Serverless Computing: A Comparative Analysis of Cloud Run and Cloud Function Prices on Google Kubernetes Engine Cluster Node Management Google Cloud
The advancement of cloud computing technology has revolutionized the way companies build and deploy applications, offering unprecedented flexibility, scalability, and efficiency. One of the most significant innovations in this space is serverless computing, which allows developers to build and run a...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
LPPM Universitas Mohammad Husni Thamrin
2025-07-01
|
| Series: | Jurnal Teknologi Informatika & Komputer |
| Online Access: | https://journal.thamrin.ac.id/index.php/jtik/article/view/2780 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | The advancement of cloud computing technology has revolutionized the way companies build and deploy applications, offering unprecedented flexibility, scalability, and efficiency. One of the most significant innovations in this space is serverless computing, which allows developers to build and run applications without managing the underlying server infrastructure. This model fundamentally changes the application development paradigm, shifting from static resource allocation to an event-driven model where resources are consumed only when needed (Sharma et al., 2021). The increasing adoption of serverless architectures has driven the need for detailed cost optimization strategies, particularly for automated infrastructure management tasks. This study examines the operational cost efficiency between Google Cloud Run and Google Cloud Functions. The study addresses the common need for programmatically managing cluster nodes within Google Kubernetes Engine. Solutions are developed and implemented using both serverless services to perform representative cluster management operations. A comprehensive analysis of pricing models, including resource consumption and invocation costs, is performed. Significant differences in operational costs are observed for this specific infrastructure automation scenario. The findings of this study provide clear guidance for architects and developers looking to minimize cloud spending through selecting the right platform. |
|---|---|
| ISSN: | 2656-9957 2622-8475 |