INFO5011. Cloud Computing Semester 2, 2011 Lecture 3, Cloud Computing Service Models

Transcription

1 INFO5011 Cloud Computing Semester 2, 2011 Lecture 3, Cloud Computing Service Models

2 Outline Recap of cloud computing servicing models SaaS architecture consideration IaaS and PaaS comparison 2

3 cloud computing Service models Recap the cloud computing definition by US goverments National Institute of Standard and Technology - Cloud computing is a model for enabling ubiquitous, convenient, ondemand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) Lower-level, Less management IaaS PaaS Higher-level, More management SaaS EC2 Azure AppEngine Force.com GoogleApps, SalesForce Utility computing 3

4 You manage You manage You manage Clouds servicing models Private (On-Premise) Infrastructure (as a Service) Platform (as a Service) Software (as a Service) Applications Applications Applications Applications Runtimes Runtimes Runtimes Runtimes Security & Integration Databases Servers Virtualization Server HW Storage Networking Security & Integration Databases Servers Virtualization Server HW Storage Networking Managed by vendor(s) Security & Integration Databases Servers Virtualization Server HW Storage Networking Managed by vendor(s) Security & Integration Databases Servers Virtualization Server HW Storage Networking Managed by vendor(s) Diagram from Azure Academic Materials Syllabus, Prepared by David S Platt, Harvard University Extension School, dplatt@fas.harvard.edu 4

5 Software As a Service - Software as a Service (SaaS): The consumer uses an application, but does not control the operating system, hardware or network infrastructure on which it's running. - Applications are restricted to business applications or applications that may normally installed in a business network or personal computer - Examples - Business applications: CRM solutions from salesforce.com - Business/Personal applications: Gmail, Google Doc, etc. 5

6 PaaS - Platform as a Service (PaaS): The consumer uses a hosting environment for their applications. The consumer controls the applications that run in the environment (and possibly has some control over the hosting environment),but does not control the operating system, hardware or network infrastructure on which they are running. The platform is typically an application framework. 6

7 IaaS Infrastructure as a Service (IaaS): The consumer uses "fundamental computing resources" such as processing power, storage, networking components or middleware. The consumer can control the operating system, storage, deployed applications and possibly networking components such as firewalls and load balancers, but not the cloud infrastructure beneath them. Cloud Server and Data Center Map: 7

8 SaaS in the news Gartner Says Worldwide Software as a Service Revenue Is Forecast to Grow 21 Percent in 2011, July 7, 2011 Worldwide software as a service (SaaS) revenue is forecast to reach $12.1 billion in 2011, a 20.7 percent increase from 2010 revenue of $10 billion, according to Gartner, Inc. The SaaS-based delivery will experience healthy growth through 2015, when worldwide revenue is projected to reach $21.3 billion. "After more than a decade of use, adoption of SaaS continues to grow and evolve within the enterprise application markets. Initial concerns about security, response time and service availability have diminished for many organizations as SaaS business and computing models have matured and adoption has become more widespread Customer relationship management (CRM) continues to be the largest market for SaaS. SaaS revenue within the CRM market is forecast to reach $3.8 billion in 2011, up from $3.2 billion in Gartner expects SaaS to represent nearly 32 percent of the CRM market's total software revenue in

9 Microsoft Takes to Cloud to Ward Off Competition New York Times, June 27, 2011 SaaS in the news Mr. Conophy, the chief information officer of the InterContinental Hotels Group, decided earlier this year to begin moving nearly all the company s 25,000 office workers off Microsoft s and Office productivity applications and onto Google s Web-based alternatives. Halting such defections is a top priority at Microsoft. Its response arrives Tuesday, when the company begins selling Office 365, a cloud-based version of Microsoft s , whiteboard collaboration software and word processing, spreadsheet and presentation programs. At $50 a year, Google s pricing seems far more appealing than the standard price for the Office PC software, from $200 to about $400, depending on features. Office 365 prices are from $2 per user a month to $27 per user a month. With cloud-based versions of Word, Excel and PowerPoint, plus several new communications and collaboration tools, that offering could be quite appealing, analysts say. The price, at $72 a year, is somewhat above Google s, but it carries the Microsoft name and familiarity. 9

10 SaaS Motivations SaaS, sometimes know as on-demand computing, internet as a platform, seems like a return to the old terminal and time-sharing system model. Incentives for giving up lots of control (individual users, organizations) - Software must be installed and configured then updated with each new release - Infrastructure, OS and low utilities must be maintained - Every update to the OS sets off a cascade of subsequent revisions to other programs - For SaaS users, WEB BROWSER is like an OS Incentives for providing taking up lots of controls (providers) - Software sold or licensed as a product must be able to cope with a baffling variety of operating environments - SaaS software runs on platform of the vendor s choosing - Updates and bug fixes are deployed in minutes - Brian Hayes Cloud computing. Commun. ACM 51, 7 (July 2008),

11 Line-of-business services Two major categories of software as a service - offered to enterprises and organizations of all sizes. Line-of-business services are often large, customizable business solutions aimed at facilitating business processes such as finances, supply-chain management, and customer relations. These services are typically sold to customers on a subscription-basis. Consumer-oriented services - offered to the general public. Consumer-oriented services are sometimes sold on a subscription-basis, but are often provided to consumers at no cost, and are supported by advertising. Slides are based on Frederick Chong and Gianpaolo Carraro, Architecture Strategies for Catching the Long Tail, Microsoft Corporation, April 2006 Accessible from: unless stated otherwise 11

12 Providing SaaS 12

13 Changing the business model Shifting the "ownership" of the software from the customer to an external provider. Reallocating responsibility for the technology infrastructure and management that is, hardware and professional services from the customer to the provider. Reducing the cost of providing software services, through specialization and economy of scale. Targeting the "long tail" of smaller businesses, by reducing the minimum cost at which software can be sold. 13

14 Selling to the long tail The Amazon long tail 14

15 Line of Business software long tail Traditional on-premise software model SaaS model 15

16 Most important attributes for SaaS architecture - Scalable - Multi-tenancy - Configuration Application architecture - Metadat based configuration instead of code based customization. Multi-tenancy and isolation may work at different level for different service models - Tenant can be a single consumer or a large organization 16

17 The Software as a Service Maturity Model 17

18 Level I: Ad Hoc/Custom SaaS Maturity levels - The first level of maturity is similar to the traditional application service provider (ASP) model of software delivery, dating back to the 1990s. Customized instance. Level II: Configurable - At the second level of maturity, the vendor hosts a separate instance of the application for each customer (or tenant). Same instance, configured to suit different customers Level III: Configurable, Multi-Tenant-Efficient - Only has the scale up option Level IV: Scalable, Configurable, Multi-Tenant-Efficient - Multiple instances; not 1:1 mapping; easy to scale out 18

19 Higher level architecture 19

20 Metadata services the metadata service provides customers with the primary means of customizing and configuring the application to meet their needs. Typical areas include: - User interface and branding - Workflow and business rules - Extensions to the data model - Access control 20

21 Dedicated Tenant Database Multi-Tenant Data Model - Using metadata to keep track of which database belongs to which tenant Shared database, fixed extension set Shared database, custom extension set 21

22 force.com data storage example Figure 4. Example of single flex column Figure 3. Force.com s data definition and storage model Diagramsfrom Craig D. Weissman, Steve Bobrowski, The Design of the Force.com Multitenant Internet Application Development Platform. In SIGMOD 09 22

23 Scaling the application - Design the application to run in a stateless fashion - Design the application to conduct I/O operations asynchronously Scalability scaling out - Pool resources such as threads, network connections and database connections - Write the database operations in such a way as to maximize concurrency and minimize exclusive locking Scaling the data - Partitioning and repartitioning - force.com partition based on tenant 23

24 Operational structure What it takes to deliver the application to customers and to keep it available and running well at cost-effective level - How many 9s in uptime Shared services - Accurately track customers' usage, and bill them for time or resources used. - Restrict or throttle access at certain times of the day, or in order to meet other criteria. - Monitor site access and performance, to ensure that SLAs are being met. - Perform other functions in order to ensure a seamless experience for your customers that meets or exceeds expectations. 24

25 Shared services Operational support services (OSS) Handle operational issues such as account activation, provisioning, service assurance, usage, and metering. Business support services (BSS) Support billing (including invoicing, rating, taxation, and collections) and customer management (which includes order entry, customer self services, customer care, trouble ticketing, and customer relationship management). 25

26 The line between PaaS and IaaS is fuzzy There are lots of services lie in between PaaS and IaaS or utility services - Many classic IaaS service providers provide computing and storage as separate services - Amazon EC2 and S3 - Rackspace Cloud Server and Cloud File - Microsoft Windows Azure Virtual Machine/compute and storage - There might be other storage options - Amazon EBS, SimpleDB, RDB, Microsoft SQL Azure Database - There might be other utility type of services for networking, messaging and so on - Amazon Simple Queue Services, Amazon Virtual Private Cloud, Microsoft virtual network, CDN, 26

27 Commonalities among major service providers Common services - Elastic compute cluster - Persistent storage - Intra-cloud network - Wide-area Network Comparisons as reported in the paper Provider Elastic Compute Storage Wide-area Network AWS Xen VM SimpleDB(table), S3(blob), SQS(queue), RDS(Relational) 3DC locations Azure Azure VM XStore(table, blob, queue) SQL Azure Database (Relational) 6DC locations (2 each in US, EU and Asia) AppEngine Proprietary sandbox DataStore(table), BlobStore (Blob) Unpublished number of Google DC Slides are based on CloudCmp: comparing public cloud providers. Ang Li, Xiaowei Yang, Srikanth Kandula, and Ming Zhang. In Proceedings of the 10th annual conference on Internet measurement (IMC '10) unless stated otherwise RackSpace Xen VM CloudFiles (blob) 2DC locations (all in US) 27

28 Elastic Compute Cluster - Pricing: Elastic Compute Cluster - AWS, Azure and CloudServers charge based on how long an instance remains allocated - AppEngine charges based on how many CPU cycles a customers application consumes - Elastic implementation - Opaque scaling (AWS, Azure and CloudServers) - Manual or policy based - Transparent scaling (AppEngine) - Automatic, - Performance Metrics - Benchmark finishing time - Cost - Scaling latency 28

29 An example of Amazon s scaling mechanism Jeff Barr, Host Your Web Site in the Cloud, published by Sitepoint,

30 Persistent Storage - Table: Relational and non-rational (NoSQL) Persistent Storage Mechanisms - Blob: Binary Large Object, such as image or video; binary data are stored in a bucket with metadata (label on the bucket) that allows one blob to be distinguished from another - Queue: A classic first-in, first-out data storage structure used used primary for passing data from one computing job to another in a loosely-coupled fashion Mechanism Operation Description Table get put query Fetch a single row(object) Insert a single row(object) Lookup rows(objects) that satisfy certain condition Blob download upload Download a single blob Upload a single blob Queue send receive Send a message to a queue Retrieve the next message from a queue 30

31 Amazon S3 - Buckets, objects and keys Blob Storage - A bucket is a container for objects stored in Amazon S3; Bucket names are drawn from a global namespace; Each S3 account can have a limited number of buckets - Objects are the fundamental entities stored in Amazon S3. Objects consist of object data and metadata. - Each object has a key to identify itself within a bucket. - Object are addressable - Microsoft Azure Blob Service has similar container/blob structure

32 Persistent Storage Pricing & Performance Metrics Storage pricing are based on of three type of costs - Storage, executing request, network transfer - S3/Azure Storage Service/Cloud File charge fixed per request cost - SDB/DataStore: charge cpu cycles used to carried out the requests - A complex query costs more than a simple one Performance Metrics - Operation Response Time - Time to Consistency - Cost Per Operation 32

33 A large cloud provider often operates several data centers - Intra-datacenter traffic within a data center is not charged Intra-cloud network - Inter-datacenter traffic is charged based on the volume crossing the data center boundary Performance metrics - Path capacity measured by TCP throughput - Path latency 33

34 Wide-area Network Wide-area network in this paper is defined as the collection of network paths between a cloud s data centers and external hosts (most likely where client app runs) Performance metrics - Optimal wide-area network latency - Initial requests from PlanetLab nodes, compute the minimum latency between a PlanetLab node and any data center owned by a provider PlanetLab currently consists of 1080 nodes at 532 sites. Diagram from 34

35 Implementation Computation Metrics - The purpose of benchmark tasks to stress various aspects of the compute infrastructure offered by cloud providers - Modify a standard Java based benchmark to suit all cloud services - The benchmark consists of CPU/memory/and IO intensive tasks respectively Storage Metrics - Various data size - Java client to test typical storage APIs - Use persistent HTTP to avoid initial SSL handshake and TCP set up time - Also provide other language client Network metrics - Standard tools like iperf and ping - For intra-cloud network performance, allocate a pair of instances in the same or different data centers and run these tools - For wide-area network performance, instantiate an instance in each data center owned by the provider and ping them from 200+ PlanetLab nodes. 35

36 Results on CPU Same performance regardless of instance type! Maybe explained by the CPU sharing policy of C2, where a virtual instance can fully use all physical CPUs on a machine if there is no contention $0.085/h (<1) $0.34/h (2) $0.64/h (4) $0.015/h $0.03/h $0.12/h (1) $0.24/h (2) $0.48/h (4) $0.96/h (8) $0.06/h $0.12/h 36

37 Results on IO 37

38 Results on scaling latency Windows instance takes longer time to create than Linux one Same provisioning time, different booting time; maybe caused by mismatch between cpu and windows code base Same booting time, different provisioning time; may be caused by various hardware infrastructure 38

39 Persistence storage (table) result The difference in query performance may be caused by indexing strategies on non-key columns 39

40 Intra-datacenter performance 40

41 Wide-area Network 41

42 Realworld application results The paper also deploy several real world application on different cloud providers to confirm the result obtained by CloudComp E-Commerce Website Parallel Scientific Computation Latency Sensitive Website 42

43 Discussion question Grid computing vs. Cloud computing Multi-tenancy and isolation levels 43

44 Resources SaaS directory Google DataStore: Ang Li, Xiaowei Yang, Srikanth Kandula, and Ming Zhang. CloudCmp: comparing public cloud providers. In Proceedings of the 10th annual conference on Internet measurement (IMC '10). ACM, New York, NY, USA, Frederick Chong and Gianpaolo, Architecture Strategies for Catching the Long Tail. Carraro, Microsoft Corporation, April