<![CDATA[The microservices architecture offers scalability and flexibility in modern application development; however, it often faces performance challenges due to inter-service communication overhead and data access latency. Distributed caching provides an effective solution to accelerate system responses by temporarily storing frequently accessed data. This study implements a Redis Cluster as a distributed cache within a microservices system consisting of three core services, deployed in a Docker Compose environment. The methodology includes the design of the caching architecture, integration of the Redis Cluster, and comparative performance evaluation using Apache JMeter. The evaluated parameters include latency, throughput, CPU usage, and database hit rate. The results indicate that employing Redis Cluster significantly reduces latency by up to 40.6%, increases throughput by 30.6%, and decreases database load by 58%. Overall, Redis Cluster proves to be an efficient, reliable, and scalable caching solution for enhancing the performance of microservices-based systems. Abstrak Arsitektur microservices menawarkan skalabilitas dan fleksibilitas dalam pengembangan aplikasi modern, namun sering menghadapi tantangan performa akibat beban komunikasi antar layanan dan latensi akses data. Distributed caching menjadi solusi untuk mempercepat respon sistem dengan menyimpan sementara data yang sering diakses. Penelitian ini mengimplementasikan Redis Cluster sebagai distributed cache pada sistem microservices yang terdiri dari tiga layanan utama dalam lingkungan Docker Compose. Metodologi mencakup perancangan arsitektur cache, integrasi Redis Cluster, serta pengujian performa komparatif menggunakan Apache JMeter. Parameter yang dievaluasi meliputi latency, throughput, penggunaan CPU, dan DB hit rate. Hasil menunjukkan bahwa penggunaan Redis Cluster secara signifikan mengurangi latency hingga 40,6%, meningkatkan throughput hingga 30,6%, dan menurunkan beban basis data hingga 58%. Redis Cluster terbukti sebagai solusi caching yang efisien, andal, dan skalabel dalam meningkatkan performa sistem microservices.]]>
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