HACM: High Availability Control Method in Container-Based Microservice Applications Over Multiple Clusters

Abstract

Emerging cloud-native technologies, such as container runtime and container orchestrator, offer unprecedented agility in developing and running applications, especially when combined with microservice-style architecture. Several commercial Samsung Network products such as Samsung Element Management System (S-EMS), 5G Radio Access Network (RAN) & Core network elements are being redesigned to fit the microservice paradigm. The cloud environment allows enterprises to scale their applications on-demand with minimum cost; however, it is often difficult to use containers without sacrificing the many benefits offered by container technology. S-EMS manages 5G RAN & Core network elements (NEs) deployed nationwide, and systematically stores a huge volume of stateful data per second. Containers are characterized to have an ephemeral state, hence ‘stateful-ness’ aspect of S-EMS makes management more complex. The existing system in a container-based application does not support geo-redundancy where services/data are stateful/state dependent. In this paper, different challenges around geo-redundancy between different independent Kubernetes set up with active and standby modes between the sites where state-dependent data is stored in each site are described. To overcome these challenges, we propose the High Availability Control Method (HACM) - which enables the Kubernetes cluster to be active and standby, where state-dependent data and context-based operations are intrinsically supported by the underlying S-EMS container application. Our approach has been designed to maintain the geo-redundancy philosophy of cloud-native by associating the status of each site using high availability (HA), switching over services based on the health of applications, deciding state when there are conflicts in site state, and the option to auto fallback based on user preference and services are transferred between sites without user intervention with optimized storage that ensures consistency, persistence, reliability, and availability. Through evaluation, we show that HACM with S-EMS can facilitate geo-redundancy HA, while not posing a significant burden on the Cloud.