Deployment Of Multi-cloud Applications Research Articles

Low-power multi-cloud deployment of large distributed service applications with response-time constraints

Distributed service applications make heavy use of clouds and multi-clouds, and must (i) meet service quality goals (e.g. response time) while (ii) satisfying cloud resource constraints and (iii) conserving power. Deployment algorithms must (iv) provide a solution meeting these requirements within a short time to be useful in practice. Very few existing deployment methods address the first three requirements, and those that do take too long to find a deployment. The Low-Power Multi-Cloud Application Deployment (LPD) algorithm fills this gap with a low-complexity heuristic combination of generalized graph partitioning between clouds, bin-packing within each cloud and queueing approximations to control the response time. LPD has no known competitor that quickly finds a solution that satisfies response time bounds. A host execution time approximation for contention is fundamental to achieving sufficient solution speed. LPD is intended for use by cloud managers who must simultaneously manage hosts and application deployments and plan capacity to offer services such as Serverless Computing.On 104 test scenarios deploying up to 200 processes with up to 240 replicas (for scaling), LPD always produced a feasible solution within 100 s (within 20 seconds in over three-quarters of cases). Compared to the Mixed Integer Program solution by CPLEX (which took a lot longer and was sometimes not found) LPD solutions gave power consumption equal to MIP in a third of cases and within 6% of MIP in 95% of cases. In 93% of all 104 cases the power consumption is within 20% of an (unachievable) lower bound.LPD is intended as a stand-alone heuristic to meet solution time restrictions, but could easily be adapted for use as a repair mechanism in a Genetic Algorithm.

Security-by-design in multi-cloud applications: An optimization approach

Currently an increasing number of customers require cloud services with guaranteed security levels. At this aim, the adoption of multi-cloud strategies is spreading in a large number of interesting application domains, since they may potentially improve security and reduce development costs. However, the problem of identifying the optimal distribution of the components of a cloud application on resources belonging to multiple and heterogeneous providers is very challenging, especially in the presence of different security and performance constraints.This paper presents a novel security-driven approach for the design, development and deployment of multi-cloud applications. It is based on a fully-automatable process that supports the developer from the elicitation of the application requirements up to the identification of the optimal deployment configuration, allowing to find the best compromise between overall cost and achieved level of security. The proposed optimization process takes explicitly into account two critical aspects that are often overlooked in similar approaches, namely the cloud on-demand leasing model for the allocation of resources and the impact that the deployment has on the security policies actually implemented by a complex application.

CloudMF

While the number of cloud solutions is continuously increasing, the development and operation of large-scale and distributed cloud applications are still challenging. A major challenge is the lack of interoperability between the existing cloud solutions, which increases the complexity of maintaining and evolving complex applications potentially deployed across multiple cloud infrastructures and platforms. In this article, we show how the Cloud Modelling Framework leverages model-driven engineering and supports the DevOps ideas to tame this complexity by providing: (i) a domain-specific language for specifying the provisioning and deployment of multi-cloud applications, and (ii) a models@run-time environment for their continuous provisioning, deployment, and adaptation.

Multi-cloud resource management: cloud service interfacing

Cloud service abstractions are currently used to hide the underlying complexity given by existing technologies and services, in hope of facilitating the enacting of Cloud Federations and Marketplaces. In particular, resource management systems dealing with multiple Cloud providers need to expose an uniform interface for various services and to build wrappers for the Cloud service APIs. In this paper we discuss the solution adopted by a recent developed open-source and vendor agnostic platform-as-a-service for Multi-Cloud application deployment. The middleware includes a multi-agent system for automatic Cloud resource management. With a modular design, the solution provides a flexible approach to encompass new Cloud service offers as well as new resource types. This paper focuses on the modules which enable resource abstraction and automatized management.