Big Data applications require extensive resources and environments to store, process and analyze this colossal collection of data in a distributed manner. Containerization with cloud computing provides a pertinent remedy to accommodate big data requirements, however requires a precise and appropriate load-balancing mechanism. The load on servers increases exponentially with increased resource usage thus making load balancing an essential requirement. Moreover, the adjustment of containers accurately and rapidly according to load as per services is one of the crucial aspects in big data applications. This study provides a review relating to containerized environments like Docker for big data applications with load balancing. A novel scheduling mechanism of containers for big data applications established on Docker Swarm and Microservice architecture is proposed. The concept of Docker Swarm is utilized to effectively handle big data applications' workload and service discovery. Results shows that increasing workloads with respect to big data applications can be effectively managed by utilizing microservices in containerized environments and load balancing is efficiently achieved using Docker Swarm. The implementation is done using a case study deployed on a single server and then scaled to four instances. Applications developed using containerized microservices reduces average deployment time and continuous integration.

In this study, acrylic-epoxy-based nanocomposite coatings loaded with different concentrations (0.5–3 wt.%) of graphene oxide (GO) nanoparticles were successfully prepared via the solution intercalation approach. The thermogravimetric analysis (TGA) revealed that the inclusion of GO nanoparticles into the polymer matrix increased the thermal stability of the coatings. The degree of transparency evaluated by the ultraviolet–visible (UV–Vis) spectroscopy showed that the lowest loading rate of GO (0.5 wt.%) had completely blocked the incoming irradiation, thus resulting in zero percent transmittance. Furthermore, the water contact angle (WCA) measurements revealed that the incorporation of GO nanoparticles and PDMS into the polymer matrix had remarkably enhanced the surface hydrophobicity, exhibiting the highest WCA of 87.55º. In addition, the cross-hatch test (CHT) showed that all the hybrid coatings exhibited excellent surface adhesion behaviour, receiving 4B and 5B ratings respectively. Moreover, the field emission scanning electron microscopy (FESEM) micrographs confirmed that the presence of the functional groups on the GO surface facilitated the chemical functionalization process, which led to excellent dispersibility. The GO composition up to 2 wt.% showed excellent dispersion and uniform distribution of the GO nanoparticles within the polymer matrix. Therefore, the unique features of graphene and its derivatives have emerged as a new class of nanofillers/inhibitors for corrosion protection applications.