Energy-QoS Tradeoffs in J2EE Hosting Centers

International audienceNowadays, hosting centres are widely used to host various kinds of applications e.g., web servers or scientific applications. Resource management is a major challenge for most organisations that run these infrastructures. Many studies show that clusters are not used at their full capacity which represents a significant source of waste. Autonomic management systems have been introduced in order to dynamically adapt software infrastructures according to runtime conditions. They provide support to deploy, configure, monitor, and repair applications in such environments. In this paper, we report our experiments in using an autonomic management system to provide resource aware management for a clustered application. We consider a standard replicated server infrastructure in which we dynamically adapt the degree of replication in order to ensure a given QoS while minimising energy consumption

Towards Grid Monitoring and deployment in Jade, using ProActive

This document describes our current effort to gridify Jade, a java-based environment for the autonomic management of clustered J2EE application servers, developed in the INRIA SARDES research team. Towards this objective, we use the java ProActive grid technology. We first present some of the challenges to turn such an autonomic management system initially dedicated to distributed applications running on clusters of machines, into one that can provide self-management capabilities to large-scale systems, i.e. deployed on grid infrastructures. This leads us to a brief state of the art on grid monitoring systems. Then, we recall the architecture of Jade, and consequently propose to reorganize it in a potentially more scalable way. Practical experiments pertain to the use of the grid deployment feature offered by ProActive to easily conduct the deployment of the Jade system or its revised version on any sort of grid

H2O: An Autonomic, Resource-Aware Distributed Database System

This paper presents the design of an autonomic, resource-aware distributed database which enables data to be backed up and shared without complex manual administration. The database, H2O, is designed to make use of unused resources on workstation machines. Creating and maintaining highly-available, replicated database systems can be difficult for untrained users, and costly for IT departments. H2O reduces the need for manual administration by autonomically replicating data and load-balancing across machines in an enterprise. Provisioning hardware to run a database system can be unnecessarily costly as most organizations already possess large quantities of idle resources in workstation machines. H2O is designed to utilize this unused capacity by using resource availability information to place data and plan queries over workstation machines that are already being used for other tasks. This paper discusses the requirements for such a system and presents the design and implementation of H2O.Comment: Presented at SICSA PhD Conference 2010 (http://www.sicsaconf.org/

Optimizing the integration of agent-based cloud archestrators and higher-level workloads

Part 5: Ph.D. Track: Autonomic and Self-Management SolutionsInternational audienceThe flexibility of cloud computing has put significant strain on operations teams. Manually installing and configuring applications in the cloud simply isn’t an option anymore. Configuration management automation solves the issue of getting a single application into a certain state automatically and reliably. However, the issue of automatic dependency management between multiple applications is still an “open, hard problem” according to researchers at Google. Agent-based modeling and orchestration tools like Juju solve the issue of getting from zero to a working set of correctly clustered and connected frameworks. The shortcomings of these state-of-the-art tools are that they don’t provide efficient ways to model and orchestrate workloads running on top of these frameworks. This paper presents a number of ways to deploy and orchestrate workloads with Juju, compares their performance and overhead, and suggests how this overhead can be minimized

Dynamic Model-based Management of Service-Oriented Infrastructure.

Models are an effective tool for systems and software design. They allow software architects to abstract from the non-relevant details. Those qualities are also useful for the technical management of networks, systems and software, such as those that compose service oriented architectures. Models can provide a set of well-defined abstractions over the distributed heterogeneous service infrastructure that enable its automated management. We propose to use the managed system as a source of dynamically generated runtime models, and decompose management processes into a composition of model transformations. We have created an autonomic service deployment and configuration architecture that obtains, analyzes, and transforms system models to apply the required actions, while being oblivious to the low-level details. An instrumentation layer automatically builds these models and interprets the planned management actions to the system. We illustrate these concepts with a distributed service update operation

Middleware-based Database Replication: The Gaps between Theory and Practice

The need for high availability and performance in data management systems has been fueling a long running interest in database replication from both academia and industry. However, academic groups often attack replication problems in isolation, overlooking the need for completeness in their solutions, while commercial teams take a holistic approach that often misses opportunities for fundamental innovation. This has created over time a gap between academic research and industrial practice. This paper aims to characterize the gap along three axes: performance, availability, and administration. We build on our own experience developing and deploying replication systems in commercial and academic settings, as well as on a large body of prior related work. We sift through representative examples from the last decade of open-source, academic, and commercial database replication systems and combine this material with case studies from real systems deployed at Fortune 500 customers. We propose two agendas, one for academic research and one for industrial R&D, which we believe can bridge the gap within 5-10 years. This way, we hope to both motivate and help researchers in making the theory and practice of middleware-based database replication more relevant to each other.Comment: 14 pages. Appears in Proc. ACM SIGMOD International Conference on Management of Data, Vancouver, Canada, June 200