Ricerc@Sapienza

The ICT industry and specifically critical sectors, such as healthcare, transportation, energy and government, require as mandatory the compliance of ICT systems and services with legislation and regulation, as well as with standards. In the era of cloud computing, this compliance management issue is exacerbated by the distributed nature of the system and by the limited control that customers have on the services.

Autoscaling of containers can leverage performance measures from the different layers of the computational stack. This paper investigate the problem of selecting the most appropriate performance measure to activate auto-scaling actions aiming at guaranteeing QoS constraints. First, the correlation between absolute and relative usage measures and how a resource allocation decision can be influenced by them is analyzed in different workload scenarios. Absolute and relative measures could assume quite different values.

Today, a new technology is going to change the way cloud platforms are designed and managed. This technology is called container. A container is a software environment where to install an application or application component and all the library dependencies, the binaries, and a basic configuration needed to run the application. The container technology promises to solve many cloud application issues, for example the application portability problem and the virtual machine performance overhead problem.

Apache Cassandra is an highly scalable and available NoSql datastore, largely used by enterprises of each size and for application areas that range from entertainment to big data analytics. Managed Cassandra service providers are emerging to hide the complexity of the installation, fine tuning and operation of Cassandra virtual data centers (VDCs). This paper address the problem of energy efficient auto-scaling of Cassandra VDC in managed Cassandra data centers. We propose three energy-aware autoscaling algorithms: Opt, LocalOpt and LocalOpt-H.