• Naseer Ahmad Shinwari
• Dr. Neeta Sharma

big data is what most industries are working with for growing their businesses and making timely decisions to win the competitive data oriented market. Huge size and complexity of data have made people move their data to the cloud since cloud providers claim the automatic scalability of resources for applications to prevent demand unmet and resource wastage. Most cloud service providers do provide scalability but fail to meet SLA level QoS, especially in case of big data processing. Because their approach to scalability is based on prediction systems and threshold based which fails for sudden load changes and the time they take for provisioning new resources is degrading the performance. In this paper we have proposed a model for auto scalable big data as-a-service services of the cloud by combining vertical and horizontal scalability to prevent resource provisioning latency and be able to handle sudden changes in load to meet SLA level QoS.

auto-scalability, unpredictable load balancing, big data as-a-service, cloud scalability.

"AUTO SCALABLE BIG DATA AS-A-SERVICE IN THE CLOUD: AN EMPIRICAL STUDY", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.175-180, April-2019, Available :http://www.jetir.org/papers/JETIR1904I30.pdf

"AUTO SCALABLE BIG DATA AS-A-SERVICE IN THE CLOUD: AN EMPIRICAL STUDY", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp175-180, April-2019, Available at : http://www.jetir.org/papers/JETIR1904I30.pdf