Sara Bouchenak

Autonomic Management of Clustered Applications

Distributed software environments are increasingly complex and difficult to manage, as they integrate various legacy software with proprietary management interfaces. Moreover, the fact that management tasks are performed by humans leads to many configuration errors and low reactivity. This paper presents Jade, a middleware for self-management of distributed software environments. The main principle is to wrap legacy software pieces in components in order to provide a uniform management interface, thus allowing the implementation of management applications. Management applications are used to deploy distributed applications and to autonomously reconfigure them as required

Architecture-Based Autonomous Repair Management: Application to J2EE Clusters

This paper presents a component-based architecture for autonomous repair management in distributed systems and its application to J2EE server clusters, called JADE. The architecture features three major elements: (1) a dynamically configurable, component-based structure that exploits the reflective features of the FRACTAL component model; (2) an explicit and configurable feedback control loop structure, that manifests the relationship between managed system and repair management functions; (3) an original replication structure for the management subsystem itself which makes it fault-tolerant and self-healing

Towards QoS-Oriented SLA Guarantees for Online Cloud Services

Cloud Computing provides a convenient means of remote on-demand and pay-per-use access to computing resources. However, its ad hoc management of quality-of-service and SLA poses significant challenges to the performance, dependability and costs of online cloud services. The paper precisely addresses this issue and makes a threefold contribution. First, it introduces a new cloud model, the SLAaaS (SLA aware Service) model. SLAaaS enables a systematic integration of QoS levels and SLA into the cloud. It is orthogonal to other cloud models such as SaaS or PaaS, and may apply to any of them. Second, the paper introduces CSLA, a novel language to describe QoS-oriented SLA associated with cloud services. Third, the paper presents a control theoretic approach to provide performance, dependability and cost guarantees for online cloud services, with time-varying workloads. The proposed approach is validated through case studies and extensive experiments with online services hosted in clouds such as Amazon EC2. The case studies illustrate SLA guarantees for various services such as a MapReduce service, a cluster-based multi-tier e-commerce service, and a low-level locking service.

Verifying cloud services: present and future

As cloud-based services gain popularity in both private and enterprise domains, cloud consumers are still lacking in tools to verify that these services work as expected. Such tools should consider properties such as functional correctness, service availability, reliability, performance and security guarantees. In this paper we survey existing work in these areas and identify gaps in existing cloud technology in terms of the verification tools provided to users. We also discuss challenges and new research directions that can help bridge these gaps.

Benchmarking Dependability of MapReduce Systems

MapReduce is a popular programming model for distributed data processing. Extensive research has been conducted on the reliability of MapReduce, ranging from adaptive and on-demand fault-tolerance to new fault-tolerance models. However, realistic benchmarks are still missing to analyze and compare the effectiveness of these proposals. To date, most MapReduce fault-tolerance solutions have been evaluated using micro benchmarks in an ad-hoc and overly simplified setting, which may not be representative of real-world applications. This paper presents MRBS, a comprehensive benchmark suite for evaluating the dependability of MapReduce systems. MRBS includes five benchmarks covering several application domains and a wide range of execution scenarios such as data-intensive vs. compute-intensive applications, or batch applications vs. online interactive applications. MRBS allows to inject various types of faults at different rates. It also considers different application workloads and data loads, and produces extensive reliability, availability and performance statistics. We illustrate the use of MRBS with Hadoop clusters running on Amazon EC2, and on a private cloud.

SLA guarantees for cloud services

Quality-of-service and SLA guarantees are among the major challenges of cloud-based services. In this paper we first present a new cloud model called SLAaaS - SLA?aware Service. SLAaaS considers QoS levels and SLA as first class citizens of cloud-based services. This model is orthogonal to other SaaS, PaaS, and IaaS cloud models, and may apply to any of them. More specifically we make three contributions: (i) we provide a novel domain specific language that allows to describe QoS-oriented SLA associated with cloud services; (ii) we present a general control-theoretic approach for managing cloud service SLA; (iii) we apply the proposed language and control approach to guarantee SLA in various case studies, ranging from cloud-based MapReduce service, to locking service, and higher-level e-commerce service; these case studies successfully illustrate SLA management with different QoS aspects of cloud services such as performance, dependability, financial energetic costs. We provide a domain specific language that allows to describe SLA in cloud services.We present a general control-theoretic approach for managing cloud service SLA.We apply our approach on MapReduce, locking, and e-commerce services.

Automated control for SLA-aware elastic clouds

Although Cloud Computing provides a means to support remote, on-demand access top a set of computing resources, its ad-hoc management for quality-of-service and SLA poses significant challenges to the performance, availability and economical costs of the cloud. This paper discusses these issues and present early ideas to handle them. First, it introduces the SLAaaS model (SLA aware service) that enriches the general paradigm of Cloud Computing SLAaaS enables a systematic and transparent integration of service levels and SLA to the cloud. It is orthogonal to IaaS, PaaS and may apply to any of them. Furthermore, the paper discusses autonomic SLA management in the cloud and present early ideas to tackle it.

Caching dynamic web content: designing and analysing an aspect-oriented solution

Caching dynamic web content is an effective approach to reduce Internet latency and server load. An ideal caching solution is one that can be added transparently by the developers and provides complete consistency of the cached documents, while minimizing false cache invalidations. In this paper, we design and implement AutoWebCache, a middleware system for adding caching of dynamic content transparently to J2EE server-side applications having a backend database. For this purpose, we first present the principles involved in caching dynamic web content, including our logic to ensure consistency of the cached entries. Thereafter, we demonstrate the use of aspect-oriented (AOP) techniques to implement our system, showing how AOP provides modularity and transparency to the entire process. Further, we evaluate the effectiveness of AutoWebCache in reducing response times of applications, thereby improving throughput. We also analyze the transparency of our system for a general application suite, considering issues such as dynamic web pages aggregating data from multiple sources, presence of insufficiently structured interfaces for exchanging information and the use of application semantics while caching. We use two standard J2EE web benchmark applications, RUBiS and TPC-W, to conduct our experiments and discuss the results obtained.

Experience with CONSER: A System for Server Control through Fluid Modeling

Server technology provides a means to support a wide range of online services and applications. However, their ad hoc configuration poses significant challenges to the performance, availability, and economical costs of applications. In this paper, we examine the impact of server configuration on the central trade-off between service performance and availability. First, we present a server model as a nonlinear continuous-time model using fluid approximations. Second, we develop concurrency control on server systems for an optimal configuration. We primarily provide two control laws for two different QoS objectives. AM-C is an availability-maximizing server control that achieves the highest service availability given a fixed performance constraint; and PM-C is a performance-maximizing control law that meets a desired availability target with the highest performance. We then improve the control with two additional multilevel laws. AA-PM-C is an availability-aware performance-maximizing control, and PA-AM-C is a performance-aware availability-maximizing control. In this paper, we present ConSer, a novel system for the control of servers. We evaluate ConSers fluid model and control techniques on the TPC-C industry-standard benchmark. Our experiments show that the proposed techniques successfully guarantee performance and availability constraints.

A Control Approach for Performance of Big Data Systems

We are at the dawn of a huge data explosion therefore companies have fast growing amounts of data to process. For this purpose Google developed MapReduce, a parallel programming paradigm which is slowly becoming the de facto tool for Big Data analytics. Although to some extent its use is already wide-spread in the industry, ensuring performance constraints for such a complex system poses great challenges and its management requires a high level of expertise. This paper answers these challenges by providing the first autonomous controller that ensures service time constraints of a concurrent MapReduce workload. We develop the first dynamic model of a MapReduce cluster. Furthermore, PI feedback control is developed and implemented to ensure service time constraints. A feedforward controller is added to improve control response in the presence of disturbances, namely changes in the number of clients. The approach is validated online on a real 40 node MapReduce cluster, running a data intensive Business Intelligence workload. Our experiments demonstrate that the designed control is successful in assuring service time constraints.