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All Journal Techno.Com: Jurnal Teknologi Informasi JUTI: Jurnal Ilmiah Teknologi Informasi JURNAL NASIONAL TEKNIK ELEKTRO JOIV : International Journal on Informatics Visualization Jurnal Komputer Terapan Jurnal ABDINUS : Jurnal Pengabdian Nusantara DISTANCE: Journal of Data Science, Technology, and Computer Science Proceeding Applied Business and Engineering Conference
Muhammad Arif Fadhly Ridha
Politeknik Caltex Riau
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Journal : Proceeding Applied Business and Engineering Conference

 1 
IMPLEMENTASI KUBERNETES CLUSTER MENGGUNAKAN LXD CONTAINER Sarah Syifa Putri Nasution; Muhammad Arif Fadhly Ridha
ABEC Indonesia Vol. 9 (2021): 9th Applied Business and Engineering Conference
Publisher : Politeknik Caltex Riau

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Abstract

The use of cloud computing service enables clients to access data and information without having to install an application which increases the number of client requests that leads to the increase of server load and could result in overload. In clustering technology, the server workload will be distributed evenly to each server. To run clustering, a platform called Kubernetes is needed. Kubernetes is used for container management. To run a clustering with Kubernetes requires virtualization using LXD. This final project compares the performance of conventional model services and Kubernetes clusters. The test results of two servers in standby condition, the technology that uses the highest CPU and memory is the Kubernetes cluster which reached 104% on CPU usage, while memory usage is 28%. It is because of the nodes that are running on the virtual machine. In busy server conditions, conventional technology is the one that uses the highest CPU and memory due to the high, which reached 1289% on CPU usage while memory usage is 46%. Number of client requests that increase CPU and memory resources.
Monitoring Kubernetes Cluster MenggunakanPrometheus dan Grafana Salma Rachman Dira; Muhammad Arif Fadhly Ridha
ABEC Indonesia Vol. 10 (2022): 10th Applied Business and Engineering Conference
Publisher : Politeknik Caltex Riau

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Abstract

The large number of client requests can cause excessive workload on the server so that it can make the server down. Because it uses cloud computing services that can increase the number of client requests. With the cluster technology in cloud computing, the server workload will be divided evenly or balanced to each server. Clustering can be combined with containers where each process or application running on each container has the same kernel. Therefore, we need an application capable of managing containers, one of which is Kubernetes. Kubernetes has several components, namely clusters, pods, services and nodes that need to be monitored. To be able to carry out monitoring, an application that can help is used, namely Prometheus and Grafana. Prometheus will retrieve the data in Kubernetes, then the data that has been obtained by Prometheus can be visualized with Grafana. Grafana can convert metric data into graphs that are easy to understand and interactive. Based on the results of functionality testing that has been carried out, Prometheus has succeeded in reading data from the target server and Grafana has succeeded in displaying it in graphical form. In the test, from 5 trials of 20-100 user access, the monitoring system can show the amount of CPU usage, memory, and traffic load that can continue to increase according to the user's access load.
High Availability Service dengan Multiple Master pada Kubernetes Cluster Menggunakan Virtualisasi Kernel Based Virtual Machine (KVM) Nabila Firdha Aisyah; Muhammad Arif Fadhly Ridha
ABEC Indonesia Vol. 10 (2022): 10th Applied Business and Engineering Conference
Publisher : Politeknik Caltex Riau

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Abstract

Servers have an important role in managing and serving requests from clients. So that high availability is needed to handle risks in server use. Cluster technology is needed, so that the server load is shared evenly. However, to run clustering, it requires the application of a method, namely the HAProxy load balancer which works by evenly distributing the traffic load to the clustered physical servers. By implementing Kernel-Based Virtual Machine (KVM) virtualization technology. In KVM virtualization there is a technology used, namely Kubernetes. From the results of this final project, the results of the High Availability testing carried out are known that the server performance with scenario 5 access experiments 20-500 users with stress testing. Parameters measured are throughput and monitoring system usage of CPU, memory according to user access load. Which is the highest value of Througput on parameter 500 clients worth 1330.6/ sec. The presence of 2 servers provides performance test results. In standby, the lowest CPU usage and memory usage occurs on the main server, which is 0.07% and 24% because there are no nodes running on top of the virtual machine. In a busy state, the lowest CPU usage occurs on the main server is 1.06% due to the division of workload on virtual machines. The lowest memory usage occurs on the main server server is 24% because there are no nodes running on top of the virtual machine.
Co-Authors - Robinson Akbar, Memen Ardianto Wibowo Dwi Listiyanti Indah Lestari Khairul Gunawan Kiki Harapan Hutapea Maheswara, Galih Ihsan Nabila Firdha Aisyah Rahmat Suhatman Restu Riani Rika Perdana Sari, Rika Perdana Salma Rachman Dira Sarah Syifa Putri Nasution Sugeng Purwantoro E.S.G.S Thesa Nabila Balqis Tjung, Yuni Widya Tri Wulan Sari wisnu ramadhani