2012 IEEE Eighth World Congress on Services Cloud-Oriented Platforms: Bearing on Application Architecture and Design Patterns Balwinder Sodhi and T.V. Prabhakar Dept. of Computer Science and Engineering, IIT Kanpur, UP 208016 India {sodhi, tvp}@cse.iitk.ac.in important architectural properties of the computing platform and that of its constituent components? c) How can the above properties be leveraged systematically to address different business problem scenarios? In this paper we address the above mentioned points. We bring out architecturally signiﬁcant properties of various computing platforms and their key underlying components. Also, we bring out the implications of such properties for the design and architecture of the applications. We then demonstrate how this knowledge can be used to device design patterns which address certain commonly occurring business problem scenarios. This paper is organized into ﬁve sections. In Section II we discuss related work pertaining to the area of presented work. Various computing platforms are examined in detail, from the application architecture viewpoint, in Section III. In Section IV we propose a novel architectural design pattern called Platform Level Aspect-Orientation and describe an example implementation of it. We conclude this paper in Section V. Abstract—The business problems that are handled by today’s computing systems have grown much in complexity. Handling data volumes in excess of peta-scale are no longer restricted to few narrow application areas. Computing platforms ecosystem has also advanced with virtualization based and cloud oriented platforms emerging as most disruptive ones. Unique characteristics of such platforms have important implications for how the architecture of business applications is designed – particularly the ability to achieve certain non-functional requirements. In this paper we ﬁrst bring out properties of the said computing platforms that are architecturally signiﬁcant from business applications’ view point. We then bring out implications that such properties have for software design and architecture. We demonstrate the use of this knowledge about platform properties by devising a novel architectural design pattern “Platform Level Aspect-Orientation” which can be used to address a variety of application scenarios. Index Terms—Software Architecture Design, Non-functional Requirements, Design Patterns, Quality Attributes, Cloud Computing, Virtualization I. I NTRODUCTION Experience shows that the design and analysis skills alone are not sufﬁcient for evaluating and synthesizing the application architectures. It is critical to deeply understand the key properties of target computing platforms and impact of such properties on functional and non-functional aspects of the system. It has been observed that the computing devices have continuously improved in their abilities over past several years. Virtualization and cloud oriented platforms have made it possible to harness the improved hardware capabilities. From perspective of the consumers, monetary and operational factors have been the major drivers for accelerated adoption of cloud oriented computing platforms. The argument of converting capital expenditure to operational expenditure by enterprises is now well known in this regard. On the other hand, primary concerns of the providers have been around optimization of different resources (both software and hardware) in a virtualized and multi-tenant environment like cloud. Majority of the literature in this area today is centred around one of these two extremes. From perspective of the application architect and other technical stakeholders who are seeking to design, build and maintain software systems on/for cloud and virtualized platforms, there are questions that still remain inadequately answered. For example: a) Is designing the architecture of a software system same as for a non-cloud environment? b) From the viewpoint of a candidate application, what are 978-0-7695-4756-5/12 $26.00 © 2012 IEEE DOI 10.1109/SERVICES.2012.49 II. R ELATED W ORK Majority of the reported work in literature deals with very speciﬁc aspects of cloud and virtualization based computing platforms. For instance, the architectural requirements of various types of cloud platforms have been discussed by Rimal et. al. [1]. They have attempted to classify these platforms according to the requirements of different stakeholders and also analyse the architectural features of cloud computing. A decomposition of the cloud into main ﬁve layers, and exploration of the interrelations between these layers as well as their inter-dependency on its constituent components has been discussed by Youseff et. al. [2]. Oliveira et. al. [3] apply taxonomy techniques in the cloud computing domain from an e-Science perspective. On the other end of spectrum are cloud vendors who provide white papers and other technical literature about their speciﬁc offerings. For instance Amazon Web Services (AWS) has a range of documentation [4], [5] that describes how to solve different types of business problems by using their different offerings. Particularly, [4] illustrates different aspects of building applications by leveraging the services available in the Internet cloud. Similarly literature exists for others such as Azure [6], [7]. An interesting discussion of application types that are suitable 409 278 is a software representation of a physical computer. Virtualization decouples the OS from physical hardware resulting in better operational ﬂexibility and utilization of the underlying hardware. A VM is executed by the Virtual Machine Monitor (VMM) on a physical hardware shared with other VMs. Often the applications running on a VM cannot tell (or care) whether they are running inside a VM instead of a dedicated physical machine. From implementation standpoint, there are two main types of virtualization: a) OS based as in Solaris containers [15], and b) Virtual Machine Monitor (VMM) based as in Xen [16]. There are further sub-categories of the VMM based virtualization: bare metal (a.k.a Type-1) and hosted (a.k.a Type-2) [17]. Then there can also be VMMs that are designed to take advantage of special purpose hardware features such as of recent Intel processors [18]. We examined the internals of major virtualized platforms such as [15], [16], [18]–[21] and brought out their key architectural properties. Among such properties some are common across different kinds of virtualized platforms whereas some are platform speciﬁc. The properties that are common to different kinds of virtualized platforms are as below: i. Abstraction of physical hardware resources as software entities. ii. Abstraction of the hardware interface APIs (e.g. VMware’s products export an x86-based computer). iii. Coarse grained computing environment isolation and VM level multi-tenancy. iv. Poor performance isolation, i.e., VMs sharing an underlying hardware fabric can interfere with each other’s performance. v. Encapsulation of all software that runs on the physical hardware vi. Limited hardware control capabilities for VMs (e.g. cannot control host power management). vii. VM check-pointing via snap shots. viii. VM migration (both live and ofﬂine). OS based virtualized platforms have the following important properties: i. Isolation of VMs is deﬁned in software under a shared OS/kernel instance. ii. Root privileged tasks (e.g. loading a device driver, changing IP in a VM) need to be performed in the host OS, or the application has to be modiﬁed to work in a VM. iii. Applications use the OS’s normal system call interface instead of emulation or via VMMs. iv. A VM cannot have a guest OS (or in some cases even kernel) different from the host one. v. Often it uses ﬁle-level copy-on-write mechanisms instead of the block-level copy-on-write schemes common on VMM based environments. As discussed in the Section III-B, most of the above properties of the virtualized computing platforms have found innovative application in the development of cloud oriented computing platforms. They also allow for very interesting for cloud computing, and also some patterns and scenarios have been described in [6]. All of these works present interesting treatment of different but focussed areas related to cloud computing platforms. To an architect or a software designer, who seeks to leverage the unique technical capabilities offered by such computing platforms, they do not provide adequate insights about architecturally signiﬁcant aspects of these platforms. For instance, they do not adequately discuss the architecturally signiﬁcant properties of different types of resource virtualization which forms the heart of entire cloud computing ecosystem. The said works also do not address issues of how to leverage such properties of the platforms for solving variety of software architecture problems. In this regard, there are questions without adequate and clear answers. Some of the important ones are: i. From perspective of an application, what are the architecturally signiﬁcant properties of a computing platform and that of its constituent components? ii. What application design paradigms a computing platform encourages and is designed for? iii. How do the above two points impact various functional and non-functional aspects of a candidate application? iv. Does existing software design and architecture body of knowledge applies as-is to cloud and virtualized computing platforms? The aim of the presented work is to address the above mentioned gaps. III. A RCHITECTURAL P ROPERTIES OF C OMPUTING P LATFORMS The set of concepts, components and design paradigms which forms the core of an application’s development and deployment environment is termed as a computing platform in this paper. We are primarily focussing on two categories of computing platforms viz. Virtualized and Cloud oriented. Each of these platforms have further sub-categories and they all have unique properties. In sections that follow, we bring out the such architectural properties of the said platforms. These properties have important implications from application architecture and deployment perspective; concept map shown in Fig. 1 depicts this context. We examined in detail the software architecture and best practices knowledge from [8]– [14] for determining the implications of such properties for the application architecture. In Section IV, we demonstrate the use of this knowledge about architecturally signiﬁcant properties of computing platforms in devising a novel architectural design pattern for addressing certain types of application scenarios. A. Virtual Machine Based The term virtualization is applicable to a broad set of entities such as hardware resources like devices, servers and networks, and to software entities like operating systems and applications. Central entity is a Virtual Machine (VM) which 279 410 Fig. 1. Computing platforms and bearing on architecture: Problem context viii. Sub-optimal billing mechanisms. Users are billed on asused basis. ix. Sub-optimal metering techniques. Related to performance isolation limitations of the VMMs. x. Lack of detailed and ﬁne grained resource monitoring mechanisms. A limited set of log traces generated by the VMM while executing your VM are provided. xi. Difﬁcult to assess software licensing structure, especially in complex deployment scenarios where multiple licenses of different software are used in a single environment. xii. Potential to abuse the relative anonymity behind acquiring and usage models for cloud services. and useful applications in modern data centres as well as in personal computing environments. B. Cloud Oriented Virtualization technologies form the core of entire cloud computing ecosystem. Hence all the properties of virtual computing platforms that we brought out in Section III-A are also available on the cloud oriented computing platforms. There are additional properties such as self service and automation of resource provisioning and management etc. that cloud oriented computing platforms provide. Therefore, the computing platform capacity can be elastic in nature and can expand without manual intervention in response to the application’s changing demands. The manageability and operational aspects of the cloud oriented platforms are the key differentiators w.r.t. the plain virtualized computing platforms. [22], [23] provides the detailed treatment of the deﬁnition and highlights of an Infrastructure/Platform/Software as a Service (XaaS) delivery models. It also explains that what is commonly understood by various deployment models such as private, public, hybrid and community of the cloud computing. Therefore, the focus in this paper is mainly on those architectural properties of such models as are relevant from the viewpoint of an application which one is seeking to build for cloud deployment. In the presented work, various features and available implementation details of different cloud platforms [24]–[31] have been explored to identify their key properties. The resultant list of such properties of the cloud oriented computing platforms, as relevant for an application’s design is: i. Elastic nature of computing resources. ii. Ability to automate provisioning tasks. iii. Self-service provisioning. iv. Measured service. v. Computing as a utility accessible over the network. vi. Lack of standards for key services such as security, VM control and management among others. vii. Lack of absolute control on data and computing assets custody. Please note that only those properties that are not speciﬁc to any particular service or deployment model of cloud oriented platform are shown in the above list. The model speciﬁc properties are discussed as below. IaaS Cloud Speciﬁc: An IaaS cloud platform provides raw computing infrastructure in the form of a VM, some virtual storage and networking. i. Cloud user is responsible for installing and managing all the software on the VM. ii. Allows resource utilization monitoring and reacting to different types of platform level events. iii. Applications running in the VM are responsible for dealing with the reactions to above mentioned events. For instance, a conﬁgured reaction for a “CPU utilization threshold reached event” may be to add more instances of the VM. It is then expected that the architecture of the application(s) running on the VM allows to harness the newly added VM’s capacity. iv. Limited control on networking components, e.g. host ﬁrewalls. v. Concerns, such as of security and isolation guarantees, arising out of shared underlying components (e.g. virtualization layer). PaaS Cloud Speciﬁc: i. No control of underlying infrastructure (network, servers, operating systems, or storage). 280 411 We brought out important architectural properties of different platforms in Section III. For instance, the most important property of virtualization based platforms is their ability to provide software abstractions for hardware resources. Among other things, this property allows the VMs to be programmatically examined, controlled and saved like a ﬁle. It helps achieve isolation and multi-tenancy at platform level. Fig. 2 makes this point more clear where it is shown side-byside with the process and thread level isolation semantics. Such properties of virtualization based platforms have greatly inﬂuenced the architecture of cloud based platforms. We would like to note that some of the properties of various platforms are very fundamental to that platform and are permanent, while there are few properties that may change with advancements in respective state-of-the-art. For instance, the software abstraction of hardware resources is a fundamental property. On the other hand, properties like poor performance isolation and limited hardware control, may eventually become less signiﬁcant with advances in respective state-of-the-art. As such, the leverage that an application architect can derive from different properties will vary in purpose and effect. 1) Implications for an Architect: It is important to note that, except in cases of special purpose VMMs, an application itself is often unaware of the fact that the underlying hardware resources that it is using are virtual. Therefore, the application architects have to design application architecture in such a manner so as to leverage the unique properties afforded by such computing platforms. He/she needs to follow the usual architecture design methods to ensure that the system’s functional and non-functional requirements are properly addressed. The main difference is that now the said platforms have brought in more properties that the architect may exploit and/or have to consider during design decisions. For instance, the architect can possibly leverage elastic nature of computing resources on an IaaS cloud to throw in more capacity dynamically at runtime when the application demands it, thus making the scaling easier. However, merely deploying an application on a cloud based platform will not automatically make it scalable. Suitable architectural patterns that harness the properties of target cloud oriented computing platform, have to be utilized (or crafted) by the architects in order to achieve desired QAs. We observe that best beneﬁts from the said virtualization and cloud based platforms can be derived if applications exhibit the following characteristics: i. Parallelism to allow partitioning the computation work. ii. Business logic is stateless and have semantic interoperability with collaborating components. iii. Have loosely coupled and modular components. iv. Designed to be service oriented. Clearly, the architectural properties of platforms as discussed in previous sections can serve as additional building blocks for software architects to exploit. In the following we leverage our ﬁndings about the platform properties for devising an architectural design pattern which addresses a variety of application scenarios. ii. Can control deployed applications and possibly its hosting environment conﬁgurations. iii. Allows only provider supported programming languages, tools, APIs and components to build applications. SaaS Cloud Speciﬁc: i. No control of underlying infrastructure (network, servers, operating systems, storage, or individual application capabilities). ii. Allows control of a limited set of user-speciﬁc application conﬁguration settings. Private Cloud Speciﬁc: i. Operated solely for one organization. ii. Total ownership, control and custody of applications, data and computing assets. iii. Allows custom conﬁgurations of cloud infrastructure. iv. Often has a homogeneous virtualization environment. Public Cloud Speciﬁc: i. Cloud infrastructure is made available to the general public for a fee. ii. Ownership of cloud infrastructure lies with the organization who is selling cloud services. iii. Cloud service provider has the custody and control of applications, data and computing assets hosted on cloud. iv. Often has homogeneous virtualization environment. Community Cloud Speciﬁc: i. Cloud infrastructure is shared by several organizations. ii. Supports a speciﬁc community that has shared goals/concerns. iii. Member organizations have total ownership, control and custody of applications, data and computing assets. Hybrid Cloud Speciﬁc: i. A logical arrangement that combines two or more disparate clouds (private, community, or public). ii. Each constituent cloud remains a unique entity retaining its own properties. In the subsequent sections we discuss implications of the above said platforms’ properties from software architecture perspective. IV. B EARING ON A PPLICATION A RCHITECTURE AND D ESIGN PATTERNS The ability of any software system to achieve certain quality is determined by a) Properties of the underlying platform on which the system is built b) How the said properties have been harnessed (or mitigated) when designing architecture of the system. Clearly, if a host platform on/for which an application is being built, does not possess the properties required for ensuring a QA, then that QA in the application gets adversely impacted. For instance, if multitasking (e.g. via threads) is not supported on a platform, performance of applications built on/for that platform will suffer. Therefore, host platform properties inﬂuence the architecture of an application which is built on such a platform. 281 412 Coarse Finer Isolation granularity A single threaded process VM Data VM Applications Disk Files Registers VM Process Files Process CPU Threads in a process A single threaded process Stack Process Network Data Files Registers Registers Stack Stack Code Code Memory Virtual Hypervisor Disk NIC Processor Memory Physical Hardware Fig. 2. Multi-tenancy and isolation models actions has been a limitation of the physical systems. For example, one cannot programmatically add a new application server instance when the capacity of the existing application server farm has peaked out. Forces: In keeping with the space requirements and readability of this paper, we have used a concise format to describe only the key elements of the pattern. The pattern description explains the problem context, forces and the solution. Platform Level Aspect-Orientation – Cross-cutting concerns exist at computing platform level. For example, software and hardware resource monitoring and automatic control. – In a physical computing platform it is difﬁcult to programmatically monitor and react to the events arising at platform level. – The corrective and control actions for physical computing platforms can be slow or even impossible in some cases. Problem Context: There are software design and implementation concerns which apply at the coarse-grained computing environment/platform level, and they cut across the applications. Examples of such cross cutting platform level concerns: – Monitoring and reacting to the attacks happening on a computing environment. – Auditing, logging and monitoring of critical system indicators including the application level ones and reacting to them. – Resource billing and quota enforcement. – System level management and operations policy compliance. – Auto-scaling events for computing resources. – Automated disaster/failure recovery. The concerns listed above are valid or applicable at the entire computing environment level. Primary issue is that with most physical computing environments it is difﬁcult to programmatically react to the events arising at the platform level. Some of the examples of such events are: CPU, memory, disk and processing load on a system etc. reaching certain threshold. Other examples of such scenarios include specialized system level monitoring and control requirements. Even though the abilities to monitor such events has existed since long, the lack of capabilities that allow reacting to such events in an automatic/programmatic manner so as to take corrective Solution: Closer examination of the problem context and forces reveals that, conceptually, the problem scenario has similarities with the Aspect Orientation (AO) paradigm [32]. Focus in case of AO paradigm is mainly on the crosscutting concerns at individual program level. The strength of AO paradigm lies in encapsulating the crosscutting artifacts and completely keeping them separated from business logic to enable their reuse. However, in the scenario at hand, the crosscutting concerns are applicable at a much coarser level and across applications. Clearly, the natural direction to look for a solution here is to identify platform properties which may allow addressing the said issues. Examining the platform properties as discussed in Section III and IV, we ﬁnd that one can utilize the property “software abstraction of hardware resources” that virtualized platforms offer, for examining and controlling the computing resources. Being software entities, the virtual hardware resources and entire VMs are much easier to examine, conﬁgure and control 282 413 Aspect definitions Platform aspects service VM management APIs of VMM VM snapshot store controls Aspect agent VM control agent Applications Aspect agent VM control agent VM management APIs of VMM VM Applications calls VM-1 VM-n Application Fig. 3. Platform Level Aspect-Orientation Implementation Monitoring agent notify Check-point monitoring service uses programmatically. Logical architecture for the proposed solution is shown in Fig. 3. The dotted arrow lines indicate the VM control interactions, whereas the solid arrow lines depict the interactions between aspect service and agent. The key components of this solution are: Checkpointing policies Fig. 4. – Aspect agent. It is deployed on each VM and its main responsibility is to examine and monitor the system as speciﬁed by the aspect deﬁnitions. – Platform aspects service. It monitors the aspect agents and reacts according to the aspect deﬁnitions by possibly sending out VM control commands. – Aspect deﬁnitions. They specify in a structured manner the system indicators/state to be examined and monitored. – VM control agent. It is deployed on the VM and allows controlling the VM. Example Scenario Implementation Platform-level Aspect Orientation pattern as described in Section IV-1 can be employed to address this problem. An outline of the solution is depicted in Fig. 4. In this particular case, the long running jobs can be deployed in VMs. These VMs are check-pointed by periodically taking snapshots based on some policy/aspect deﬁnition. On detecting failures, the VM can be restored to a previously known good state thus preventing the loss of partially completed work. An added beneﬁt of such an approach is that this solution can be generic in nature, that is, it need not have application speciﬁc failure recovery implementation. Hence a common VM monitoring and control mechanism can be used to checkpoint different applications/VMs, thus saving the development maintenance costs. One may observe that this solution is a specialized version of the generic solution shown in Fig. 3. The monitoring agent periodically notiﬁes the application’s status to a check-point monitoring service. Existing standards and technologies such as Java Management Extensions (JMX) API or similar can be used to build the monitoring agent and the check-point monitoring service components. The conditions under which to check-point and restore a VM’s state are handled by specifying check-pointing policies or rules. The check-pointing and restore of VM is carried out via the VM management APIs exposed by the VMM. This solution can be viewed as a fusion of three ideas: a) Observer pattern b) The feedback-and-control tactics and c) Abstracting out system level cross-cutting concerns. The aspect agent and service roughly correspond to the observable and observer. The reactive commands are sent to the VMs by the aspect service via VM control agent. Implementation Scenario Example: A common business application scenario is the execution of long running tasks with chain or pipeline type of dependencies. For instance, in investment banking industry it is common to ﬁnd nightly cron jobs which download large volumes of daily stock markets data and feed it into different kinds of analytics and learning algorithms or transformations of varying kinds. Often such jobs are long running and failures in the middle are costly. Impacts of such failures get further compounded when multiple applications have dependencies forming a chain. To handle the failures without losing partially completed work requires complex programming solutions which are expensive to develop, debug, test and maintain. Such solutions are often implemented in application speciﬁc manner and are not reusable across applications. It is desirable to have simpler, cheaper and reusable solution to handle failure recovery in the said scenario. It is easy to observe that the concern of failure monitoring and recovery cuts across different applications. Solution like V. C ONCLUSION We have presented an in-depth study of cloud oriented and virtualized computing platforms. Most existing literature on this subject deals either with only a narrow aspect of the said platforms, or it is vendor’s offering speciﬁc in nature. In this paper, we have approached the said platforms from an application’s design and architecture perspective. That is, we examined the said platforms to bring out their key architectural 283 414 properties and their implications for the design of an application. For instance, the most important and useful property of the platforms is the software abstraction of hardware which allows for a ﬂuid computing environment. Such a ﬂuid computing environment can be examined, compared, saved, moved around over the wire and monitored by programmatic means. Properties such as this can be exploited to achieve certain QAs. In the presented worn we have shown the efﬁcacy of our ﬁndings by exploiting the said platform properties to devise a novel architectural design pattern. This design pattern addresses commonly occurring application scenarios across business domains. Solving those application scenarios in the past was limited by the purely physical nature of the computing environments. We believe that our ﬁndings can be useful in the evaluation of architectural design decisions. [19] A. Kivity, Y. 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