What is necessary to achieve interoperability in the Cloud?

As described in the previous sections, 3 major interoperability approaches arise. First, there is the standardisation approach, next there is the middleware approach and last but not least there is the API approach. This is also supported by [Hof09] and [Gov10]. In addition to that, [Gov10] suggests building abstraction layers in order to achieve interoperability and transportability.
There are two main aspects where interoperability is necessary. One level is the management level. This deals with handling the virtual machine(s), applying load balancing, setting DNS settings, auto scaling features and other tasks that come with IaaS solutions. However, this level is mainly necessary in IaaS solutions as PaaS solutions already take care of most of it. The other level is the services level. The services level is basically everything that comes with application services such as messaging, data storage and databases.

Figure: Cloud interoperability approaches
These requirements are described in several relevant papers such as [End10], [Mel09], [Jha09].
Parameswaran et al. describes similar challenges for Cloud interoperability. The authors see two different approaches, the first via a unified cloud interface (UCI) and the second via Enterprise Cloud Orchestration [Par09].
A unified cloud interface is basically an API that is written “around” other cloud APIs that is vendor specific. It requires some re-writing of and integration. This is similar to the approach selected by Apache jClouds and Apache libcloud.
The Enterprise Cloud Orchestration is a layer where different cloud providers register their services. The platform then provides these services for users like in a discovery. This is very similar to UDDI. The downside of this is that the orchestration layer still needs to integrate all different services (and built wrappers around them). However, it is transparent to the end-user.

Figure: Enterprise Orchestration Layer [Par09]
This post is part of a work done on Cloud interoperability. You can access the full work here and the list of references here.

PaaS Semantic Interoperability Framework (PSIF)

Loutas et al. defines semantic interoperability as “the ability of heterogeneous Cloud PaaS systems and their offerings to overcome the semantic incompatibilities and communicate” [Lou11]. The target of this framework is to give developers the ability to move their application(s) and data seamlessly from one provider to another. Loutas et al. propose a three-dimensional model addressing semantic interoperability for public cloud solutions [Lou11].
Fundamental PaaS Entities
The fundamental PaaS entities consist of several models: the PaaS System, the PaaS Offering, an IaaS-Offering, Software Components and an Application [Lou11].
Levels of Semantic Conflicts
Loutas et al. [Lou11] assumes that there are 3 major semantic conflicts that can be raised for PaaS offerings. The first one is an interoperability problem between the metadata definitions. This occurs when different data models describe one PaaS offering. The second problem is when the same data gets interpreted differently and the third is when different pieces of data have similar meaning. Therefore, [Lou11] uses a two-level approach for solving semantic conflicts. The first level is the Information Model that refers to differences with data and data structures/models. The other level is the data level that refers to differences in the data because of various representations.
Types of Semantics
Three different types of semantics are defined [Lou11]. The first type is the functional semantic. This is basically a representation of everything that a PaaS solution can offer. The second type, the non-functional semantic, is about elements such as pricing or Quality of Service. The third semantic is the execution semantic, which is describing runtime semantics.
This post is part of a work done on Cloud interoperability. You can access the full work here and the list of references here.

Apache jClouds

Apache jclouds is a framework provided by the Apache Software Foundation. The framework is written in Java and serves the purpose to provide an independent library for typical cloud operations. At present (November 2014), Apache jclouds provides 2 kinds of services: a compute service and a blob service [Apa14b]. Apache jclouds can be used from Java and Clojure. The library offers an abstraction for more than 30 cloud providers, including AWS, Azure, OpenStack and Rackspace.
Apache jclouds is primarily built for infrastructure interoperability. As for the platform layer, only blob storage is currently supported. The focus of jclouds is to support a large variety of platforms over implementing a large variety of services. The Blob storage in Apache jclouds works with the concept of Containers, Folders and Blobs. The library supports access control lists for objects. The upload of Multipart objects is also supported, which allows jclouds to handle large files. [Apa14c]

Libcloud

[Apa14d] Apache libcloud is similar to Apache jClouds. The library is developed as an abstraction to different cloud providers. Libcloud currently supports more than 30 different providers. Libcloud is available as a Python library.
Libcloud is infrastructure-focused with most of it’s implementations done for computing, DNS and Load balancing. There is also an object storage implementation available.
This post is part of a work done on Cloud interoperability. You can access the full work here and the list of references here.

Gonidis [Gon11] defines an approach on how to enable interoperability for PaaS solutions. It is about building a standard for existing cloud platforms. However, this is a challenge given that every platform provider has it’s own proprietary API. Furthermore, services available on the one platform aren’t available on the other platform. In the following posts, existing interoperability frameworks, solutions and standards for Platform as a Service are evaluated.

Standard initiatives

Current standard initiatives are the Open Cloud Computing Interface (OCCI) and the Distributed Management Task Force (DMTF) initiatives. In the next posts, I will outline them in detail.

Libraries and Frameworks

Libraries and Frameworks for Cloud Interoperability are: Apache jClouds and Libcloud. They will be described in the following posts.

Middleware solutions

Middleware Solutions for Cloud interoperability are: mOSAIC, PaaS Semantic Interoperability Framework (PSIF), Frascati-based Multi PaaS Solution and SimpleCloud. They will be described in the following posts.

Interoperability Solutions for the Cloud

Interoperability is used in various levels of software and systems. With Cloud Computing, several major interoperability questions arise. First of all, interoperability can be seen as an infrastructure interoperability element. As for infrastructure interoperability, it is basically about the question on how to move virtual instances from one cloud provider to another.
Another interoperability question is about software and tools interoperability. This is not on how to transfer software from one provider to another, it is about how different software languages and tools collaborate in one cloud ecosystem or different cloud ecosystems. An example of that is a message-based communication between a Java-based solution and a Microsoft .NET solution. Mayrbäurl et al. described such a scenario on a Microsoft Azure based solution that itself communicates with an on-premise solution that is written in Java, whereas the Cloud service uses .NET [May11].
The third interoperability question is about the services offered by different distributors. When someone builds a cloud solution based on a specific provider and uses a software stack such as J2EE or Microsoft .NET, it is not that difficult to move the application to another instance or Cloud provider. However, when this application consumes platform-specific services such as a distributed storage service, a messaging service, e-mail and alike, migration becomes challenging. Therefore, providing interoperability on the platform services level is another key issue in Cloud computing interoperability.
Gonidis et al. defines Interoperability with two different characteristics [Gon11]. According to this paper, interoperability is when two components in different cloud environments are collaborating, whereas the possibility to move from one cloud platform to another is portability. Liu et al. defines portability itself with system portability, which means that a virtual machine can easily be moved to another cloud provider’s platform [Nis11]. In general, they define portability with the ability to move an application and all it’s data with little effort from one cloud provider to another cloud provider.
As for interoperability and portability, current literature knows different approaches. In Gonidis et al. portability and interoperability are distinct features [Gon11], whereas Dowel et al. defines portability to be a subset of interoperability [Dow11]. Petcu et al. discusses interoperability consisting of two dimensions: a horizontal dimension and a vertical dimension [Pet11]. Horizontal interoperability (as illustrated in figure 2) means that two cloud services on the same service level (e.g. PaaS) can communicate with each other, whereas vertical interoperability describes the ability to host an application on different cloud providers. When implementing vertical portability, it is necessary to support different cloud platforms.

Another description of interoperability for cloud solutions is given by Parameswaran et al. [Par12]. The authors describe 4 major factors of interoperability challenges. The first is portability, which was already discussed. The second is interoperability itself, which focuses on efficient and reliable protocols. The third is heterogeneity. This states that there are several protocols such as SOAP and Representational State Transfer (REST) [Fie00] and different formats such as XML and JSON. A PaaS application will need to deal with all of these protocols and formats in order to ensure interoperability in a heterogeneous environment. Last, there is geo-diversity. This means that smaller, but geographically more distributed datacentres might be more effective than large datacentres that are only available in some regions.
Why is interoperability so important to the cloud?
Leavitt [Lea09] addresses potential issues with the vendor Lock-In in cloud computing. When it is not possible to move from one platform to another at low cost and effort, it is very likely that one get’s locked into a certain platform. Should the provider decide to increase prices, the customer has to stick to the new conditions without the ability to move the application to a cheaper carrier. Another reason is when the cloud provider fails. Even large providers such as Microsoft [Oky14] and Amazon [Kep14] fail. This could mean that the platform is not available for several hours to days. In their SLA’s, cloud providers typically don’t reimburse the customers for lost revenue [Ama14b], [Mic14c]. But it could become worse: the cloud provider might actually disappear and customers have to move entirely to another platform entirely. This happened in February 2009 when Coghead, a cloud Platform went out of service [Kin09]. Users could export their data, but couldn’t port their applications.
This post is part of a work done on Cloud interoperability. You can access the full work here and the list of references here.