AUTO SCALING DATABASE SERVICE WITH MICRO KUBERNETES CLUSTER - Anita Rosdina Nasution; Favian Dewanta; Bagus Aditya (Informatika, Universitas Jenderal Soedirman, 2022)
Data storage media, or what is often referred to as a database is something that is quite vital for technological developments. As the amount of data increases, it allows database services to experience downtime. For this reason, it is necessary to build an infrastructure that can replicate itself, so that it will avoid downtime. This infrastructure can be built using a container orchestration tool called Kubernetes which has high availability and autoscaler features, so it can replicate and guarantee service availability, to avoid downtime. This research builds a MongoDB NoSQL database service. This service is built using micro Kubernetes clusters from several different data centers. This service also implements a horizontal pod autoscaler feature that is capable of replicating pods, to increase high availability and avoid downtime. The autoscaling process will be tested by providing a load request for the service. Testing is done several times on each server. This study will compare the MongoDB service that was built monolithically with a micro Kubernetes cluster, and with HPA features and without HPA features by paying attention to several things. Based on Response Time, Response Code per Seconds, and CPU Usage, the results obtained are that the service built on a micro Kubernetes cluster with HPA features is the best, with a constant response time value below 100 ms, Response Code per Seconds reaches 500 threads per second. seconds, and CPU Usage in the range of 30 – 55%.