Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING Teknika
Fachrudin, Mochamad Rizal
Unknown Affiliation
Computer Science & IT Electrical & Electronics Engineering Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Implementation and Analysis of Container Image Optimization Using Alpine Linux and Multi-Stage Builds Fachrudin, Mochamad Rizal; Affandi, Arif Saivul
Teknika Vol. 14 No. 1 (2025): March 2025
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v14i1.1118

Abstract

Containerization enables isolation within a host, with Docker being a popular tool for packaging applications and their dependencies in container images. However, challenges like slow build processes and bloated image sizes can consume resources, slow down builds, and pose security risks. This study optimizes Docker images by combining the Alpine base image with multi-stage builds, analyzing size, build speed, and security across different combinations and environments to identify and propose the most efficient combination solution. The approach used is a quantitative quasi-experiment with a within-subject design. The sample used was a JavaScript framework, with the main experimental group being the combination of Alpine and multi-stage builds, while the comparison group included combinations of Node and Node-Alpine, both in single-stage and multi-stage configurations, as well as single-stage Alpine. Data was obtained from CI/CD, container registry, and Trivy reports. Analyzed by descriptive analysis, One-Way ANOVA or Kruskal Wallis test, and post-hoc test. The results show that combining multi-stage builds with Alpine is considered best practice because it produces the smallest image size, reducing it by up to 94% compared to single-stage Node. It also achieves the shortest build times across all environments and presents low vulnerability issues. However, it is important to note that while the Alpine multi-stage combination offers the most efficient build times, it experiences a 1.3x increase in duration in low-spec environments.
Optimization of Application Deployment Architecture in Container Orchestration Fachrudin, Mochamad Rizal; Muslikh, Ahmad Rofiqul
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.8972

Abstract

Container orchestration has become a widely adopted standard for application deployment among medium to large-scale organizations. Docker Swarm is one of the popular container orchestration tools due to its relatively simple configuration. However, if the Docker Swarm cluster architecture is not properly designed, the goal of container orchestration, which is availability, cannot be achieved optimally. Challenges such as centralized traffic on a single node and service dependency on a single node are critical issues that need to be addressed. This study proposes solutions through an experimental approach involving the design, implementation, testing, and evaluation of a Docker Swarm cluster architecture to address these challenges. The results of this study demonstrate that the proposed architecture successfully resolves these issues. Traffic can be distributed more evenly across all nodes. When only one node is available, 5 out of 10 requests can be handled with a response latency of 197.4 ms. With two nodes available, the number of requests handled increases to 7 out of 10, with a response latency of 534.86 ms. The greater the number of available nodes, the more requests can be successfully processed. Services also become more flexible, and capable of running on any node, while offering additional benefits such as dual load balancing through DNS-based load balancing and the default load balancing provided by Docker Swarm's routing mesh. However, limitations such as the need for more complex adjustments and configurations should be considered, especially when implementing this architecture in on-premise environments, to ensure the best adoption and results.
Co-Authors Arif Saivul Affandi Muslikh, Ahmad Rofiqul