Cloud and Data Technologies
We research and develop technologies for the new era where IoT, big data, and analytics meet on the cloud. In the emerging scenarios, enormous amounts of data generated by IoT are streamed and stored on the cloud, to be continuously exploited by analytic workloads. The scale of the data processing (in both throughput and size), combined with the scale and dynamic nature of the cloud resources, create new types of challenges as well as new opportunities, and this is where our work is focused. We are making the 'pipes' through which the data is streamed from its source to destination (e.g. from IoT frameworks to object storage, from storage to analytics applications) faster and smarter - optimizing both the streaming velocity and data transformation to make it analytics-ready. We work to improve the performance of analytic workloads on the cloud (such as those using Apache Spark), enable them to better exploit the scale and dynamic nature of the cloud and the data. Cloud operations at scale generates new types of problems which impact continuous availability and are difficult to debug; To help with this, we are developing a diagnostic framework which integrates root cause analysis with first-aid recovery operations, at scale. An important aspect is adapting to new economic models associated with cloud resources - we are working on cost optimization and a smart cloud brokering service.