reach service-‐based apps into a variety of different implementa7on plaPorms -‐ in par7cular federated cloud compu7ng forma7ons.

Michael P. Papazoglou © Keynote: “Australian Symposium on Services Innovation”, 21-22 November, Wollongong, Australia. 6

Brief Introduction to Cloud Computing

Cloud: Consump7on & Delivery Models Op7mized by Workload

•  A new consump7on and delivery model inspired by consumer Internet services.

  Private, Public and Hybrid   Workload and/or Programming Model Specific

  The Industrializa7on of Delivery for IT supported Services

Cloud Services

Cloud Compu0ng Model

  Infrastructure configuring   Highly virtualized infrastructure   Sourcing op7ons   Economies-‐of-‐scale

Mul0ple Types of Clouds will co-‐exist:

“Cloud” represents:

Cloud enables: “Cloud” is:

Cloud Computing Overview

8 8 Michael P. Papazoglou © Keynote: “Australian Symposium on Services Innovation”, 21-22 November, Wollongong, Australia.

Cloud Computing Delivery & Deployment Models

Cloud Deployment

Models

9

Hybrid Private Public

Cloud service delivery model (provided by Cloud Providers)

Cloud Service

Applica0ons

Infrastructure as a Service (IaaS) •  Virtualized servers •  Memory, CPUs, Disk space •  Networking

PlaEorm as a Service (PaaS) •  Middleware – applica7on servers •  Process automa7on middleware •  Database servers •  Provisioning, etc.

SoFware as a Service (SaaS) •  Applica7ons (ERP, SCM, CRM) •  Processes •  Informa7on

Client-‐2 Client-‐n

Client-‐1

Michael P. Papazoglou © Keynote: “Australian Symposium on Services Innovation”, 21-22 November, Wollongong, Australia.

Cloud Architecture

Standard APIs

Service Developer

Service Consumer

Standard APIs Service Provider

User Interface

SLAs/ contracts

Service Template Creation

Service Template Publication

Service Analytics &

Reporting Service Metering

Service Monitoring

Service Provisioning

Capacity Mgmt

SLA Mgmt

Service Billing

Service Reporting

Service Management

Hardware

Software Kernel (OS, Virtual Machine Manager)

Virtualized Resources

servers storage network

Infrastructure as a Service (IaaS)

Software as a Service (SaaS)

Cloud apps Cloud

apps

Cloud apps

Platform as a Service (PaaS)

Virtual Image Mgt

Image Library

Image

Data Privacy

Authentication &

Authorization

Auditing &

Accounting

Data Network Security

Certification &

compliance

Security


Purchasing

Billing & Collections Management

Service-based Application

Service Provider

Service

interface


Service Provider

Service

interface


Service

interface


Service Provider Se

rvice

interface

End-to-end Logistics Processes

Inventory

SOA in the Cloud

11

Service Provider


Cloud environment (platform & infrastructure providers)

Order Management

The Cloud Delivery Model Landscape

Inflexible Monolithic Cloud Delivery Models

•  A monolithic one-size-fits-all SaaS/PaaS/IaaS stack architecture and vendor lock-in prevails.

•  PaaS offerings are constrained by providers’

capabilities. They don’t allow easy extensibility, mashup, or customization options at the consumer or developer levels.

•  Rigid service orchestration practices tied to a specific resource/infrastructure configuration at the application level.

•  SaaS is predominantly tethered to proprietary application platforms in which the cloud provider runs all elements of the service and presents a complete application to the client. They’re hard to extend or customize.

Data

Runtime

Middelware

OS

Virtualization

Servers

Sotrage

Networking

Application

SaaS


Example: Impediments of Current SaaS Solutions

-‐  Difficult to compose SaaS solu3ons in end-‐to-‐end processes -‐  Difficult to re-‐configure/customize SaaS solu3ons


Stairway to the Clouds: Breaking the Cloud Delivery Monolith

15

S1

SaaS

PaaS

IaaS

S2

SaaS

PaaS

IaaS

Provider #1 Provider #2


The Syndicated Multi-channel Cloud Delivery Model

Benefits •  Increased interoperability •  Protec7on against vendor lock-‐in in the cloud

•  Increased quality, callability, performance, (low latency, bandwidth)

•  Control, reliability, simplicity, faster deployment, enabling new applica7ons

•  New business models, innova7on, cost reduc7on

Virtualized applica0ons comprising end-‐to-‐end

Processes (BPaaS-‐Layer)

Client-‐2 Client-‐3 Client-‐n

SaaS-‐1 SaaS-‐2 SaaS-‐3 SaaS-‐n

PaaS-‐1 PaaS-‐2 PaaS-‐3 PaaS-‐n

IaaS-‐1 IaaS-‐2 IaaS-‐3

Applica0on


Managing the Cloud

Meta-data Templates

•  Meta-‐data templates: Templates describe how a cloud offering is presented & consumed. The offering is abstracted from the specific type of cloud resources offered. The provider uses service templates to describe in a general form what a cloud service can offer.

  The Open Virtualiza7on Format (OVF) is an open, portable, &

flexible format for the packaging & distribu7on of virtual appliances (pre-‐built solu7ons comprised of one or more VMs).

  By packaging virtual appliances in OVF, vendors can create a single, pre-‐packaged appliance that can run on customers’ virtualiza7on plaPorms of choice.


Model-driven Approaches

19

•  IaaS model-‐driven approaches automate the deployment of complex IaaS services on cloud infrastructure.

  A virtual appliance model treats virtual images as building blocks for IaaS composite solu7ons.

  Virtual appliances are composed into a virtual solu7on model which helps developers determine deployment-‐7me requs in a cloud-‐independent manner using a parameterized deployment plan.

  Composite appliances automate the deployment of complex app services on a cloud infrastructure.


The Blueprint Cloud Delivery Model

The Blueprint Model

21

•  The term "blueprint” refers to any detailed architectural plan, e.g., a technical drawing documen7ng an architecture or an engineering design.

•  The blueprint model builds & documents a holis7c cloud architectural solu7on as assembled & operated, by engaging available cloud stack modules at all layers.

•  It configures a unique op7mized cloud environment to meet specific a broad range of applica7on requirements & policies, which specify what is desired (e.g., consistency, security and privacy requirements) & not how it is to be accomplished.


The Blueprint Model: Commoditizing the Cloud

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SaaS Service

PaaS Service

IaaS Service

SaaS-BP

PaaS-BP

IaaS-BP

Blueprints Cloud Services

Describes

Describes

Describes

Provides abstract reusable and composable descrip7ons of cloud stack services that can be used as lego blocks to describe, create and deploy desired federated cloud architectures.

Features of the Blueprint Model

23

•  It lets developers syndicate, configure, par77on & deploy virtual service app payloads on VM & resource pools in the cloud by clearly separa7ng service processing concerns.

•  It alleviates vendor lock-‐in & promotes interoperability. –  Any service can interoperate horizontally with another service at the same level of the cloud stack provided elsewhere.

–  Upstream or downstream (ver7cal) interopera7on of cloud services is possible.

•  It maps declara7ve configura7on points for abstract cloud service specs to available resources, & composes them into complete solu7on models (using simple aggrega7on and cross-‐configura7on of virtual services).


Elements of the Blueprint Framework

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Opera0onal service descrip0on, performance-‐oriented service capabili0es, resource u0liza0on

Query BDL & BCL templates & reason about correspondences,

mismatches, etc.

Based on model mgt algebraic ops, e.g., match, merge, compose, extract, delete, etc

Resource Le

verage

Any aspect of an SLA about a service: includes security, privacy,& compliance requirements

Blueprint Constraint Language

Blueprint Manipula0on Language

Blueprint Query Language & Reasoning Mechs

Declara0ve Blueprint Request Language

Blueprint Defini0on Language

Developer/user centric language


The Blueprint Cloud Lifecycle Model

Marketplace Repository

AD

Applica7on Developer

End user

Service provider

AD

SP

User

Customized source blueprints

Source Blueprint model

Customized source blueprints

Blueprint Query Engine

Blueprint Manipula0on Language

User

AD

+

Source Blueprint models

Interim Target Blueprint model

Deployment Plans & Configura0on Op0ons

Op0mized Target Blueprint model

SP Blueprint Defini0on Language



User Design

Design

Selec0on

25 Michael P. Papazoglou © "Research Roadmap in Service Oriented Computing" Summer School, Espoo, Finland - August 26, 2011

Cloud resources

Tes0ng &

Monitoring

Blueprint Defn Language: Specifying Blueprints

•  Func7onal characteris7cs, including: •  Service type •  Messages •  Interfaces •  Opera7ons

•  Defines the KPIs associated to the services, e.g.,: •  Ranges of service availability •  Latency •  Bandwidth

•  Describes the physical infrastructure & resources that are required to run the service described in the blueprint. Prototypical items include: average and peak workload requirements

•  Policies: •  Prescribe, constrain and specify any aspect of a

business agreement needed to use a service, including items such as security, privacy and compliance requirements.

Opera0onal Service Descrip0on

Resource U7liza7on

Policies Performance-‐oriented

Service Capabili0es

Virtual Resource Net

Blueprint Template

•  Inter-‐connected abstract resources: states func7onal inter-‐dependencies & deployment dependencies & deployment op7ons


Example: Specifying Vehicle Mgt Cloud Services <<Blueprint Vehicle Management App>>

•  Operation Service Description •  BlueprintID= VM-SaaS •  Description=The vehicle management software provided by AutoInc •  Ownership= {AutoInc, Software Industry, Netherlands, …} •  Version= 1.0 •  Release Date= 12/04/2011 •  Capability= Vehicle Management Software •  Service Signature

•  Functionality = To manage the status and location of fleet vehicles •  APIs Location = http//autoinc.com/apis •  Endpoint Location =http://autoinc.com/endpoint •  Range Nr Of Instances = {2,5}

•  Resource Utilization •  Resource Requirement= {‘AutoInc-Req01’, ‘JEE Application Server’, (1,1), ‘AutoInc-Req-QP01’}

•  Resource Requirement= {‘AutoInc-Req03’, ‘MySQL DB’, (2,2), ‘AutoInc-Req-QP02’}

•  ……

•  Policy Section •  Resource Constraint = Ethernet Exists Only” •  Resource Constraint = “Synchronous Communication is absent ” •  QoS Inv Profile = AutoInc-Inv-QP01 •  Policy Inv Profile = AutoInc-Inv-PP01

<<Policy Profile >> AutoInc-Off-PP01

•  Price/month = 10000 euros for <= 500 vehicles

•  Used only in the Netherlands •  All Dutch legal and tax issues are applied

<<QoS Profile>> AutoInc-Req-QP02

• Response time <= 3 s • Throughput >= 80 req/s

Example of a Virtual Resource Network

28

AutoInc-Blueprint

Directed Graph - Vertexes •  Service Offering •  Implementation Artefact •  Resource Requirement - Edges •  Abstract Resource Link •  Horizontal Link •  Vertical Link

VehicleMgt-SaaS

Data.zip App.war

2AutoInc-Req01 JEE App Server with Servlet Container -

PaaS

AutoInc-Req04 3Gbit Network Link

- IaaS

AutoInc-Req02 Relational Database

- PaaS

2

AutoInc-Req03 Context-as-a-Service- SaaS

-  Horizontal Link: a functional dependency -  Vertical Link : a deployment dependency -  AbstractResourcekLink: connection to an abstract resource


Blueprint Mgt Language: Unary Blueprint Operators

Operator Name

CreateBlueprint GetBlueprintByID GetBlueprintByProperties ModifyBlueprintProperties

GetProperty

DeleteBlueprint


BML - Binary Operators

Operator Name CompareBlueprintProperties

CompareBlueprints - Compare two blueprints

MergeBlueprintProperties - merge selected blueprint properties

SplitBlueprint - split a blueprint into smaller reusable blueprints

ComposeHorizontally - compose two or more blueprints at the same cloud stack level, e.g., SaaS to SaaS, PaaS to PaaS.

ComposeVertically - compose two or more blueprints at adjacent cloud stack levels, e.g., compose SaaS with PaaS, PaaS with IaaS. ResourceLink - Return the resources that will be claimed by this blueprint


Blueprint Predicates (BP)

Resource Utilization Constr.

SLA/QoS constraints

Example • FP1: ((Servlet 2.5 Container Exists ) Runs On (Intel Dual Core 2Ghz Exists))

• FP2-: Composition Engine )Exists

• FP4: Network Link 2Gbit Exists

• FP5-Link 2:N etwork Link 2Gbit Exists

• FP6-Link 3 2 Network Links 3Gbit Exists

Example • NFP1: Throughput >= 100 req/s

• NFP2: Availability >= 98% on 24/7

Security/Compliance const.

Example • RP1:use WS-Security & XML-Digital Signature

BCL is grounded on: •  Linear Temporal and Monoidal t-‐norm based Logic (LTL/MTL)

•  Compliance paLerns.

Deployment/Data residency constraints

Is composed of

Example • RP1: Only used in the Netherlands



The CRL in BCL is designed for: •  the formal specifica7on of compliance requirements. •  enabling automa7c design-‐7me compliance verifica7on. •  Grounded on:

•  Temporal logic; Linear Temporal Logic (LTL/MTL) •  Compliance paLerns.

•  Supports non-‐monotonic requirements to relax rules and handle excep7onal situa7ons.

•  CRL is an open extensible language.


Blueprint Example: Interactive Telco Services

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Cloud Compu7ng and Rendering

•  High quality of video & services –  Bandwidth availability -‐higher priority to game traffic during network boLlenecks

–  Video encoding is computa7onally demanding

•  Low latency for interac7ve applica7ons –  Real 7me new view rendering at the browser client end –  Adap7ve Stream management to handle user requests and network loads


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Interac7ve Mobile Video Gaming

Server

Internet

Video Encoding

Clients

Full-‐frame Rendering

CG applica7on

Out of resources!

Bandwidth: 2-‐6Mbit per client

CG app controls the shape, appearance, and mo7on of objects drawn using programmable graphics hardware.

Michael P. Papazoglou © Keynote: “Australian Symposium on Services Innova7on”, 21-‐22 November, Wollongong, Australia.

Video Decoding

Video Decoding

Video Decoding

Gaming app Integrating Iaas/Paas/Saas Components

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Image Cache

Data-‐base

Authen0ca-‐ 0on

Mobile Client

On line Rendering

Storage

Mobile Client

On line Rendering

Authen0ca-‐ 0on

Data-‐base

SaaS-‐view

PaaS-‐view IaaS-‐view

Image Cache Storage


Blueprints for Interactive Video Application

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Au * PlaPorm Descrip7on * -‐  API -‐  Endpoint -‐  Authen7ca7on conf.

* Infrastructure Descrip7on *

* Policies Descrip7on *

* Infrastructure Descrip7on *

* Policies Descrip7on *

* Constrained Infrastructure Descrip7on * − Medium size VM

* Policies Descrip7on * − Es7mate avg delay – if delay goes below 100 ms migrate to other IaaS − 99.999 % availability

* Applica7on Descrip7on * − Metrics: …

* Infrastructure Descrip7on * − Medium size VM − Medium storage

* Policies Descrip7on * − Deploy with rendering service − Use Amazon’s autoscale

* PlaPorm Descrip7on * − Beanstock

* PlaPorm Descrip7on * API -‐ Endpoint -‐ Database conf.

* Applica7on Descrip7on * − Metrics: delay, availability .. − Loca7on: URI − Version: … − Package: caching service − Environment: servlet

Authen0ca0on service BP

Rendering service BP

Caching service BP

Database service BP

Authen7ca7on Configura7on

Authen7ca7on Configura7on

DB Configura7on

DB Configura7on IaaS

Configura7on

-‐ Medium VM -‐  Large storage capacity

Check dependencies

Deploy

Deploy

Horizontal configura7on points Ver7cal configura7on points Exposure of horizontal parameters Externally enforced by

IaaS provider

DML composi0on point


Closing Remarks

Closing Remarks

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•  Contemporary cloud technologies are fraught with problems. New technologies are required to support the mgt of clouds and allow for the dynamic deployment and management of services.

•  Blueprin7ng allows cloud crea7ng cloud forma7ons dynamically

to comprise an arbitrary assembly of virtual cloud services (business processes, virtual plaPorms, virtual machines, & virtual storage volumes) connected into whatever design of IT service-‐based applica7on & associated infrastructure a customer desires. –  It provisions cloud services, effec7vely manages workload segmenta7on and portability, and supports cloud architectures that automa7cally manage the lifecycle of cloud services, par77on work & op7mize workload distribu7on.


References

1. M.P. Papazoglou and W.J. van den Heuvel, “Blueprin7ng the Cloud”, IEEE Internet Compu7ng, Nov/December 2011.

2. M.P. Papazoglou and M. Vaqueros “Knowledge-‐Intensive Cloud Services: Transforming the Cloud Service Stack”, in Knowledge Service Engineering Handbook, CRC Press, Taylor & Francis Group, 2012.

3.  Distributed Management Task Force “Interoperable Clouds”, White Paper CIM Version 1.0, document DSP-‐IS010, November 2009, available from: hLp://www.dmP.org.

4.  A. V. Konstan7nou et. al. “An Architecture for Virtual Solu7on Composi7on and Deployment in Infrastructure Clouds”, 3rd Interna7onal Workshop on Virtualiza7on Technologies in. Distributed Compu7ng, June 2009, Barcelona, Spain.

5.  T.C. Chieu et. al. “Solu7on-‐based deployment of complex applica7on services on a Cloud”, Interna7onal Conference on Service Opera7ons and Logis7cs and Informa7cs, Qindao -‐ China, IEEE CS, August 2010.

6.  F. Galan et. al., “Service Specifica7on in Cloud Environments Based on Extensions to Open Standards”, 4th Interna7onal Conference on Communica7on System Soxware and Middleware, June 2009, Dublin, Ireland.

7.  A. Elgammal, O. Turetken, W.J. van den Heuvel, M.P. Papazoglou, “Root-‐Cause Analysis of Design-‐7me Compliance Viola7ons on the basis of Property PaLerns”, 8th Interna7onal Conference on Service-‐Oriented Compu7ng, San Francisco, December 2010.

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