Design and Implementation of Flutter based Multi-platform Docker Controller App

• URL: http://arxiv.org/abs/2502.11708v1
• Date: Mon, 17 Feb 2025 11:48:02 GMT
• Title: Design and Implementation of Flutter based Multi-platform Docker Controller App
• Authors: Adarsh Saxena, Sudhakar Singh, Shiv Prakash, Nand Lal Yadav, Tiansheng Yang, Rajkumar Singh Rathore, Shreya Singh,
• Abstract summary: This paper focuses on developing a Flutter application for controlling Docker resources remotely.<n>The application uses the SSH protocol to establish a secure connection with the server and execute the commands.<n>An alternative approach is also explored, which involves connecting the application with the Docker engine using HTTP.
• Score: 1.1443262816483672
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper focuses on developing a Flutter application for controlling Docker resources remotely. The application provides a user-friendly interface for executing various Docker-related commands on the server where the Docker engine is installed. The application uses the SSH protocol to establish a secure connection with the server and execute the commands. Further, an alternative approach is also explored, which involves connecting the application with the Docker engine using HTTP. This proposed Docker controller application provides a significant advantage for managing Docker resources remotely, which is highly beneficial in DevOps fields. It provides a user-friendly interface to manage containers, making it easy to create, start, stop, restart, and remove containers. It abstracts away the complexities of working with Docker commands, allowing users to interact with containers more intuitively. It can be used to manage a number of docker engines from one place making it easy to control and monitor all the docker resources. Its performance, security, and scalability are evaluated using various testing techniques, and the results are found satisfactory. Further improvements may include enhancing the application's features, optimizing the performance, and exploring other possible approaches for establishing the connection between the application and the Docker engine.

Related papers

• Toward Automated Test Generation for Dockerfiles Based on Analysis of Docker Image Layers [1.1879716317856948]
  The process for building a Docker image is defined in a text file called a Dockerfile. A Dockerfile can be considered as a kind of source code that contains instructions on how to build a Docker image. We propose an automated test generation method for Dockerfiles based on processing results rather than processing steps.
  arXiv  Detail & Related papers  (2025-04-25T08:02:46Z)
• UFO2: The Desktop AgentOS [60.317812905300336]
  UFO2 is a multiagent AgentOS for Windows desktops that elevates into practical, system-level automation. We evaluate UFO2 across over 20 real-world Windows applications, demonstrating substantial improvements in robustness and execution accuracy over prior CUAs. Our results show that deep OS integration unlocks a scalable path toward reliable, user-aligned desktop automation.
  arXiv  Detail & Related papers  (2025-04-20T13:04:43Z)
• An LLM-based Agent for Reliable Docker Environment Configuration [9.436480907117415]
  Repo2Run is an agent designed to fully automate environment configuration and generate executable Dockerfiles for arbitrary Python repositories. We address two major challenges: (1) enabling the LLM agent to configure environments within isolated Docker containers, and (2) ensuring the successful configuration process is recorded and accurately transferred to a Dockerfile without error. We evaluate Repo2Runon our proposed benchmark of 420 recent Python repositories with unit tests, where it achieves an 86.4% success rate, outperforming the best baseline by 63.9%.
  arXiv  Detail & Related papers  (2025-02-19T12:51:35Z)
• Cognitive Kernel: An Open-source Agent System towards Generalist Autopilots [54.55088169443828]
  We introduce Cognitive Kernel, an open-source agent system towards the goal of generalist autopilots.<n>Unlike copilot systems, which primarily rely on users to provide essential state information, autopilot systems must complete tasks independently.<n>To achieve this, an autopilot system should be capable of understanding user intents, actively gathering necessary information from various real-world sources, and making wise decisions.
  arXiv  Detail & Related papers  (2024-09-16T13:39:05Z)
• Securing 3rd Party App Integration in Docker-based Cloud Software Ecosystems [0.0]
  We present a new concept for significant security improvements for cloud-based software ecosystems using Docker for 3rd party app integration. Based on the security features of Docker we describe a secure integration of applications in the cloud environment securely.
  arXiv  Detail & Related papers  (2024-05-18T15:26:38Z)
• AgentScope: A Flexible yet Robust Multi-Agent Platform [66.64116117163755]
  AgentScope is a developer-centric multi-agent platform with message exchange as its core communication mechanism. The abundant syntactic tools, built-in agents and service functions, user-friendly interfaces for application demonstration and utility monitor, zero-code programming workstation, and automatic prompt tuning mechanism significantly lower the barriers to both development and deployment.
  arXiv  Detail & Related papers  (2024-02-21T04:11:28Z)
• Patterns of Multi-Container Composition for Service Orchestration with Docker Compose [5.1861106408299635]
  This work curates a dataset of successful projects that employ Docker Compose as an orchestration tool to run multiple service containers. The collection of data and analysis enables the identification and naming of repeating multi-container composition patterns. These patterns highlight how software systems are orchestrated in the real-world and can give examples to anybody wishing to compose their own service orchestrations.
  arXiv  Detail & Related papers  (2023-05-18T20:32:58Z)
• DRIVE: Dockerfile Rule Mining and Violation Detection [6.510749313511299]
  A Dockerfile defines a set of instructions to build Docker images, which can then be instantiated to support containerized applications. Recent studies have revealed a considerable amount of quality issues with Dockerfiles. We propose a novel approach to mine implicit rules and detect potential violations of such rules in Dockerfiles.
  arXiv  Detail & Related papers  (2022-12-12T01:15:30Z)
• Studying the Practices of Deploying Machine Learning Projects on Docker [9.979005459305117]
  Docker is a containerization service that allows for convenient deployment of websites, databases, applications' APIs, and machine learning (ML) models with a few lines of code. We conducted an exploratory study to understand how Docker is being used to deploy ML-based projects.
  arXiv  Detail & Related papers  (2022-06-01T18:13:30Z)
• Repro: An Open-Source Library for Improving the Reproducibility and Usability of Publicly Available Research Code [74.28810048824519]
  Repro is an open-source library which aims at improving the usability of research code. It provides a lightweight Python API for running software released by researchers within Docker containers.
  arXiv  Detail & Related papers  (2022-04-29T01:54:54Z)
• Interactive Visualization of Protein RINs using NetworKit in the Cloud [57.780880387925954]
  In this paper, we consider an example from protein dynamics, specifically residue interaction networks (RINs) We use NetworKit to build a cloud-based environment that enables domain scientists to run their visualization and analysis on large compute servers. To demonstrate the versatility of this approach, we use it to build a custom Jupyter-based widget for RIN visualization.
  arXiv  Detail & Related papers  (2022-03-02T17:41:45Z)
• AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks [68.58179110398439]
  Existing GAN compression algorithms are limited to handling specific GAN architectures and losses.<n>Inspired by the recent success of AutoML in deep compression, we introduce AutoML to GAN compression and develop an AutoGAN-Distiller framework.<n>We evaluate AGD in two representative GAN tasks: image translation and super resolution.
  arXiv  Detail & Related papers  (2020-06-15T07:56:24Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.