Alla Segal

Dynamic Scaling of Web Applications in a Virtualized Cloud Computing Environment

Scalability is critical to the success of many enterprises currently involved in doing business on the web and in providing information that may vary drastically from one time to another. Maintaining sufficient resources just to meet peak requirements can be costly. Cloud computing provides a powerful computing model that allows users to access resources on-demand. In this paper, we will describe a novel architecture for the dynamic scaling of web applications based on thresholds in a virtualized Cloud Computing environment. We will illustrate our scaling approach with a front-end load-balancer for routing and balancing user requests to web applications deployed on web servers installed in virtual machine instances. A dynamic scaling algorithm for automated provisioning of virtual machine resources based on threshold number of active sessions will be introduced. The on-demand capability of the Cloud to rapidly provision and dynamically allocate resources to users will be discussed. Our work has demonstrated the compelling benefits of the Cloud which is capable of handling sudden load surges, delivering IT resources on-demands to users, and maintaining higher resource utilization, thus reducing infrastructure and management costs.

A Multi-Agent Systems Approach to Autonomic Computing

The goal of autonomic computing is to create computing systems capable of managing themselves to a far greater extent than they do today. This paper presents Unity, a decentralized architecture for autonomic computing based on multiple interacting agents called autonomic elements. We illustrate how the Unity architecture realizes a number of desired autonomic system behaviors including goal-driven self-assembly, self-healing, and real-time self-optimization. We then present a realistic prototype implementation, showing how a collection of Unity elements self-assembles, recovers from certain classes of faults, and manages the use of computational resources (e.g. servers) in a dynamic multi-application environment. In Unity, an autonomic element within each application environment computes a resource-level utility function based on information specified in that applicationýs service-level utility function. Resource-level utility functions from multiple application environments are sent to a Resource Arbiter element, which computes a globally optimal allocation of servers across the applications. We present illustrative empirical data showing the behavior of our implemented system in handling realistic Web-based transactional workloads running on a Linux cluster.

Unity: experiences with a prototype autonomic computing system

The behavior of a system results from the behaviors of its components, and from the interactions and relationships among them. In order to create computing systems that manage themselves, we will need to design both the behaviors of the individual elements, and the relationships that are formed among them. This paper describes a research project called Unity, carried out at IBMs Thomas J. Watson Research Center, in which we explore some of the behaviors and relationships that will allow complex computing systems to manage themselves; to be self-configuring, self-optimizing, self-protecting, and self-healing. The four principle aspects of Unity that we examine are the overall architecture of the system, the role of utility functions in decision-making within the system, the way the system uses goal-driven self-assembly to configure itself, and the design patterns that enable self-healing within the system.

Solution-based deployment of complex application services on a Cloud

Managing and containing runaway IT costs for solution deployment is one of the top priorities for enterprises. Cloud Computing, with its on-demand provisioning capability on shared resources, has emerged as a new paradigm for reducing IT costs. In this paper, we describe a solution-based provisioning mechanism to automate the deployment of complex application services on a Cloud infrastructure. We introduce the concept of Composite Appliance and show how it can be used to deploy a complete solution and to simplify management tasks. We illustrate the advantages of our approach with a prototype solution consisting of two-tier application services that are deployed and configured automatically on virtual machine instances without manual intervention.

Policy-Based Autonomic Storage Allocation

The goal of autonomic storage allocation is to achieve management of storage resources, including allocation, performance monitoring, and hotspot elimination, by specifying comparatively high-level goals, rather than by means of low-level manual steps. The process of automation should allow specification of policies as administrator specified constraints under which the resources are managed. This paper describes the system design and implementation experiences from a prototype autonomic storage manager being developed in IBM Research. The prototype is being developed for a storage network that includes a SAN switch, an IBM Enterprise Storage Subsystem, and AIX servers. Our early experience from this prototype implementation is that there are a large number of mundane manual steps in storage management and it is feasible to automate them such that the automation is driven by higher-level goals under policy control. However, to manage heterogeneous storage a standard ontology is needed for specification of goals and how to achieve them.

Simplifying solution deployment on a Cloud through composite appliances

Containing runaway IT costs is one of the top priorities for enterprises. Cloud Computing, with its on-demand provisioning capability on shared resources, has emerged as a new paradigm for managing IT costs. In this paper, we describe a framework to simplify deployment of complex solutions on a Cloud infrastructure. We discuss the concept of a composite appliance and show how it can be used to reduce management costs. We illustrate the benefits of our approach with a complex three-tiered solution that can be deployed and configured on a set of virtual machines instances without any manual intervention.

A Cloud Provisioning System for Deploying Complex Application Services

Cloud Computing, with its on-demand provisioning capability on shared resources, has emerged as a new paradigm for reducing IT costs. In this paper, we present the architecture of a provisioning system that simplifies the deployment of complex application services on a Cloud infrastructure. We will introduce the concept of Composite Appliance and explain how it can be implemented and utilized to simplify management tasks and to reduce costs. We illustrate the extensibility and advantages of our design with a prototype solution consisting of a 3-tier application services that are deployed and configured automatically without manual intervention on a set of virtual machines instances in a Cloud.

Work in Progress: Availability-Aware Self-Configuration in Autonomic Systems

The Unity project is a prototype autonomic system demonstrating and validating a number of ideas about self-managing computing systems. We are currently working to enhance the self-configuring and self-optimizing aspects of the system by incorporating the notion of component availability into the system’s policies, and into its models of itself.

A toolkit-based approach to policy-managed storage

The goal of policy-based storage management is to allow storage resources in an IT complex to be managed by setting comparatively high-level policies, rather than by doing low-level manual configuration. We describe the policy management and rule execution architecture in a prototype autonomic storage manager being developed in IBM Research. The prototype uses generic communication, a policy repository, and policy translation and execution services provided by an autonomic manager toolkit. The prototype supports a set of policy templates developed from a policy-based storage management framework.

Scalable Metering for an Affordable IT Cloud Service Management

As the cloud services journey through their life-cycle towards commodities, cloud service providers have to carefully choose the metering and rating tools and scale their infrastructure to effectively process the collected metering data. In this paper, we focus on the metering and rating aspects of the revenue management and their adaptability to business and operational changes. We design a framework for IT cloud service providers to scale their revenue systems in a cost-aware manner. The main idea is to dynamically use existing or newly provisioned SaaS VMs, instead of dedicated setups, for deploying the revenue management systems. At on-boarding of new customers, our framework performs off-line analysis to recommend appropriate revenue tools and their scalable distribution by predicting the need for resources based on historical usage. This allows the revenue management to adapt to the ever evolving business context. We evaluated our framework on a test bed of 20 physical machines that were used to deploy 12 VMs within Open Stack environment. Our analysis shows that service management related tasks can be offloaded to the existing VMs with at most 15% overhead in CPU utilization, 10% overhead for memory usage, and negligible overhead for I/O and network usage. By dynamically scaling the setup, we were able to reduce the metering data processing time by many folds without incurring any additional cost.