1,769 research outputs found
Research challenges for cross-cloud application
Federated clouds can expose the Internet as a homogeneous compute fabric. There is an opportunity for developing cross-cloud applications that can be deployed pervasively over the Internet, dynamically adapting their internal topology to their needs. In this paper we explore the main challenges for fully realizing the potential of cross-cloud applications. First, we focus on the networking dimension of these applications. We evaluate what support is needed from the infrastructure, and what are the further implications of opening the networking side. On a second part, we examine the impact of a distributed deployment for applications, assessing the implications from a management perspective, and how it affects the delivery of quality of service and non-functional requirements
Decision Support Tools for Cloud Migration in the Enterprise
This paper describes two tools that aim to support decision making during the
migration of IT systems to the cloud. The first is a modeling tool that
produces cost estimates of using public IaaS clouds. The tool enables IT
architects to model their applications, data and infrastructure requirements in
addition to their computational resource usage patterns. The tool can be used
to compare the cost of different cloud providers, deployment options and usage
scenarios. The second tool is a spreadsheet that outlines the benefits and
risks of using IaaS clouds from an enterprise perspective; this tool provides a
starting point for risk assessment. Two case studies were used to evaluate the
tools. The tools were useful as they informed decision makers about the costs,
benefits and risks of using the cloud.Comment: To appear in IEEE CLOUD 201
Atlas: Hybrid Cloud Migration Advisor for Interactive Microservices
Hybrid cloud provides an attractive solution to microservices for better
resource elasticity. A subset of application components can be offloaded from
the on-premises cluster to the cloud, where they can readily access additional
resources. However, the selection of this subset is challenging because of the
large number of possible combinations. A poor choice degrades the application
performance, disrupts the critical services, and increases the cost to the
extent of making the use of hybrid cloud unviable. This paper presents Atlas, a
hybrid cloud migration advisor. Atlas uses a data-driven approach to learn how
each user-facing API utilizes different components and their network footprints
to drive the migration decision. It learns to accelerate the discovery of
high-quality migration plans from millions and offers recommendations with
customizable trade-offs among three quality indicators: end-to-end latency of
user-facing APIs representing application performance, service availability,
and cloud hosting costs. Atlas continuously monitors the application even after
the migration for proactive recommendations. Our evaluation shows that Atlas
can achieve 21% better API performance (latency) and 11% cheaper cost with less
service disruption than widely used solutions.Comment: To appear at EuroSys 202
- …