The increasing softwarization of network infrastructures introduces an important challenge for network configuration. On the one hand, the growth of the network configuration space as a result of new device types and the expanding inter-dependence of network service components, increases the network configuration complexity. On the other hand, new service deployment architectures lack mechanisms to validate the impact of service configuration on network resilience. Network operators need to adopt new mechanisms to validate and verify network configuration changes, inspired by popular Continuous Integration/Continuous Development (CI/CD) mechanisms. This paper introduces Network Emulation-based Automated Testing (NEAT), an automated testing framework for network configuration. NEAT allows network managers to define network topologies and tests through YAML files and run realistic network topologies and tests. Furthermore, network managers can control the fidelity of their network tests and bound the execution time of testing suites, as well as exploit parallelization of modern servers to speedup test execution.

Network softwarization has revitalized the interest of the network community towards emulation as an effective mechanism for network experimentation. Relevant platforms automate the deployment of virtual network topologies on a host, providing users the ability to manually run experimental scenarios. Whilst this may suit prototyping, modern development and deployment practices such as CI/CD depend on fully automated testing processes, built around high-level testing APIs and abstracting the challenges involved with synchronizing complex node interaction scenarios. In this paper, we present Network Emulation System (NES): a cloud-native, and highlyparallelizable Network Emulation as a Service (NEaaS) platform designed from the ground up to facilitate codeless experiment specification and to automate network testing workflows in cloud CI/CD environments. We demonstrate that NES offers a 8x speedup improvement in topology instantiation times in comparison to existing emulation platforms, and its life-cycle model can automate testing processes for complex service configurations using existing CI/CD platforms such as GitHub Actions.

Intent-based networking (IBN) systems have become the de-facto control abstraction to drive self-service, self-healing, and self-optimized capabilities in service delivery processes. Nonetheless, the operation complexity of modern network infrastructures make network practitioners apprehensive towards adoption in production, requiring further evidence for correctness. In this paper, we argue that testing, verification and monitoring should become first-class citizens in reference IBN architecture, in order to improve the detection errors during operations. Towards this goal, we present an extension for an intent architecture that allows IBN system to validate the correctness of network configuration using realistic network emulation. Furthermore, we present an intent use-case that ensure correct operation in hybrid networks.

Resilience in networks has often relied on high availability to ensure minimal disruption to end users when faults occur, but this has grown difficult for retaining state with the growing popularity of hardware middleboxes -blackbox hardware network functions that have served as an important part of network design in recent years. There is potential room for the introduction of Network Function Virtualisation (NFV) in the field of resilience in connection with middlebox usage. Rather than relying on overprovisioning, we propose Middlebox Minion (MiMi) VNF, a system design that can be inserted around inaccessible hardware. This recreates state in accordance with the middlebox function, using NFV to establish stateful failover mechanisms without the need to replace existing hardware. The experiment we present is a failover analogy examining the importance of state retention and the complexities involved with inaccessible hardware. Results suggest a promising improvement of connection quality and up to 60% lower loss when state can be preserved across failover instances, as well as potential for further exploration of the topic area.