基于容器化的软件部署与管理技术研究
摘 要
随着云计算和微服务架构的快速发展，软件部署与管理面临日益复杂的挑战，传统虚拟化技术在资源利用率、部署效率及灵活性方面逐渐显现出局限性。为此，本文聚焦于基于容器化的软件部署与管理技术，旨在探索其在提升系统性能、简化运维流程以及支持弹性扩展方面的潜力。研究通过分析Docker、Kubernetes等主流容器技术的核心机制，结合实际应用场景设计并实现了一套高效的容器化部署与管理系统。该系统采用多层次架构，集成了自动化构建、动态调度及监控功能，显著优化了资源分配与任务执行效率。实验结果表明，与传统虚拟化方案相比，本研究提出的容器化方案能够将部署时间缩短约70%，同时降低约30%的资源开销。此外，本文创新性地提出了一种基于预测模型的容器负载均衡策略，有效提升了系统的稳定性和响应速度。
关键词：容器化技术 软件部署 Kubernetes
Abstract
With the rapid development of cloud computing and micro-service architecture, software deployment and management are facing increasingly complex challenges, and traditional virtualization technologies are gradually showing limitations in resource utilization, deployment efficiency, and flexibility. To this end, this paper focuses on containerization-based software deployment and management technologies to explore its potential to improve system performance, simplify operational processes, and support flexible expansion. By analyzing the core mechanism of mainstream container technology such as Docker and Kubernetes, the paper designs and realizes a set of efficient container deployment and management system combined with practical application scenarios. The system adopts a multi-level architecture, integrates automatic construction, dynamic scheduling and monitoring functions, and significantly optimizes the efficiency of resource allocation and task execution. The experimental results show that the containerization scheme proposed in this study can reduce deployment time by about 70% and reduce resource overhead by about 30% compared with traditional virtualization schemes. In addition, this paper innovatively proposes a container load balancing strategy based on the prediction model, which effectively improves the stability and response speed of the system.
Keyword:Containerization Technology Software Deployment Kubernetes
目 录
1绪论 1
1.1容器化技术的研究背景与意义 1
1.2国内外容器化技术研究现状分析 1
1.3本文研究方法与技术路线 2
2容器化部署技术原理与实现 2
2.1容器化部署的基本概念与框架 2
2.2容器编排工具的功能与比较 3
2.3部署流程中的关键问题分析 3
2.4容器镜像管理的技术挑战与优化 4
2.5实例解析 4
3容器化环境下的资源管理技术 4
3.1资源分配与调度的核心机制 5
3.2动态资源调整的实现策略 5
3.3容器性能监控与优化方法 5
3.4异常检测与故障恢复机制 6
3.5资源管理的实际应用案例 6
结论 7
参考文献 8
致谢 9
摘 要
随着云计算和微服务架构的快速发展，软件部署与管理面临日益复杂的挑战，传统虚拟化技术在资源利用率、部署效率及灵活性方面逐渐显现出局限性。为此，本文聚焦于基于容器化的软件部署与管理技术，旨在探索其在提升系统性能、简化运维流程以及支持弹性扩展方面的潜力。研究通过分析Docker、Kubernetes等主流容器技术的核心机制，结合实际应用场景设计并实现了一套高效的容器化部署与管理系统。该系统采用多层次架构，集成了自动化构建、动态调度及监控功能，显著优化了资源分配与任务执行效率。实验结果表明，与传统虚拟化方案相比，本研究提出的容器化方案能够将部署时间缩短约70%，同时降低约30%的资源开销。此外，本文创新性地提出了一种基于预测模型的容器负载均衡策略，有效提升了系统的稳定性和响应速度。
关键词：容器化技术 软件部署 Kubernetes
Abstract
With the rapid development of cloud computing and micro-service architecture, software deployment and management are facing increasingly complex challenges, and traditional virtualization technologies are gradually showing limitations in resource utilization, deployment efficiency, and flexibility. To this end, this paper focuses on containerization-based software deployment and management technologies to explore its potential to improve system performance, simplify operational processes, and support flexible expansion. By analyzing the core mechanism of mainstream container technology such as Docker and Kubernetes, the paper designs and realizes a set of efficient container deployment and management system combined with practical application scenarios. The system adopts a multi-level architecture, integrates automatic construction, dynamic scheduling and monitoring functions, and significantly optimizes the efficiency of resource allocation and task execution. The experimental results show that the containerization scheme proposed in this study can reduce deployment time by about 70% and reduce resource overhead by about 30% compared with traditional virtualization schemes. In addition, this paper innovatively proposes a container load balancing strategy based on the prediction model, which effectively improves the stability and response speed of the system.
Keyword:Containerization Technology Software Deployment Kubernetes
目 录
1绪论 1
1.1容器化技术的研究背景与意义 1
1.2国内外容器化技术研究现状分析 1
1.3本文研究方法与技术路线 2
2容器化部署技术原理与实现 2
2.1容器化部署的基本概念与框架 2
2.2容器编排工具的功能与比较 3
2.3部署流程中的关键问题分析 3
2.4容器镜像管理的技术挑战与优化 4
2.5实例解析 4
3容器化环境下的资源管理技术 4
3.1资源分配与调度的核心机制 5
3.2动态资源调整的实现策略 5
3.3容器性能监控与优化方法 5
3.4异常检测与故障恢复机制 6
3.5资源管理的实际应用案例 6
结论 7
参考文献 8
致谢 9
