Implementasi Load Balancing pada Google Cloud Platform Untuk Membangun Online Learning
DOI:
https://doi.org/10.25126/jtiik.124Abstrak
Dalam era digital, institusi pendidikan menghadapi tantangan dalam menyediakan sistem pembelajaran daring yang andal, skalabel, dan responsif terhadap lonjakan pengguna. Salah satu permasalahan utama yang sering terjadi adalah bottleneck pada server web dan database, yang dapat menyebabkan penurunan performa saat jumlah pengguna meningkat secara signifikan. Penelitian ini bertujuan untuk mengatasi permasalahan tersebut dengan mengimplementasikan load balancing pada Google Cloud Platform (GCP) guna membangun platform pembelajaran daring berbasis Moodle yang optimal. Metode yang digunakan dalam penelitian ini mencakup perancangan dan implementasi infrastruktur berbasis layanan GCP, termasuk Compute Engine untuk hosting server web, Cloud SQL sebagai database terkelola, Cloud Memorystore Redis untuk caching guna mengurangi beban query pada database, serta Cloud Filestore untuk penyimpanan data. HTTPS Load Balancer digunakan untuk mendistribusikan lalu lintas pengguna secara merata ke beberapa instance server, sementara autoscaler diaktifkan untuk menyesuaikan kapasitas sumber daya secara dinamis sesuai kebutuhan pengguna. Hasil pengujian menunjukkan bahwa bottleneck utama pada sistem e-learning terjadi pada beban tinggi di database dan server web, yang dapat diatasi dengan caching dan load balancing. Implementasi ini memungkinkan sistem menangani lonjakan lalu lintas hingga 5.000 pengguna simultan. dengan penggunaan moodle data base mencapai 80,28 %, penggunaan autoscaling mencapai level 1,916. Utilisasi mulai menurun dan menunjukkan stabilisasi mendekati nilai 1. Stabilitas ini mengindikasikan bahwa autoscaler berhasil menyesuaikan jumlah instance dengan kebutuhan beban kerja, menjaga performa optimal aplikasi. Dengan demikian, penggunaan load balancing pada GCP terbukti meningkatkan keandalan, skalabilitas, dan efisiensi platform pembelajaran daring, serta memberikan panduan praktis bagi institusi pendidikan dalam mengadopsi teknologi cloud untuk mendukung kegiatan belajar-mengajar secara daring.
Abstract
In the digital era, educational institutions face the challenge of providing a reliable, scalable and responsive online learning system to the surge of users. One of the main problems that often occurs is bottleneck on the web server and database, which can cause performance degradation when the number of users increases significantly. This research aims to overcome this problem by implementing load balancing on Google Cloud Platform (GCP) to build an optimal Moodle-based online learning platform. The method used in this research includes the design and implementation of GCP service-based infrastructure, including Compute Engine for web server hosting, Cloud SQL as a managed database, Cloud Memorystore Redis for caching to reduce query load on the database, and Cloud Filestore for data storage. HTTPS Load Balancer is used to distribute user traffic evenly across multiple server instances, while autoscaler is enabled to dynamically adjust resource capacity according to user needs. The test results show that the main bottleneck in the e-learning system occurs at high loads on the database and web server, which can be addressed by caching and load balancing. This implementation allows the system to handle traffic spikes of up to 5,000 simultaneous users. with moodle data base utilization reaching 80.28%, autoscaling utilization reaching a level of 1.916. This stability indicates that the autoscaler successfully adjusts the number of instances to the needs of the workload, maintaining optimal application performance. Thus, the use of load balancing on GCP is proven to improve the reliability, scalability, and efficiency of the online learning platform, and provides practical guidance for educational institutions in adopting cloud technology to support online teaching and learning activities.
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