Optimization of Application Deployment Architecture in Container Orchestration
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 pro...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Politeknik Negeri Batam
2025-03-01
|
| Series: | Journal of Applied Informatics and Computing |
| Subjects: | |
| Online Access: | https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/8972 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850172225740603392 |
|---|---|
| author | Mochamad Rizal Fachrudin Ahmad Rofiqul Muslikh |
| author_facet | Mochamad Rizal Fachrudin Ahmad Rofiqul Muslikh |
| author_sort | Mochamad Rizal Fachrudin |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-a41dd47da4df41c48b4fecc2c540ed5d |
| institution | OA Journals |
| issn | 2548-6861 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Politeknik Negeri Batam |
| record_format | Article |
| series | Journal of Applied Informatics and Computing |
| spelling | doaj-art-a41dd47da4df41c48b4fecc2c540ed5d2025-08-20T02:20:08ZengPoliteknik Negeri BatamJournal of Applied Informatics and Computing2548-68612025-03-019238339210.30871/jaic.v9i2.89726561Optimization of Application Deployment Architecture in Container OrchestrationMochamad Rizal Fachrudin0https://orcid.org/0009-0009-7007-3786Ahmad Rofiqul Muslikh1https://orcid.org/0009-0000-2457-6803Universitas Merdeka MalangUniversitas Merdeka MalangContainer 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.https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/8972optimizationcluster architecturecontainer orchestrationdocker swarmload balancing |
| spellingShingle | Mochamad Rizal Fachrudin Ahmad Rofiqul Muslikh Optimization of Application Deployment Architecture in Container Orchestration Journal of Applied Informatics and Computing optimization cluster architecture container orchestration docker swarm load balancing |
| title | Optimization of Application Deployment Architecture in Container Orchestration |
| title_full | Optimization of Application Deployment Architecture in Container Orchestration |
| title_fullStr | Optimization of Application Deployment Architecture in Container Orchestration |
| title_full_unstemmed | Optimization of Application Deployment Architecture in Container Orchestration |
| title_short | Optimization of Application Deployment Architecture in Container Orchestration |
| title_sort | optimization of application deployment architecture in container orchestration |
| topic | optimization cluster architecture container orchestration docker swarm load balancing |
| url | https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/8972 |
| work_keys_str_mv | AT mochamadrizalfachrudin optimizationofapplicationdeploymentarchitectureincontainerorchestration AT ahmadrofiqulmuslikh optimizationofapplicationdeploymentarchitectureincontainerorchestration |