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借助人工智能实现高效的 DevSecOps 工作流程.pdf

上传人: 竿*** 编号:981521 2025-11-29 58页 11.03MB

1、 2024 GitLab Inc.QCon London 2024 Efficient DevSecOps workflows with a little help from AI 2024 GitLab Inc.Senior Developer AdvocatednsmichiMichael Friedrich 2024 GitLab Inc.This presentation contains research and resources about AI and efficient DevSecOps workflows,and focuses on practical use-case

2、s and learning pathways,not on specific products.It is important to note that the information presented is for informational purposes only.If you are interested in learning how GitLab integrates AI into the DevSecOps platform,refer to the following resources:1.https:/ 2.https:/ get started!2024 GitL

3、ab Inc.DevSecOps Cloud-NativePhoto by Jonatan Pie on Unsplash 2024 GitLab Inc.Where are you in your DevSecOps journey?MilestonesAssign IssueApprovalMerge AcceptedReleaseEpicsCreate a merge requestAutomated TestPush CodeScanCollaboration&reviewDeployIssuesHere?2024 GitLab Inc.Which is the most ineffi

4、cient task?MilestonesAssign IssueApprovalMerge AcceptedReleaseEpicsCreate a merge requestAutomated TestPush CodeScanCollaboration&reviewDeployIssues 2024 GitLab Inc.What if AI can help?Start with an assessment of your workflowsEstablish guardrails for AIMeasure the impact of AIBlog:How to put genera

5、tive AI to workin your DevSecOps environment AutomatedtestingImprovedsecurityImprovedplanningFaster codingFaster onboardingBetter documentationSource:2023 DevSecOps survey 2024 GitLab Inc.Workflows:DevPlan,Manage,Code,Tests,Docs,Reviews 2024 GitLab Inc.New projects,build tools,CI/CD config,code erro

6、rs,follow up questions.Wants:An all knowing Chat prompt.How:AI-assisted Chat prompt UI.Get HelpScreenshots from Anthropic workbench,Claude 3 2024 GitLab Inc.Plan:Start with issuesProposals take long to write How:Issue description generation,from a short summary into a more detailed summary.Example s

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根据报告的内容,本文主要探讨了如何利用人工智能(AI)提高DevSecOps工作流程的效率。以下是关键点: 1. **AI在DevSecOps中的应用**:AI可以帮助自动化测试、提高安全性、优化规划、加快编码、加速入职和改善文档。 2. **AI辅助工具**:例如,AI可以辅助生成问题描述、总结讨论、提供代码建议、生成测试用例、重构代码、分析CI/CD失败原因、进行安全漏洞分析和修复。 3. **AI的挑战**:包括数据隐私、安全、性能和可观察性。 4. **AI的透明度和治理**:需要确保AI的使用是透明的,并遵守AI伦理原则。 5. **AI的测量**:除了开发者生产力指标外,还应考虑团队满意度、代码质量、测试覆盖率等。 6. **AI的采纳**:GitLab建议将AI集成到产品和工作流程中,并建立相应的安全和管理框架。 7. **RAG(检索增强生成)**:结合外部知识库和LLM(大型语言模型)来提高AI的准确性和可靠性。 8. **AI代理**:构建自定义AI代理来处理更复杂的任务。
"AI赋能DevSecOps,效率翻倍?" "代码生成,AI来帮忙?" "AI守护,安全无忧?"
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