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DevOps and CI/CD for Data Engineering Performance · LearnSpace
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courseraIT и технологии

DevOps and CI/CD for Data Engineering Performance

Курс от Coursera
Начальный≈ 14.2 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

You'll build the skills to manage, automate, and optimize production-grade data systems using industry-standard DevOps practices. By completing this course, you'll be able to resolve complex version control conflicts, design branching strategies for collaborative development, containerize data environments with Docker, automate infrastructure configuration with Ansible, deploy data pipelines through CI/CD workflows, and optimize query performance to maintain service levels. This course is unique because it bridges the gap between software engineering and data engineering — giving you hands-on experience with the exact tools and workflows used in real production environments. Rather than covering concepts in isolation, you'll integrate version control, containerization, automation, and performance tuning into a cohesive DevOps skillset that employers actively seek. Whether you're moving into a data engineering role or strengthening your current practice, you'll finish with portfolio-ready work that demonstrates job-ready capability.

Навыки, которые вы освоите

DevOpsCI/CDGit (Version Control System)Performance TuningContainerizationData PipelinesAnsibleInfrastructure as Code (IaC)Root Cause AnalysisConfiguration ManagementApplication DeploymentSoftware VersioningData InfrastructureVersion ControlDocker (Software)Development EnvironmentDevops ToolsContinuous IntegrationContinuous Deployment

Программа курса

13 модулей · 85 учебных материалов

01Apply Merge Conflict Resolution Techniques5 материалов
Applying Conflict Resolution Strategies in Real ScenariosDIALOGUEUnderstanding Merge Conflicts: Text vs Binary ChallengesВидеоConflict Resolution Decision Matrix for Data EngineersЧтениеResolving Text Conflicts in SQL Schema FilesВидео

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Professionals from the Industry

Преподаватель курса

DevOps and CI/CD for Data Engineering Performance
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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 14.2 ч

13 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Немецкий, Пушту, Испанский, Дари, Японский

Часть программы вашего университета
Conflict Resolution Knowledge CheckЗадание
02Analyze Commit History for Bug Tracing7 материалов
Why Git Forensics Transforms Debugging from Guesswork to ScienceВидеоGit Bisect: Binary Search Algorithm for Bug DetectionВидеоAdvanced Git History Analysis TechniquesЧтениеAutomated Git Bisect with Custom Test ScriptsВидеоSystematic Debugging Strategy DevelopmentDIALOGUEBug Tracing and Git History Analysis Knowledge CheckЗаданиеSQL Schema Merge Conflict Resolution Задание
03 Branching Strategy Fundamentals6 материалов
Why Version Control Strategy Matters in Data Engineering TeamsВидеоUnderstanding Branching Models and Team Collaboration PatternsЧтениеBranch Naming Conventions and Merge Protocol DesignВидеоAnalyzing Team Workflow Requirements for Strategy SelectionDIALOGUEDesign Your Team's Branching Workflow DocumentationЗаданиеBranching Strategy Fundamentals Knowledge CheckЗадание
04 Implementation & Process Design7 материалов
Scaling Development Teams Through Strategic ImplementationВидеоGitHub Branch Protection Rules and Workflow AutomationЧтениеConfiguring GitHub Branch Protection and Required ReviewsВидеоSetting Up Automated GitHub Actions for Branch WorkflowsВидеоEvaluating GitHub Implementation Challenges and SolutionsDIALOGUEGitHub Implementation and Workflow Automation Knowledge CheckЗаданиеComplete Branching Strategy Implementation ProjectЗадание
05Container Fundamentals & Multi-stage Dockerfiles7 материалов
Why Containerization Transforms Data Engineering WorkflowsВидеоContainer Fundamentals for Data Processing EnvironmentsВидеоMulti-stage Dockerfile Architecture for Data ProcessingЧтениеBuilding Multi-stage Dockerfiles for Spark Data ProcessingВидеоContainerization Strategy Planning for Data Processing EnvironmentsDIALOGUEBuild Production-Ready Multi-stage Dockerfile for Data ProcessingЛабораторнаяContainer Fundamentals Knowledge CheckЗадание
06Image Versioning & Registry Publishing7 материалов
Enterprise Container Registry Integration Value PropositionЧтениеSystematic Container Image Tagging for Data InfrastructureВидеоAmazon ECR Integration Patterns for Data Engineering TeamsЧтениеSetting Up Amazon ECR Repository and AuthenticationВидеоDeployment Integration Scenarios and Strategy PlanningDIALOGUEContainer Registry Integration and Deployment Workflow ConceptsЗаданиеComplete Containerization Workflow Mastery AssessmentЗадание
07 Configuration Management Foundations6 материалов
The Infrastructure Challenge: From Manual Chaos to Automated ExcellenceВидеоConfiguration Management Fundamentals for Data InfrastructureЧтениеAnsible Architecture and Automation WorkflowВидеоPlanning Your First Ansible Automation ProjectDIALOGUEDesign Your First Configuration Management StrategyЗаданиеAnsible Fundamentals Knowledge Check Задание
08Ansible Automation Implementation8 материалов
Enterprise Automation Success Stories: From Manual Chaos to Scalable InfrastructureЧтениеUnderstanding Ansible Playbooks: Components and StructureЧтениеAdvanced Playbook Features: Variables, Templates, and Error HandlingВидеоBuilding a Complete Python Web Server DeploymentВидеоOptimizing Ansible Playbooks for Production EnvironmentsDIALOGUECreate Ansible Playbooks for Automated Software InstallationЛабораторнаяAnsible Automation Implementation Knowledge CheckЗаданиеAnsible Automation Mastery AssessmentЗадание
09 CI/CD Pipeline Fundamentals6 материалов
Why Automated Deployments Transform Data OperationsВидеоCI/CD Pipeline Architecture for Data SystemsВидеоEssential CI/CD Tools and Technologies for Data TeamsЧтениеSetting Up Your First GitHub Actions WorkflowВидеоExploring CI/CD Implementation ScenariosDIALOGUECI/CD Pipeline Fundamentals Knowledge CheckЗадание
10 Automated Data Deployment8 материалов
Synthesizing CI/CD Pipeline Implementation for Production Data SystemsDIALOGUEEnterprise Data Deployment Challenges and Automation SolutionsЧтениеAdvanced GitHub Actions for Production DeploymentsВидеоMonitoring and Validation Strategies for Automated DeploymentsЧтениеBuilding Complete GitHub Actions Deployment PipelineВидеоAutomated Data Pipeline Deployment with GitHub ActionsЛабораторнаяAdvanced Data Deployment Automation Knowledge CheckЗаданиеComprehensive CI/CD Pipeline Implementation AssessmentЗадание
11 Query Performance Analysis Foundations7 материалов
Why Query Performance Analysis Prevents System FailuresВидеоQuery Performance Fundamentals for Data EngineersВидеоPostgreSQL Performance Monitoring Tools and TechniquesЧтениеInterpreting Query Execution Plans for OptimizationВидеоUsing pg_stat_activity to Identify Performance IssuesВидеоApplying Performance Analysis in Production ScenariosDIALOGUEPostgreSQL Performance Analysis Knowledge CheckЗадание
12Resource Allocation and Optimization6 материалов
Strategic Performance Optimization PlanningDIALOGUEStrategic Database Resource Allocation for Performance OptimizationЧтениеStrategic Resource Allocation for Service Level AgreementsВидеоImplementing Memory and Index Optimization in PostgreSQLВидеоPostgreSQL Resource Allocation Knowledge CheckЗаданиеQuery Performance Analysis and Resource Allocation MasteryЗадание
13Project: DevOps and CI/CD for Data Engineering Performance5 материалов
Why This Project MattersЧтениеProject RequirementsЧтениеAssignment: DevOps CI/CD Data Engineering WorkflowЧтениеGraded Quiz: DevOps and CI/CD for Data Engineering PerformanceЗаданиеSolution KeyЧтение