  Edge/Fog computing is a novel computing paradigm that provides
resource-limited Internet of Things (IoT) devices with scalable computing and
storage resources. Compared to cloud computing, edge/fog servers have fewer
resources, but they can be accessed with higher bandwidth and less
communication latency. Thus, integrating edge/fog and cloud infrastructures can
support the execution of diverse latency-sensitive and computation-intensive
IoT applications. Although some frameworks attempt to provide such integration,
there are still several challenges to be addressed, such as dynamic scheduling
of different IoT applications, scalability mechanisms, multi-platform support,
and supporting different interaction models. FogBus2, as a new python-based
framework, offers a lightweight and distributed container-based framework to
overcome these challenges. In this chapter, we highlight key features of the
FogBus2 framework alongside describing its main components. Besides, we provide
a step-by-step guideline to set up an integrated computing environment,
containing multiple cloud service providers (Hybrid-cloud) and edge devices,
which is a prerequisite for any IoT application scenario. To obtain this, a
low-overhead communication network among all computing resources is initiated
by the provided scripts and configuration files. Next, we provide instructions
and corresponding code snippets to install and run the main framework and its
integrated applications. Finally, we demonstrate how to implement and integrate
several new IoT applications and custom scheduling and scalability policies
with the FogBus2 framework.
