Markus Klems

What's inside the Cloud? An architectural map of the Cloud landscape

We propose an integrated Cloud computing stack architecture to serve as a reference point for future mash-ups and comparative studies. We also show how the existing Cloud landscape maps into this architecture and identify an infrastructure gap that we plan to address in future work.

MetaStorage: A Federated Cloud Storage System to Manage Consistency-Latency Tradeoffs

Cost and scalability benefits of Cloud storage services are apparent. However, selecting a single storage service provider limits availability and scalability to the selected provider and may further cause a vendor lock-in effect. In this paper, we present MetaStorage, a federated Cloud storage system that can integrate diverse Cloud storage providers. MetaStorage is a highly available and scalable distributed hash table that replicates data on top of diverse storage services. MetaStorage reuses mechanisms from Amazons Dynamo for cross-provider replication and hence introduces a novel approach to manage consistency-latency tradeoffs by extending the traditional quorum (N,R,W) configurations to an (N_P,R,W) scheme that includes different providers as an additional dimension. With MetaStorage, new means to control consistency-latency tradeoffs are introduced.

Cloud service engineering

Building on compute and storage virtualization, Cloud Computing provides scalable, network-centric, abstracted IT infrastructure, platforms, and applications as on-demand services that are billed by consumption. Cloud Service Engineering is the application of a systematic approach to leverage Cloud Computing in the context of the Internet in its combined role as a platform for technical, economic, organizational and social networks. This tutorial introduces concepts and technology of Cloud Computing and Cloud Service Engineering, providing an overview of state-of-the-art in research and practice. We show how to set up a private Cloud that delivers Infrastructure-as-a-Service (IaaS). Eucalyptus and OpenNebula are popular open source software frameworks for creating on-premise Clouds. Promises, challenges and solutions for integrating services of a private Cloud with public Cloud services such as Amazon EC2 and SQS are discussed. We show how the best of both worlds - private and public Clouds - can be combined to build scalable and secure systems.

A Runtime Quality Measurement Framework for Cloud Database Service Systems

Cloud database services promise high performance, high availability, and elastic scalability. The system that provides cloud database services must, hence, be designed and managed in a way to achieve these high quality objectives. There are two technology trends that facilitate the design and management of cloud database service systems. First, the development of distributed replicated database software that is optimally designed for highly available and scalable Web applications and offered as open source software. Second, the possibility to deploy the system on cloud computing infrastructure to facilitate availability and scalability via on-demand provisioning of geo-located servers. We argue that a runtime quality measurement and analysis framework is necessary for the successful runtime management of cloud database service systems. Our framework offers three contributions over the state of the art: (i) the analysis of scaling strategies, (ii) the analysis of conflicts between contradictory objectives, and (iii) the analysis of system configuration changes on runtime performance and availability.

A Middleware Guaranteeing Client-Centric Consistency on Top of Eventually Consistent Datastores

Applications often have consistency requirements beyond those guaranteed by the underlying eventually consistent storage system. In this work, we present an approach that guarantees monotonic read consistency and read your writes consistency by running a special middleware component on the same server as the application. We evaluate our approach using both simulation and real world experiments on Cloud storage systems.

Requirements for an IaaS deployment language in federated Clouds

The advent of advanced virtualized IT infrastructures that can be provisioned as on-demand services, known as Infrastructure-as-a-Service (IaaS) Cloud Computing, has created new research challenges and opportunities. The capability to rapidly allocate and deallocate seemingly infinite amounts of system resources is a defining characteristic of this technological trend. Operating multi-tier applications on a continuously changing environment is one of the big challenges in IaaS Cloud Computing. This challenge is even more daring, if applications are not running at one specific Cloud site but on multiple different sites of various providers. This work is motivated by the need for new deployment description approaches that target application run-time aspects in federated Clouds. We propose six key requirements for IaaS deployment description languages that facilitates continuous application deployment on a permanently changing infrastructure across multiple Cloud sites: software deployment on dynamic virtual machine resource pools, continuous system supervision and change management, a generic model for federated Clouds, automated software configuration management, multi-tier dependency management, and use of a machine-readable language.

The Yahoo!: cloud datastore load balancer

Sherpa is a large-scale distributed and globally replicated multi-tenant cloud data storage system. Sherpa scales by horizontally partitioning data into tablets and distributing these tablets across multiple servers. While Sherpa scales for increasing workload sizes by adding servers, it is vulnerable to load imbalance among tablets that cause hotspots to develop on just a few servers. In this paper we describe Yak, the Sherpa load balancer. Yak detects hotspots and then automatically balances load by migrating tablets from the overloaded servers, and also by splitting data into new tablets. We describe Yaks design principles, algorithms and architecture. We then evaluate Yak on workloads based on Sherpa production scenarios.

Automating the delivery of IT Service Continuity Management through cloud service orchestration

IT Service Continuity Management (ITSCM) delivers the recovery of IT services in the event of a disaster. ITSCM is widely perceived as an expensive challenge for enterprise-class IT operations. Cloud computing offers a model for dynamic, scalable infrastructure resource allocation on a pay-per-use basis. These attributes promise to bring cost-efficiency to ITSCM invocation and operation processes that only in the rare event of a rehearsal or an actual disaster need to allocate infrastructure resources. We propose to use the Web Service Business Process Execution Language (BPEL) in combination with Virtual Appliances to implement standardized, testable and executable ITSCM processes. The suggested solution is described and evaluated against collected data from manual recovery processes.

A Configuration Crawler for Virtual Appliances in Compute Clouds

Compute clouds are pools of virtual machines that are shared in a multi-tenant environment by multiple users. The virtual machine images are stored in one or more repositories and are pre-configured with an operating system. Users of the compute cloud can upload their own images or install and configure additional software on top of existing basic virtual machines. Today, the Amazon Elastic Compute Cloud (EC2) counts more than 35,000 publicly available virtual machine images. We observe, however, that the meta-data that describes the virtual machine images is of poor quality and does not cover vital information such as operating system configurations or software package installations. The sprawl of poorly documented virtual machine images poses a hurdle to sharing and re-use among members of the compute cloud community. We present a method that allows collecting software-related meta-data in compute clouds through appliance introspection. Moreover, we show how applications in the domains of selection and configuration management benefit from rich meta-data and interact with the method. The method has been implemented as an automated tool, the crawler, that collects configuration data of virtual machine images in public compute clouds and evaluated our approach by crawling Amazon EC2.

Consistency Benchmarking: Evaluating the Consistency Behavior of Middleware Services in the Cloud

Cloud service providers such as Amazon Web Services offer a set of next-generation storage and messaging middleware services that can be utilized on-demand over the Internet. Outsourcing software into the cloud, however, confronts application developers with the challenge of understanding the behavior of distributed systems, which are out of their control. This work proposes an approach to benchmark the consistency behavior of services by example of Amazon Simple Queue Service (SQS), a hosted, Web-scale, distributed message queue that is exposed as a Web service. The data of our consistency benchmarking tests are evaluated with the metric harvest as described by Fox and Brewer (1999). Our tests with SQS indicate that the client-service interaction intensity has an influence on harvest.