An autonomic approach for fault tolerance using scaling, replication and monitoring in cloud computing

Cloud based systems are more popular in today's world but fault tolerance in cloud is a gigantic challenge, as it affects the reliability and availability for the end users. A number of tools have been deployed to minimize the impact of faults. A fault tolerable system ensures to perform continuous operation and produce correct results even after the failure of components up to some extent. More over huge amount of data in the cloud cannot monitor manually by the administrator. Automated tools, dynamic deploying of more servers are the basic requirements of the todays cloud system in order to handle unexpected traffic spikes in the network. This proposed work introduces an autonomic prospective on managing the fault tolerance which ensure scalability, reliability and availability. HAProxy has been used to provide scaling to the web servers for load balancing in proactive manner. It also monitors the web servers for fault prevention at the user level. Our framework works with autonomic mirroring and load balancing of data in database servers using MySQL master- master replication and Nginx respectively. Administrator keeps an eye on working of servers through Nagios tool 24×7 monitoring can't be done manually by the service provider. The proposed work has been implemented in the cloud virtualization environment. Experimental results show that our framework can deal with fault tolerance very effectively.