Fault Tolerant, Self-Healing and Vendor Neutral Multi-Cloud Patterns and Framework Focusing on Deployment and Management
Many organizations are looking to migrate to the cloud and looking for the best way to do it securely, reliably and without vendor lock in. Most organizations have to pick a cloud provider that uses proprietary APIs and Software. Most vendors currently do not implement any cloud API standards i.e. TOSCA or OASIS CAMP. Therefore, to date, the standard approaches to cloud computing have not been successful. In addition, cloud providers experience outages, frequently with serious business impact—so fault tolerance in cloud environment still needs more research and clear and prescriptive guidance. Variable performance is also an issue because most cloud providers overprovision their virtualized infrastructure and it results in degradation of performance and quality of service for customers depending on overprovisioning factor set by the cloud provider. This study focuses on development of multi-cloud vendor neutral framework and patterns that deliver non-proprietary APIs and Software above IaaS layer with the functionality that will be on par with proprietary software or service offered by an individual cloud provider. We demonstrate how to design Fault Tolerant, Self-Healing, Performant, Secure and Cost Efficient Deployment using Patterns in the Multi-cloud environment without vendor lock in. We detail and catalog the developed solutions to common multi-cloud problems via patterns and multi-cloud framework using open source software which ensures portability across cloud providers. Framework and patterns can be re-produced by setup scripts, code and examples which are provided in the accompanying code repository. All of the failure scenarios are validated and demonstrated clearly showing the fault tolerance and limits of each solution.
Computer Engineering|Computer science
Rybka, Andrey, "Fault Tolerant, Self-Healing and Vendor Neutral Multi-Cloud Patterns and Framework Focusing on Deployment and Management" (2017). ETD Collection for Pace University. AAI10791155.
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