Michael H. Kalantar

Oceano-SLA based management of a computing utility

Oceano is a prototype of a highly available, scaleable, and manageable infrastructure for an e-business computing utility. It enables multiple customers to be hosted on a collection of sequentially shared resources. The hosting environment is divided into secure domains, each supporting one customer. These domains are dynamic: the resources assigned to them may be augmented when the load increases and reduced when load dips. This dynamic resource allocation enables flexible service level agreements (SLAs) with customers in an environment where peak loads are an order of magnitude greater than the normal steady state.

An architecture for virtual solution composition and deployment in infrastructure clouds

The combination of virtual server technology and the Infrastructure-as-a-Service (IaaS) approach to utility computing promises to revolutionize the way in which distributed software services are deployed. Server virtualization technology can be used to capture complete reusable software stacks, shifting the complexity of middleware installation and configuration from deployment to packaging. IaaS clouds provide a set of interfaces for controlling virtual machines and configuring their hardware and network environment, substantially reducing the complexity of service provisioning. In this paper we identify and tackle a few of the remaining challenges in fulfilling the promise of radical simplification of distributed software service composition and deployment. We propose an approach and architecture for composition and deployment of virtual software services in cloud environments. We introduce a virtual appliance model which treats virtual images as building blocks for composite solutions. Virtual appliances use a port abstraction to negotiate their communication parameters. A solution architect creates a virtual solution model by composing virtual appliances and defining requirements on the environment in a cloud-independent manner. The virtual solution model is transformed to a cloud-specific virtual solution deployment model used to generate a parameterized deployment plan that can be executed by an unskilled user. We validated our approach through a prototype implementation demonstrating flexible composition and automated deployment in our local lab virtualization infrastructure and in Amazon EC2.

Pattern Based SOA Deployment

A key function of a Service Oriented Architecture is the separation between business logic and the platform of its implementation and deployment. Much of the focus in SOA research has been on service design, implementation, composition, and placement. In this paper we address the challenge of configuring the hosting infrastructure for SOA service deployment. The functional and non-functional requirements of services impose constraints on the configuration of their containers at different levels. Presently, such requirements are captured in informal documents, making service deployment a slow, expensive, and error-prone process. In this paper, we introduce a novel approach to formally capturing service deployment best-practices as model-based patterns. Deployment patterns capture the structure of a solution, without bindings to specific resource instances. They can be defined at different levels of abstraction supporting reuse, and role-based iterative refinement and composition. We show how we extended an existing model driven deployment platform to support pattern based deployment. We formally define pattern semantics, validation, and refinement. We also present an algorithm for automatically instantiating such patterns on multiple distributed service environments. Our approach has been verified in a large prototype that has been used to capture a variety of functional and non-functional deployment constraints, and demonstrate their end-to-end maintenance and realization.

Managing the configuration complexity of distributed applications in Internet data centers

In this article we examine the challenges faced by data center administrators when deploying and configuring Web applications. We discuss how the configuration dependencies of these Web applications cut across software stacks, network layers, and middleware container boundaries. We argue that the deployment and configuration process requires the combined expertise from multiple domains such as application, middleware, network, security, reliability, and performance. We review the model-based tools available today to manage the configuration complexity of these applications and introduce a new tool that extends the existing state of the art by automatically generating actionable distributed deployment models using model transformation techniques. The key idea behind this new tool is the principle of separation of concerns: developers capture the logical structure of the application in a model, best practices experts define deployment model transformation rules, deployers specify the required deployment patterns, and an operator provides a model describing the data center resources. The tool automatically finds solutions based on these four inputs and executes the deployment.

Reducing the complexity of application deployment in large data centers

The deployment and configuration of distributed applications is a human intensive and highly complex process that poses significant challenges to data center operators. The process involves many cross-cutting concerns such as connectivity, performance, and security requirements, as well as resource availability, policies and best practices. These interdependencies represent a significant source of complexity, cost, and risk in data center management. In this paper we address this problem using a new approach that leverages concepts from the model-driven architecture research domain. We describe a prototype application deployment automation system based on model transformation techniques. We show how model transformation techniques can replace the manual process of writing and adapting scripts and workflows, reduce the deployment complexity, guarantee configuration integrity and consistency, and allow for a separation of concerns.

Neptune: A Dynamic Resource Allocation and Planning System for a Cluster Computing Utility

We present Neptune - the resource director of Océano, a policy driven fabric management system that dynamically reconfigures resources in a computing utility cluster. Neptune implements an on-line control mechanism subject to policy-based performance and resource configuration objectives. Neptune reassigns servers and bandwidth among a set of service domains, based on pre-defined policy, in response to workload changes. It builds and executes a reconfiguration plan through a planning framework, breaking reconfiguration objectives into individual tasks delegated to set of lower level resource managers. We describe an example decision policy algorithm that we implemented and demonstrated in an 80 server multi-domain computing utility.

Automatic Realization of SOA Deployment Patterns in Distributed Environments

Deployment patterns have been proposed as a mechanism to support the provisioning of SOA-based services. Deployment patterns represent the structure and constraints of composite solutions, including non-functional properties, such as performance, availability, and security, without binding to specific resource instances. In previous work [1], we have presented a formal mechanism for capturing such service deployment patterns using models. Our pattern models define abstract connectivity and configuration requirements which are then realized by an existing or planned infrastructure. Realization mapping is used to enforce policies, and is materialized at deployment time. In this paper we extend that work to address the problem of automatic pattern realization over a given infrastructure. We first formalize the problem and present three variations of increasing power and complexity. We then present a variation of a search-based graph isomorphism algorithm with extensions for our pattern model semantics. Next, we show that our worst-case exponential complexity algorithm performs well in practice, over a number of pattern and infrastructure combinations. We speculate that this is because deployment topologies represent heavily labeled and sparse graphs. We present a number of heuristics which we have compared experimentally, and have identified one which performs best across most scenarios. Our algorithm has been incorporated into a large deployment modeling platform, now part of the IBM Rational Software Architect (RSA) tool [2].

Dynamic resource management in an eUtility

Oceano is management software for a eUtility infrastructure capable of providing cost-effective, autonomic resource allocation for multiple customer or application domains, in response to existent performance and availability conditions. The control layer of Oceano provides mechanisms to manage resources. This layer consists of a resource director and a set of resource managers. The resource director formulates resource configurations and coordinates their execution through resource managers. These resource managers maintain restore state and carry out detailed configuration tasks. This paper describes the Oceano resource management model and its server and application deployment resource managers. A prototype of Oceano has been developed and deployed on an 80 server platform, and has been tested with multiple domains and applications.

Causally ordered multicast: the conservative approach

Process group toolkits provide methods to structure a system as a set of groups of cooperating processes, to detect process failures, and to order events (by ordering messages). Such tools have a performance cost for applications, particularly when a system is built using a large number of overlapping groups. We built an event-driven simulation to study performance of causally ordered message delivery in large systems composed of overlapping groups. Our studies, the first ever of multiple group systems, reveal some conditions under which the delays can be very large: two orders of magnitude greater than when delays are not required. Further, in a large system these delays can lead to increased system burstiness which limits system scalability. These results suggest that a system supporting multiple overlapping groups needs to be carefully designed and the system should often provide users with control over when to apply ordering guarantees.

Weaver: language and runtime for software defined environments

Continuous delivery of software and related infrastructure environments is a challenging proposition. Typical enterprise environments, comprising distributed software and its supporting infrastructure, exhibit non-obvious, often implicit dependencies and requirements. Further increasing this challenge is that knowledge about configuration is fragmented and informally recorded. Given this situation, we propose Weaver, a domain-specific language designed to formally specify blueprints, desired state descriptions of environments. An associated runtime executes blueprints to create or modify environments through a set of target-specific platform providers that supply cloud-specific implementations. New and existing automation to implement and maintain the desired state can be associated with a blueprint specified in Weaver. Furthermore, Weaver supports the definition of conditions to validate a blueprint at design time and deployment time, as well as to continuously validate a deployed environment. We demonstrate the use of Weaver to deploy IBM Connections, an enterprise social software platform.