[{"data":1,"prerenderedAt":791},["ShallowReactive",2],{"/en-us/blog/how-we-built-a-structured-streamlit-application-framework-in-snowflake":3,"navigation-en-us":37,"banner-en-us":437,"footer-en-us":447,"blog-post-authors-en-us-Radovan Bacovic":689,"blog-related-posts-en-us-how-we-built-a-structured-streamlit-application-framework-in-snowflake":703,"assessment-promotions-en-us":743,"next-steps-en-us":781},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":27,"isFeatured":11,"meta":28,"navigation":29,"path":30,"publishedDate":20,"seo":31,"stem":34,"tagSlugs":35,"__hash__":36},"blogPosts/en-us/blog/how-we-built-a-structured-streamlit-application-framework-in-snowflake.yml","How We Built A Structured Streamlit Application Framework In Snowflake",[7],"radovan-bacovic",null,"engineering",{"featured":11,"template":12,"slug":13},false,"BlogPost","how-we-built-a-structured-streamlit-application-framework-in-snowflake",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"How we built a structured Streamlit Application Framework in Snowflake","Want to transform development from chaos to compliance? Learn how we implemented governance early on rather than retrofitting when maintenance costs climb exponentially.",[18],"Radovan Bacovic","https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097447/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%284%29_3LZkiDjHLjhqEkvOvBsVKp_1750097447404.png","2025-10-10","Recently, the GitLab Data team transformed scattered\n[Streamlit](https://streamlit.io/) applications into a unified, secure, and\nscalable solution for our Snowflake environment. To accomplish this, we\npacked Python, Snowflake, and Streamlit together with GitLab. Follow along\non this journey and discover the results we achieved, and learn how you can,\ntoo.\n\n## The challenge\n\nImagine this scenario: Your organization has dozens of Streamlit applications across different environments, running various Python versions, connecting to sensitive data with inconsistent security practices. Some apps work, others break mysteriously, and nobody knows who built what or how to maintain them.\n\n\nThis was exactly the challenge our data team faced. Applications were being created in isolation, with no standardization, no security oversight, and no clear deployment process. The result? A compliance nightmare and a maintenance burden that was growing exponentially.\n\n\n![Functional architectural design (high level)](https://res.cloudinary.com/about-gitlab-com/image/upload/v1760035999/i50lpkrwy9bok056rdak.png)\n\n\u003Cp>\u003C/p>\n\n\u003Ccenter>\u003Ci>Functional architectural design (high level)\u003C/i>\u003C/center>\n\n## How we started\n\nWe leveraged our unique position as customer zero by building this entire framework on GitLab's own CI/CD infrastructure and project management tools. Here are the ingredients we started with: \n\n1. [GitLab](https://about.gitlab.com/platform/) (product)\n\n1. [Snowflake](https://about.gitlab.com/platform/) - our single source of truth (SSOT) for the data warehouse activities (and more than that)\n\n1. [Streamlit](https://streamlit.io/) - an open-source tool for visual applications that has pure Python code under the hood\n\nThis provided us with immediate access to enterprise-grade DevSecOps capabilities, enabling us to implement automated testing, code review processes, and deployment pipelines from the outset. By utilizing GitLab's built-in features for issue tracking, merge requests, and automated deployments (CI/CD pipelines), we can iterate rapidly and validate the framework against real-world enterprise requirements. This internal-first approach ensured our solution was battle-tested on GitLab's own infrastructure before any external implementation.\n\n### The lessons we learned\n\nThe most critical lesson we learned from building the Streamlit Application Framework in Snowflake is that **structure beats chaos every time** — implement governance early rather than retrofitting it later when maintenance becomes exponential.\n\nYou also need to clearly define roles and responsibilities, separating infrastructure concerns from application development, so that each team can focus on its strengths.\n\nSecurity and compliance cannot be afterthoughts; they must be built into templates and automated processes from day one, as it's far easier to enforce consistent standards upfront than to force them after the fact. Invest heavily in automation and CI/CD pipelines, as manual processes don't scale and introduce human error.\n\n![Architecture of the framework (general overview)](https://res.cloudinary.com/about-gitlab-com/image/upload/v1760035998/qt9gfemxjnj8kjumkuh7.png)\n\n\u003Cp>\u003C/p>\n\n\u003Ccenter>\u003Ci>Architecture of the framework (general overview)\u003C/i>\u003C/center>\n\n##  How the Streamlit Application Framework changes everything\n\nThe Streamlit Application Framework turns a scattered approach into a structure. It gives developers freedom within secure guardrails, while automating deployment and eliminating maintenance complexity.\n\n### Three clear roles, one unified process\n\nThe framework introduces a structured approach with three distinct roles:\n\n1. **Maintainers** (Data team members and contributors) handle the infrastructure, including CI/CD pipelines, security templates, and compliance rules. They ensure the framework runs smoothly and stays secure.\n\n2. **Creators** (those who need to build applications) can focus on what they do best: creating visualizations, connecting to Snowflake data, and building user experiences. They have full flexibility to create new applications from scratch, add new pages to existing apps, integrate additional Python libraries, and build complex data visualisations — all without worrying about deployment pipelines or security configurations.\n\n3. **Viewers** (end users) access polished, secure applications without any technical overhead. All they need is Snowflake access.\n\n![Roles overview and their functionality](https://res.cloudinary.com/about-gitlab-com/image/upload/v1760035999/oatqyx3ug7vsgzishpma.png)\n\n\u003Cp>\u003C/p>\n\n\u003Ccenter>\u003Ci>Overview of roles and their functions\u003C/i>\u003C/center>\n\n## Automate everything\n\nBy implementing CI/CD, days of manual deployments and configuration headaches are gone. The framework provides:\n\n- **One-click environment preparation:** With a set of `make` commands, the environment is installed and ready in a few seconds.\n\n\n```yaml\n================================================================================\n✅ Snowflake CLI successfully installed and configured!\nConnection: gitlab_streamlit\nUser: YOU@GITLAB.COM\nAccount: gitlab\n================================================================================\nUsing virtualenv: /Users/YOU/repos/streamlit/.venv\n📚 Installing project dependencies...\nInstalling dependencies from lock file\nNo dependencies to install or update\n✅ Streamlit environment prepared!\n```\n\n- **Automated CI/CD pipelines:** Handle testing, code review, and deployment from development to production.\n\n- **Secure sandbox environments:** Provide for safe development and testing before production deployment.\n\n\n```yaml\n╰─$ make streamlit-rules\n🔍 Running Streamlit compliance check...\n================================================================================\nCODE COMPLIANCE REPORT\n================================================================================\nGenerated: 2025-07-09 14:01:16\nFiles checked: 1\n\nSUMMARY:\n\n✅ Passed: 1\n❌ Failed: 0\n\nSuccess Rate: 100.0%\n\nAPPLICATION COMPLIANCE SUMMARY:\n\n📱 Total Applications Checked: 1\n⚠️ Applications with Issues: 0\n📊 File Compliance Rate: 100.0%\n\nDETAILED RESULTS BY APPLICATION:\n...\n\n```\n\n\n- **Template-based application creation:** Ensures consistency across all applications and pages.\n\n\n```shell\n╰─$ make streamlit-new-page STREAMLIT_APP=sales_dashboard STREAMLIT_PAGE_NAME=analytics\n📝 Generating new Streamlit page: analytics for app: sales_dashboard\n📃 Create new page from template:\nPage name: analytics\nApp directory: sales_dashboard\nTemplate path: page_template.py\n✅ Successfully created 'analytics.py' in 'sales_dashboard' directory from template\n```\n\n\n- **Poetry-based dependency management:** Prevents version conflicts and maintains clean environments.\n\n- **Organized project structure:** Has dedicated folders for applications, templates, compliance rules, and configuration management.\n\n\n```text\n├── src/\n│   ├── applications/     # Folder for Streamlit applications\n│   │   ├── main_app/     # Main dashboard application\n│   │   ├── components/   # Shared components\n│   │   └── \u003Cyour_apps>/  # Your custom application\n│   │   └── \u003Cyour_apps2>/ # Your 2nd custom application\n│   ├── templates/        # Application and page templates\n│   ├── compliance/       # Compliance rules and checks\n│   └── setup/            # Setup and configuration utilities\n├── tests/                # Test files\n├── config.yml            # Environment configuration\n├── Makefile              # Build and deployment automation\n└── README.md             # Main README.md file\n```\n\n\n- **Streamlined workflow:** Takes local development through testing schema to production, all automated through GitLab CI/CD pipelines.\n\n\n![GitLab CI/CD pipelines for full automation of the process](https://res.cloudinary.com/about-gitlab-com/image/upload/v1760035998/usyma2jkgiazu9iay1au.png)\n\n\u003Cp>\u003C/p>\n\u003Ccenter>\u003Ci>GitLab CI/CD pipelines for full automation of the process\u003C/i>\u003C/center>\n\n## Security and compliance by design\n\nInstead of bolting on security as an afterthought, the structured Streamlit Application Framework builds it in from the ground up. Every application adheres to the same security standards, and compliance requirements are automatically enforced. Audit trails are maintained throughout the development lifecycle.\n\nWe introduce our compliance rules and verify them with a single command. For instance, we can list which classes and methods are mandatory to use, which files you should have, and which roles are allowed and which are forbidden to share the application with. The rules are flexible and descriptive; all you need to do is define them in a YAML file:\n\n\n```yaml\n\nclass_rules:\n  - name: \"Inherit code for the page from GitLabDataStreamlitInit\"\n    description: \"All Streamlit apps must inherit from GitLabDataStreamlitInit\"\n    severity: \"error\"\n    required: true\n    class_name: \"*\"\n    required_base_classes:\n      - \"GitLabDataStreamlitInit\"\n    required_methods:\n      - \"__init__\"\n      - \"set_page_layout\"\n      - \"setup_ui\"\n      - \"run\"\n\nfunction_rules:\n  - name: \"Main function required\"\n    description: \"Must have a main() function\"\n    severity: \"error\"\n    required: true\n    function_name: \"main\"\n\nimport_rules:\n  - name: \"Import GitLabDataStreamlitInit\"\n    description: \"Must import the mandatory base class\"\n    severity: \"error\"\n    required: true\n    module_name: \"gitlab_data_streamlit_init\"\n    required_items:\n      - \"GitLabDataStreamlitInit\"\n  - name: \"Import streamlit\"\n    description: \"Must import streamlit library\"\n    severity: \"error\"\n    required: true\n    module_name: \"streamlit\"\n\nfile_rules:\n  - name: \"Snowflake configuration required (snowflake.yml)\"\n    description: \"Each application must have a snowflake.yml configuration file\"\n    severity: \"error\"\n    required: true\n    file_pattern: \"**/applications/**/snowflake.yml\"\n    base_path: \"\"\n  - name: \"Snowflake environment required (environment.yml)\"\n    description: \"Each application must have a environment.yml configuration file\"\n    severity: \"error\"\n    required: true\n    file_pattern: \"**/applications/**/environment.yml\"\n    base_path: \"\"\n  - name: \"Share specification required (share.yml)\"\n    description: \"Each application must have a share.yml file\"\n    severity: \"warning\"\n    required: true\n    file_pattern: \"**/applications/**/share.yml\"\n    base_path: \"\"\n  - name: \"README.md required (README.md)\"\n    description: \"Each application should have a README.md file with a proper documentation\"\n    severity: \"error\"\n    required: true\n    file_pattern: \"**/applications/**/README.md\"\n    base_path: \"\"\n  - name: \"Starting point recommended (dashboard.py)\"\n    description: \"Each application must have a dashboard.py as a starting point\"\n    severity: \"warning\"\n    required: true\n    file_pattern: \"**/applications/**/dashboard.py\"\n    base_path: \"\"\n\nsql_rules:\n  - name: \"SQL files must contain only SELECT statements\"\n    description: \"SQL files and SQL code in other files should only contain SELECT statements for data safety\"\n    severity: \"error\"\n    required: true\n    file_extensions: [\".sql\", \".py\"]\n    select_only: true\n    forbidden_statements:\n      - ....\n    case_sensitive: false\n  - name: \"SQL queries should include proper SELECT statements\"\n    description: \"When SQL is present, it should contain proper SELECT statements\"\n    severity: \"warning\"\n    required: false\n    file_extensions: [\".sql\", \".py\"]\n    required_statements:\n      - \"SELECT\"\n    case_sensitive: false\n\nshare_rules:\n  - name: \"Valid functional roles in share.yml\"\n    description: \"Share.yml files must contain only valid functional roles from the approved list\"\n    severity: \"error\"\n    required: true\n    file_pattern: \"**/applications/**/share.yml\"\n    valid_roles:\n      - ...\n    safe_data_roles:\n      - ...\n  - name: \"Share.yml file format validation\"\n    description: \"Share.yml files must follow the correct YAML format structure\"\n    severity: \"error\"\n    required: true\n    file_pattern: \"**/applications/**/share.yml\"\n    required_keys:\n      - \"share\"\n    min_roles: 1\n    max_roles: 10\n\n```\n\n\nWith one command running:\n\n\n```bash\n\n╰─$ make streamlit-rules\n\n```\n\n\nWe can verify all the rules we have created and validate that the developers (who are building a Streamlit application) are following the policy specified by the creators (who determine the policies and building blocks of the framework), and that all the building blocks are in the right place. This ensures consistent behavior across all Streamlit applications.\n\n\n```yaml\n🔍 Running Streamlit compliance check...\n================================================================================\nCODE COMPLIANCE REPORT\n================================================================================\nGenerated: 2025-08-18 17:05:12\nFiles checked: 4\n\nSUMMARY:\n✅ Passed: 4\n❌ Failed: 0\nSuccess Rate: 100.0%\n\nAPPLICATION COMPLIANCE SUMMARY:\n📱 Total Applications Checked: 1\n⚠️ Applications with Issues: 0\n📊 File Compliance Rate: 100.0%\n\nDETAILED RESULTS BY APPLICATION:\n================================================================================\n✅ PASS APPLICATION: main_app\n------------------------------------------------------------\n📁 FILES ANALYZED (4):\n✅ dashboard.py\n📦 Classes: SnowflakeConnectionTester\n🔧 Functions: main\n📥 Imports: os, pwd, gitlab_data_streamlit_init, snowflake.snowpark.exceptions, streamlit\n\n✅ show_streamlit_apps.py\n📦 Classes: ShowStreamlitApps\n🔧 Functions: main\n📥 Imports: pandas, gitlab_data_streamlit_init, snowflake_session, streamlit\n\n✅ available_packages.py\n📦 Classes: AvailablePackages\n🔧 Functions: main\n📥 Imports: pandas, gitlab_data_streamlit_init, streamlit\n\n✅ share.yml\n👥 Share Roles: snowflake_analyst_safe\n\n📄 FILE COMPLIANCE FOR MAIN_APP:\n✅ Required files found:\n✓ snowflake.yml\n✓ environment.yml\n✓ share.yml\n✓ README.md\n✓ dashboard.py\n\nRULES CHECKED:\n----------------------------------------\nClass Rules (1):\n- Inherit code for the page from GitLabDataStreamlitInit (error)\n\nFunction Rules (1):\n- Main function required (error)\n\nImport Rules (2):\n- Import GitLabDataStreamlitInit (error)\n- Import streamlit (error)\n\nFile Rules (5):\n- Snowflake configuration required (snowflake.yml) (error)\n- Snowflake environment required (environment.yml) (error)\n- Share specification required (share.yml) (warning)\n- README.md required (README.md) (error)\n- Starting point recommended (dashboard.py) (warning)\n\nSQL Rules (2):\n- SQL files must contain only SELECT statements (error)\n🗄 SELECT-only mode enabled\n🚨 Forbidden: INSERT, UPDATE, DELETE, DROP, ALTER...\n- SQL queries should include proper SELECT statements (warning)\n\nShare Rules (2):\n- Valid functional roles in share.yml (error)\n👥 Valid roles: 15 roles defined\n🔒 Safe data roles: 11 roles\n- Share.yml file format validation (error)\n------------------------------------------------------------\n✅ Compliance check passed\n-----------------------------------------------------------\n```\n\n\n## Developer experience that works\n\nWhether you prefer your favorite IDE, a web-based development environment, or Snowflake Snowsight, the experience remains consistent. The framework provides:\n\n- **Template-driven development:** New applications and pages are created through standardized templates, ensuring consistency and best practices from day one. No more scattered design and elements.\n\n\n```yaml\n╰─$ make streamlit-new-app NAME=sales_dashboard\n🔧 Configuration Environment: TEST\n📝 Configuration File: config.yml\n📜 Config Loader Script: ./setup/get_config.sh\n🐍 Python Version: 3.12\n📁 Applications Directory: ./src/applications\n🗄 Database: ...\n📊 Schema: ...\n🏗 Stage: ...\n🏭 Warehouse: ...\n🆕 Creating new Streamlit app: sales_dashboard\nInitialized the new project in ./src/applications/sales_dashboard\n```\n\n\n- **Poetry package management:** All dependencies are managed through Poetry, creating isolated environments that won't disrupt your existing Python setup.\n\n\n```toml\n[tool.poetry]\nname = \"GitLab Data Streamlit\"\nversion = \"0.1.1\"\ndescription = \"GitLab Data Team Streamlit project\"\nauthors = [\"GitLab Data Team \u003C*****@gitlab.com>\"]\nreadme = \"README.md\"\n\n[tool.poetry.dependencies]\npython = \"\u003C3.13,>=3.12\"\nsnowflake-snowpark-python = \"==1.32.0\"\nsnowflake-connector-python = {extras = [\"development\", \"pandas\", \"secure-local-storage\"], version = \"^3.15.0\"}\nstreamlit = \"==1.22.0\"\nwatchdog = \"^6.0.0\"\ntypes-toml = \"^0.10.8.20240310\"\npytest = \"==7.0.0\"\nblack = \"==25.1.0\"\nimportlib-metadata = \"==4.13.0\"\npyyaml = \"==6.0.2\"\npython-qualiter = \"*\"\nruff = \"^0.1.0\"\ntypes-pyyaml = \"^6.0.12.20250516\"\njinja2 = \"==3.1.6\"\n\n[build-system]\nrequires = [\"poetry-core\"]\nbuild-backend = \"poetry.core.masonry.api\"\n```\n\n- **Multi-page application support:** Creators can easily build complex applications with multiple pages and add new libraries as needed. Multi-page applications are part of the framework and a developer is focusing on the logic, not the design and structuring.\n\n\n![Multipage application example (in Snowflake)](https://res.cloudinary.com/about-gitlab-com/image/upload/v1760035999/at1q2xgmjthkrgju4okm.png)\n\n\u003Cp>\u003C/p>\n\n\u003Ccenter>\u003Ci>Multipage application example (in Snowflake)\u003C/i>\u003C/center>\n\n\u003Cp>\u003C/p>\n\n- **Seamless Snowflake integration:** Built-in connectors and authentication handling for secure data access provide the same experience, whether in local development or directly in Snowflake.\n\n\n```yaml\nmake streamlit-push-test APPLICATION_NAME=sales_dashboard\n📤 Deploying Streamlit app to test environment: sales_dashboard\n...\n------------------------------------------------------------------------------------------------------------\n🔗 Running share command for application: sales_dashboard\nRunning commands to grant shares\n🚀 Executing: snow streamlit share sales_dashboard with SOME_NICE_ROLE\n✅ Command executed successfully\n📊 Execution Summary: 1/1 commands succeeded\n```\n\n- **Comprehensive Makefile:** All common commands are wrapped in simple Makefile commands, from local development to testing and deployment, including CI/CD pipelines.\n\n\n- **Safe local development:** Everything runs in isolated Poetry environments, protecting your system while providing production-like experiences.\n\n\n![Same experience despite the environment (example of the local development)](https://res.cloudinary.com/about-gitlab-com/image/upload/v1760035999/phmubsb34hn2mfefjvqh.png)\n\n\u003Cp>\u003C/p>\n\n\u003Ccenter>\u003Ci>Same experience despite the environment (example of the local development)\u003C/i>\u003C/center>\n\n\u003Cp>\u003C/p>\n\n- **Collaboration via code:** All applications and components are wrapped up in one repository, which allows the entire organization to collaborate on the same resources and avoid double work and redundant setup.\n\n## How you can get started\n\nIf you're facing similar challenges with scattered Streamlit applications, here's how to begin and move quickly:\n\n1. **Assess your current state:** Inventory your existing applications and identify pain points.\n\n2. **Define your roles:** Separate maintainer responsibilities from creator and end users' needs.\n\n3. **Start with templates:** Create standardized application templates that enforce your security and compliance requirements.\n\n4. **Implement CI/CD:** Automate your deployment pipeline to reduce manual errors and ensure consistency.\n\n\n![Deploy the application in Snowflake](https://res.cloudinary.com/about-gitlab-com/image/upload/v1760036003/mzge9s1fhkhnx38y1a3i.png)\n\n\u003Cp>\u003C/p>\n\n\u003Ccenter>\u003Ci>The application deployed in Snowflake\u003C/i>\u003C/center>\n\n\n## The bigger picture\n\n\nThis framework represents more than just a technical solution — it's a paradigm shift toward treating data applications as first-class citizens in your enterprise (data) architecture.\n\nBy providing structure without sacrificing flexibility, the GitLab Data team created an environment where anyone in the company with minimal technical knowledge can innovate rapidly while maintaining the highest standards of security and compliance.\n\n\n### What's next?\n\nWe're continuing to enhance the framework based on user feedback and emerging needs. Future improvements include expanded template libraries, enhanced monitoring capabilities, more flexibility, and a smoother user experience.\n\n**The goal isn't just to solve today's problems, but to create a foundation that scales with your organization's growing data application needs.**\n\n## Summary\n\n[The GitLab Data Team](https://handbook.gitlab.com/handbook/enterprise-data/) transformed dozens of scattered, insecure Streamlit applications with no standardization into a unified, enterprise-grade framework that separates roles cleanly:\n\n\n1. **Maintainers** handle infrastructure and security.\n\n2. **Creators** focus on building applications without deployment headaches.\n\n3. **Viewers** access polished, compliant apps.\n\n\nAnd we used these building blocks:\n\n1. Automated **CI/CD** pipelines\n\n2. Fully collaborative and versioned code in **git**\n\n3. **Template-based** development\n\n4. 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IIT Bombay students are coding the future with GitLab","At GitLab, we often talk about how software accelerates innovation. But sometimes, you have to step away from the Zoom calls and stand in a crowded university hall to remember why we do this.",[709],"Nick Veenhof","https://res.cloudinary.com/about-gitlab-com/image/upload/v1750099013/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%2814%29_6VTUA8mUhOZNDaRVNPeKwl_1750099012960.png","2026-01-08",[259,611,713],"open source","The GitLab team recently had the privilege of judging the **iHack Hackathon** at **IIT Bombay's E-Summit**. The energy was electric, the coffee was flowing, and the talent was undeniable. But what struck us most wasn't just the code — it was the sheer determination of students to solve real-world problems, often overcoming significant logistical and financial hurdles to simply be in the room.\n\n\nThrough our [GitLab for Education program](https://about.gitlab.com/solutions/education/), we aim to empower the next generation of developers with tools and opportunity. Here is a look at what the students built, and how they used GitLab to bridge the gap between idea and reality.\n\n## The challenge: Build faster, build securely\n\nThe premise for the GitLab track of the hackathon was simple: Don't just show us a product; show us how you built it. We wanted to see how students utilized GitLab's platform — from Issue Boards to CI/CD pipelines — to accelerate the development lifecycle.\n\nThe results were inspiring.\n\n## The winners\n\n### 1st place: Team Decode — Democratizing Scientific Research\n\n**Project:** FIRE (Fast Integrated Research Environment)\n\nTeam Decode took home the top prize with a solution that warms a developer's heart: a local-first, blazing-fast data processing tool built with [Rust](https://about.gitlab.com/blog/secure-rust-development-with-gitlab/) and Tauri. They identified a massive pain point for data science students: existing tools are fragmented, slow, and expensive.\n\nTheir solution, FIRE, allows researchers to visualize complex formats (like NetCDF) instantly. What impressed the judges most was their \"hacker\" ethos. They didn't just build a tool; they built it to be open and accessible.\n\n**How they used GitLab:** Since the team lived far apart, asynchronous communication was key. They utilized **GitLab Issue Boards** and **Milestones** to track progress and integrated their repo with Telegram to get real-time push notifications. As one team member noted, \"Coordinating all these technologies was really difficult, and what helped us was GitLab... the Issue Board really helped us track who was doing what.\"\n\n![Team Decode](https://res.cloudinary.com/about-gitlab-com/image/upload/v1767380253/epqazj1jc5c7zkgqun9h.jpg)\n\n### 2nd place: Team BichdeHueDost — Reuniting to Solve Payments\n\n**Project:** SemiPay (RFID Cashless Payment for Schools)\n\nThe team name, BichdeHueDost, translates to \"Friends who have been set apart.\" It's a fitting name for a group of friends who went to different colleges but reunited to build this project. They tackled a unique problem: handling cash in schools for young children. Their solution used RFID cards backed by a blockchain ledger to ensure secure, cashless transactions for students.\n\n**How they used GitLab:** They utilized [GitLab CI/CD](https://about.gitlab.com/topics/ci-cd/) to automate the build process for their Flutter application (APK), ensuring that every commit resulted in a testable artifact. This allowed them to iterate quickly despite the \"flaky\" nature of cross-platform mobile development.\n\n![Team BichdeHueDost](https://res.cloudinary.com/about-gitlab-com/image/upload/v1767380253/pkukrjgx2miukb6nrj5g.jpg)\n\n### 3rd place: Team ZenYukti — Agentic Repository Intelligence\n\n**Project:** RepoInsight AI (AI-powered, GitLab-native intelligence platform)\n\nTeam ZenYukti impressed us with a solution that tackles a universal developer pain point: understanding unfamiliar codebases. What stood out to the judges was the tool's practical approach to onboarding and code comprehension: RepoInsight-AI automatically generates documentation, visualizes repository structure, and even helps identify bugs, all while maintaining context about the entire codebase.\n\n**How they used GitLab:** The team built a comprehensive CI/CD pipeline that showcased GitLab's security and DevOps capabilities. They integrated [GitLab's Security Templates](https://gitlab.com/gitlab-org/gitlab/-/tree/master/lib/gitlab/ci/templates/Security) (SAST, Dependency Scanning, and Secret Detection), and utilized [GitLab Container Registry](https://docs.gitlab.com/user/packages/container_registry/) to manage their Docker images for backend and frontend components. They created an AI auto-review bot that runs on merge requests, demonstrating an \"agentic workflow\" where AI assists in the development process itself.\n\n![Team ZenYukti](https://res.cloudinary.com/about-gitlab-com/image/upload/v1767380253/ymlzqoruv5al1secatba.jpg)\n\n## Beyond the code: A lesson in inclusion\n\nWhile the code was impressive, the most powerful moment of the event happened away from the keyboard.\n\nDuring the feedback session, we learned about the journey Team ZenYukti took to get to Mumbai. They traveled over 24 hours, covering nearly 1,800 kilometers. Because flights were too expensive and trains were booked, they traveled in the \"General Coach,\" a non-reserved, severely overcrowded carriage.\n\nAs one student described it:\n\n*\"You cannot even imagine something like this... there are no seats... people sit on the top of the train. This is what we have endured.\"*\n\nThis hit home. [Diversity, Inclusion, and Belonging](https://handbook.gitlab.com/handbook/company/culture/inclusion/) are core values at GitLab. We realized that for these students, the barrier to entry wasn't intellect or skill, it was access.\n\nIn that moment, we decided to break that barrier. We committed to reimbursing the travel expenses for the participants who struggled to get there. It's a small step, but it underlines a massive truth: **talent is distributed equally, but opportunity is not.**\n\n![hackathon class together](https://res.cloudinary.com/about-gitlab-com/image/upload/v1767380252/o5aqmboquz8ehusxvgom.jpg)\n\n### The future is bright (and automated)\n\nWe also saw incredible potential in teams like Prometheus, who attempted to build an autonomous patch remediation tool (DevGuardian), and Team Arrakis, who built a voice-first job portal for blue-collar workers using [GitLab Duo](https://about.gitlab.com/gitlab-duo/) to troubleshoot their pipelines.\n\nTo all the students who participated: You are the future. Through [GitLab for Education](https://about.gitlab.com/solutions/education/), we are committed to providing you with the top-tier tools (like GitLab Ultimate) you need to learn, collaborate, and change the world — whether you are coding from a dorm room, a lab, or a train carriage. **Keep shipping.**\n\n> :bulb: Learn more about the [GitLab for Education program](https://about.gitlab.com/solutions/education/).\n",{"slug":716,"featured":11,"template":12},"how-iit-bombay-students-code-future-with-gitlab",{"content":718,"config":726},{"title":719,"description":720,"authors":721,"heroImage":722,"date":723,"category":9,"tags":724,"body":725},"Artois University elevates research and curriculum with GitLab Ultimate for Education","Artois University's CRIL leveraged the GitLab for Education program to gain free access to Ultimate, transforming advanced research and computer science curricula.",[709],"https://res.cloudinary.com/about-gitlab-com/image/upload/v1750099203/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%2820%29_2bJGC5ZP3WheoqzlLT05C5_1750099203484.png","2025-12-10",[611,259,23],"Leading academic institutions face a critical challenge: how to provide thousands of students and researchers with industry-standard, **full-featured DevSecOps tools** without compromising institutional control. Many start with basic version control, but the modern curriculum demands integrated capabilities for planning, security, and advanced CI/CD.\n\nThe **GitLab for Education program** is designed to solve this by providing access to **GitLab Ultimate** for qualifying institutions, allowing them to scale their operations and elevate their academic offerings. \n\nThis article showcases a powerful success story from the **Centre de Recherche en Informatique de Lens (CRIL)**, a joint laboratory of **Artois University** and CNRS in France. After years of relying solely on GitLab Community Edition (CE), the university's move to GitLab Ultimate through the GitLab for Education program immediately unlocked advanced capabilities, transforming their teaching, research, and contribution workflows virtually overnight. This story demonstrates why GitLab Ultimate is essential for institutions seeking to deliver advanced computer science and research curricula.\n\n## GitLab Ultimate unlocked: Managing scale and driving academic value\n\n**Artois University's** self-managed GitLab instance is a large-scale operation, supporting nearly **3,000 users** across approximately **19,000 projects**, primarily serving computer science students and researchers. While GitLab Community Edition was robust, the upgrade to GitLab Ultimate provided the sophisticated tooling necessary for managing this scale and facilitating advanced university-level work.\n\n***\"We can see the difference,\" says Daniel Le Berre, head of research at CRIL and the instance maintainer. \"It's a completely different product. Each week reveals new features that directly enhance our productivity and teaching.\"***\n\nThe institution joined the GitLab for Education program specifically because it covers both **instructional and non-commercial research use cases** and offers full access to Ultimate's features, removing significant cost barriers.\n\n### Key GitLab Ultimate benefits for students and researchers\n\n* **Advanced project management at scale:** Master's students now benefit from **GitLab Ultimate's project planning features**. This enables them to structure, track, and manage complex, long-term research projects using professional methodologies like portfolio management and advanced issue tracking that seamlessly roll up across their thousands of projects.\n\n* **Enhanced visibility:** Features like improved dashboards and code previews directly in Markdown files dramatically streamline tracking and documentation review, reducing administrative friction for both instructors and students managing large project loads.\n\n## Comprehensive curriculum: From concepts to continuous delivery\n\nGitLab Ultimate is deeply integrated into the computer science curriculum, moving students beyond simple `git` commands to practical **DevSecOps implementation**.\n\n* **Git fundamentals:** Students begin by visualizing concepts using open-source tools to master Git concepts.\n\n* **Full CI/CD implementation:** Students use GitLab CI for rigorous **Test-Driven Development (TDD)** in their software projects. They learn to build, test, and perform quality assurance using unit and integration testing pipelines—core competency made seamless by the integrated platform.\n\n* **DevSecOps for research and documentation:** The university teaches students that DevSecOps principles are vital for all collaborative work. Inspired by earlier work in Delft, students manage and produce critical research documentation (PDFs from Markdown files) using GitLab, incorporating quality checks like linters and spell checks directly in the CI pipeline. This ensures high-quality, reproducible research output.\n\n* **Future-proofing security skills:** The GitLab Ultimate platform immediately positions the institution to incorporate advanced DevSecOps features like SAST and DAST scanning as their research and development code projects grow, ensuring students are prepared for industry security standards.\n\n## Accelerating open source contributions with GitLab Duo\n\nAccess to the full GitLab platform, including our AI capabilities, has empowered students to make impactful contributions to the wider open source community faster than ever before.\n\nTwo Master's students recently completed direct contributions to the GitLab product, adding the **ORCID identifier** into user profiles. Working on GitLab.com, they leveraged **GitLab Duo's AI chat and code suggestions** to navigate the codebase efficiently.\n\n***\"This would not have been possible without GitLab Duo,\" Daniel Le Berre notes. \"The AI features helped students, who might have lacked deep codebase knowledge, deliver meaningful contributions in just two weeks.\"***\n\nThis demonstrates how providing students with cutting-edge tools **accelerates their learning and impact**, allowing them to translate classroom knowledge into real-world contributions immediately.\n\n## Empowering open research and institutional control\n\nThe stability of the self-managed instance at Artois University is key to its success. This model guarantees **institutional control and stability** — a critical factor for long-term research preservation.\n\nThe institution's expertise in this area was recently highlighted in a major 2024 study led by CRIL, titled: \"[Higher Education and Research Forges in France - Definition, uses, limitations encountered and needs analysis](https://hal.science/hal-04208924v4)\" ([Project on GitLab](https://gitlab.in2p3.fr/coso-college-codes-sources-et-logiciels/forges-esr-en)). The research found that the vast majority of public forges in French Higher Education and Research relied on **GitLab**. This finding underscores the consensus among academic leaders that self-hosted solutions are essential for **data control and longevity**, especially when compared to relying on external, commercial forges.\n\n## Unlock GitLab Ultimate for your institution today\n\nThe success story of **Artois University's CRIL** proves the transformative power of the GitLab for Education program. By providing **free access to GitLab Ultimate**, we enable large-scale institutions to:\n\n1.  **Deliver a modern, integrated DevSecOps curriculum.**\n\n2.  **Support advanced, collaborative research projects with Ultimate planning features.**\n\n3.  **Empower students to make AI-assisted open source contributions.**\n\n4.  **Maintain institutional control and data longevity.**\n\nIf your academic institution is ready to equip its students and researchers with the complete DevSecOps platform and its most advanced features, we invite you to join the program.\n\nThe program provides **free access to GitLab Ultimate** for qualifying instructional and non-commercial research use cases.\n\n**Apply now [online](https://about.gitlab.com/solutions/education/join/).**\n",{"slug":727,"featured":29,"template":12},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"content":729,"config":741},{"category":9,"tags":730,"body":732,"date":733,"updatedDate":734,"heroImage":735,"authors":736,"title":739,"description":740},[26,731,106],"git","\nEnterprise teams are increasingly migrating from Azure DevOps to GitLab to gain strategic advantages and accelerate secure software delivery. \n\n\n- GitLab comes with integrated controls, policies, and [compliance frameworks](https://docs.gitlab.com/user/compliance/compliance_frameworks/) that allow organizations to implement software delivery standards at scale. This is especially important for regulated industries.\n\n- [Security testing](https://docs.gitlab.com/user/application_security/) is embedded in the pipeline and results show in the developer workflow, including static application security testing (SAST), source code analysis (SCA), dynamic application security testing (DAST), infrastructure-as-code scanning (IaC), container scanning, and API scanning.\n\n- [AI capabilities](https://about.gitlab.com/gitlab-duo-agent-platform/) across the full software delivery lifecycle include advanced agent orchestration and customizable flows to support how your organizational teams work.\n\n\nGitLab's open-source, open-core approach, flexible deployment options such as single-tenant dedicated and self-managed, and truly unified platform eliminate integration complexity and security gaps. \n\n\nFor teams facing mounting pressure to accelerate delivery while strengthening security posture and maintaining regulatory compliance, GitLab represents not just a migration but a platform evolution.\n\n\nMigrating from Azure DevOps to GitLab can seem like a daunting task, but with the right approach and tools, it can be a smooth and efficient process. This guide will walk you through the steps needed to successfully migrate your projects, repositories, and pipelines from Azure DevOps to GitLab.\n\n\n## Overview\n\nGitLab provides both [Congregate](https://gitlab.com/gitlab-org/professional-services-automation/tools/migration/congregate/) (maintained by [GitLab Professional Services](https://about.gitlab.com/professional-services/) organization) and [a built-in Git repository import](https://docs.gitlab.com/user/project/import/repo_by_url/) for migrating projects from Azure DevOps (ADO). These options support repository-by-repository or bulk migration and preserve git commit history, branches, and tags. With Congregate and professional services tools, we support additional assets such as wikis, work items, CI/CD variables, container images, packages, pipelines, and more (see this [feature matrix](https://gitlab.com/gitlab-org/professional-services-automation/tools/migration/congregate/-/blob/master/customer/ado-migration-features-matrix.md)). Use this guide to plan and execute your migration and complete post-migration follow-up tasks.\n\n\nEnterprises migrating from ADO to GitLab commonly follow a multi-phase approach:\n\n\n- Migrate repositories from ADO to GitLab using Congregate or GitLab's built-in repository migration.\n\n- Migrate pipelines from Azure Pipelines to GitLab CI/CD.\n\n- Migrate remaining assets such as boards, work items, and artifacts to GitLab Issues, Epics, and the Package and Container Registries.\n\n\nHigh-level migration phases:\n\n\n```mermaid\ngraph LR\n    subgraph Prerequisites\n        direction TB\n        A[\"Set up identity provider (IdP) and\u003Cbr/>provision users\"]\n        A --> B[\"Set up runners and\u003Cbr/>third-party integrations\"]\n        B --> I[\"Users enablement and\u003Cbr/>change management\"]\n    end\n    \n    subgraph MigrationPhase[\"Migration phase\"]\n        direction TB\n        C[\"Migrate source code\"]\n        C --> D[\"Preserve contributions and\u003Cbr/> format history\"]\n        D --> E[\"Migrate work items and\u003Cbr/>map to \u003Ca href=\"https://docs.gitlab.com/topics/plan_and_track/\">GitLab Plan \u003Cbr/>and track work\"]\n    end\n    \n    subgraph PostMigration[\"Post-migration steps\"]\n        direction TB\n        F[\"Create or translate \u003Cbr/>ADO pipelines to GitLab CI\"]\n        F --> G[\"Migrate other assets\u003Cbr/>packages and container images\"]\n        G --> H[\"Introduce \u003Ca href=\"https://docs.gitlab.com/user/application_security/secure_your_application/\">security\u003C/a> and\u003Cbr/>SDLC improvements\"]\n    end\n    \n    Prerequisites --> MigrationPhase\n    MigrationPhase --> PostMigration\n\n    style A fill:#FC6D26\n    style B fill:#FC6D26\n    style I fill:#FC6D26\n    style C fill:#8C929D\n    style D fill:#8C929D\n    style E fill:#8C929D\n    style F fill:#FFA500\n    style G fill:#FFA500\n    style H fill:#FFA500\n```\n\n\n## Planning your migration\n\n\n**To plan your migration, ask these questions:**\n\n\n- How soon do we need to complete the migration?\n\n- Do we understand what will be migrated?\n\n- Who will run the migration?\n\n- What organizational structure do we want in GitLab?\n\n- Are there any constraints, limitations, or pitfalls that need to be taken into account?\n\n\nDetermine your timeline, as it will largely dictate your migration approach. Identify champions or groups familiar with both ADO and GitLab platforms (such as early adopters) to help drive adoption and provide guidance.\n\n\n**Inventory what you need to migrate:**\n\n\n- The number of repositories, pull requests, and contributors\n\n- The number and complexity of work items and pipelines\n\n- Repository sizes and dependency relationships\n\n- Critical integrations and runner requirements (agent pools with specific capabilities)\n\n\nUse GitLab Professional Services's [Evaluate](https://gitlab.com/gitlab-org/professional-services-automation/tools/utilities/evaluate#beta-azure-devops) tool to produce a complete inventory of your entire Azure DevOps organization, including repositories, PR counts, contributor lists, number of pipelines, work items, CI/CD variables and more. If you're working with the GitLab Professional Services team, share this report with your engagement manager or technical architect to help plan the migration.\n\n\nMigration timing is primarily driven by pull request count, repository size, and amount of contributions (e.g. comments in PR, work items, etc). For example, 1,000 small repositories with few PRs and limited contributors can migrate much faster than a smaller set of repositories containing tens of thousands of PRs and thousands of contributors. Use your inventory data to estimate effort and plan test runs before proceeding with production migrations.\n\n\nCompare inventory against your desired timeline and decide whether to migrate all repositories at once or in batches. If teams cannot migrate simultaneously, batch and stagger migrations to align with team schedules. For example, in Professional Services engagements, we organize migrations into waves of 200-300 projects to manage complexity and respect API rate limits, both in [GitLab](https://docs.gitlab.com/security/rate_limits/) and [ADO](https://learn.microsoft.com/en-us/azure/devops/integrate/concepts/rate-limits?view=azure-devops).\n\n\nGitLab's built-in [repository importer](https://docs.gitlab.com/user/project/import/repo_by_url/) migrates Git repositories (commits, branches, and tags) one-by-one. Congregate is designed to preserve pull requests (known in GitLab as merge requests), comments, and related metadata where possible; the simple built-in repository import focuses only on the Git data (history, branches, and tags).\n\n\n**Items that typically require separate migration or manual recreation:**\n\n\n- Azure Pipelines - create equivalent GitLab CI/CD pipelines (consult with [CI/CD YAML](https://docs.gitlab.com/ci/yaml/) and/or with [CI/CD components](https://docs.gitlab.com/ci/components/)). Alternatively, consider using AI-based pipeline conversion available in Congregate.\n\n- Work items and boards - map to GitLab Issues, Epics, and Issue Boards.\n\n- Artifacts, container images (ACR) - migrate to GitLab Package Registry or Container Registry.\n\n- Service hooks and external integrations - recreate in GitLab.\n\n- [Permissions models](https://docs.gitlab.com/user/permissions/) differ between ADO and GitLab; review and plan permissions mapping rather than assuming exact preservation.\n\n\nReview what each tool (Congregate vs. built-in import) will migrate and choose the one that fits your needs. Make a list of any data or integrations that must be migrated or recreated manually.\n\n\n**Who will run the migration?**\n\n\nMigrations are typically run by a GitLab group owner or instance administrator, or by a designated migrator who has been granted the necessary permissions on the destination group/project. Congregate and the GitLab import APIs require valid authentication tokens for both Azure DevOps and GitLab.\n\n\n- Decide whether a group owner/admin will perform the migrations or whether you will grant a specific team/person delegated access.\n\n- Ensure the migrator has correctly configured personal access tokens (Azure DevOps and GitLab) with the scopes required by your chosen migration tool (for example, api/read_repository scopes and any tool-specific requirements). \n\n- Test tokens and permissions with a small pilot migration.\n\n**Note:** Congregate leverages file-based import functionality for ADO migrations and requires instance administrator permissions to run ([see our documentation](https://docs.gitlab.com/user/project/settings/import_export/#migrate-projects-by-uploading-an-export-file)). If you are migrating to GitLab.com, consider engaging Professional Services. For more information, see the [Professional Services Full Catalog](https://about.gitlab.com/professional-services/catalog/). Non-admin account cannot preserve contribution attribution!\n\n\n**What organizational structure do we want in GitLab?**\n\nWhile it's possible to map ADO structure directly to GitLab structure, it's recommended to rationalize and simplify the structure during migration. Consider how teams will work in GitLab and design the structure to facilitate collaboration and access management. Here is a way to think about mapping ADO structure to GitLab structure:\n\n\n```mermaid\ngraph TD\n    subgraph GitLab\n        direction TB\n        A[\"Top-level Group\"]\n        B[\"Subgroup (optional)\"]\n        C[\"Projects\"]\n        A --> B\n        A --> C\n        B --> C\n    end\n\n    subgraph AzureDevOps[\"Azure DevOps\"]\n        direction TB\n        F[\"Organizations\"]\n        G[\"Projects\"]\n        H[\"Repositories\"]\n        F --> G\n        G --> H\n    end\n\n    style A fill:#FC6D26\n    style B fill:#FC6D26\n    style C fill:#FC6D26\n    style F fill:#8C929D\n    style G fill:#8C929D\n    style H fill:#8C929D\n```\n\nRecommended approach:\n\n\n- Map each ADO organization to a GitLab group (or a small set of groups), not to many small groups. Avoid creating a GitLab group for every ADO team project. Use migration as an opportunity to rationalize your GitLab structure.\n\n- Use subgroups and project-level permissions to group related repositories.\n\n- Manage access to sets of projects by using GitLab groups and group membership (groups and subgroups) rather than one group per team project.\n\n- Review GitLab [permissions](https://docs.gitlab.com/ee/user/permissions.html) and consider [SAML Group Links](https://docs.gitlab.com/user/group/saml_sso/group_sync/) to implement an enterprise RBAC model for your GitLab instance (or a GitLab.com namespace).\n\n\n**ADO Boards and work items: State of migration**\n\n\nIt's important to understand how work items migrate from ADO into GitLab Plan (issues, epics, and boards).\n\n\n- ADO Boards and work items map to GitLab Issues, Epics, and Issue Boards. Plan how your workflows and board configurations will translate.\n\n- ADO Epics and Features become GitLab Epics.\n\n- Other work item types (e.g., user stories, tasks, bugs) become project-scoped issues.\n\n- Most standard fields are preserved; selected custom fields can be migrated when supported.\n\n- Parent-child relationships are retained so Epics reference all related issues.\n\n- Links to pull requests are converted to merge request links to maintain development traceability.\n\n\nExample: Migration of an individual work item to a GitLab Issue, including field accuracy and relationships:\n\n\n![Example: Migration of an individual work item to a GitLab Issue](https://res.cloudinary.com/about-gitlab-com/image/upload/v1764769188/ztesjnxxfbwmfmtckyga.png)\n\n\nBatching guidance:\n\n\n- If you need to run migrations in batches, use your new group/subgroup structure to define batches (for example, by ADO organization or by product area).\n\n- Use inventory reports to drive batch selection and test each batch with a pilot migration before scaling.\n\n\n**Pipelines migration**\n\n\nCongregate [recently introduced](https://gitlab.com/gitlab-org/professional-services-automation/tools/migration/congregate/-/merge_requests/1298) AI-powered conversion for multi-stage YAML pipelines from Azure DevOps to GitLab CI/CD. This automated conversion works best for simple, single-file pipelines and is designed to provide a working starting point rather than a production-ready `.gitlab-ci.yml` file. The tool generates a functionally equivalent GitLab pipeline that you can then refine and optimize for your specific needs.\n\n\n- Converts Azure Pipelines YAML to `.gitlab-ci.yml` format automatically.\n\n- Best suited for straightforward, single-file pipeline configurations.\n\n- Provides a boilerplate to accelerate migration, not a final production artifact.\n\n- Requires review and adjustment for complex scenarios, custom tasks, or enterprise requirements.\n\n- Does not support Azure DevOps classic release pipelines — [convert these to multi-stage YAML](https://learn.microsoft.com/en-us/azure/devops/pipelines/release/from-classic-pipelines?view=azure-devops) first.\n\n\nRepository owners should review the [GitLab CI/CD documentation](https://docs.gitlab.com/ci/) to further optimize and enhance their pipelines after the initial conversion.\n\n\nExample of converted pipelines:\n\n\n```yml \n\n# azure-pipelines.yml\n\ntrigger:\n  - main\n\nvariables:\n  imageName: myapp\n\nstages:\n  - stage: Build\n    jobs:\n      - job: Build\n        pool:\n          vmImage: 'ubuntu-latest'\n        steps:\n          - checkout: self\n\n          - task: Docker@2\n            displayName: Build Docker image\n            inputs:\n              command: build\n              repository: $(imageName)\n              Dockerfile: '**/Dockerfile'\n              tags: |\n                $(Build.BuildId)\n\n  - stage: Test\n    jobs:\n      - job: Test\n        pool:\n          vmImage: 'ubuntu-latest'\n        steps:\n          - checkout: self\n\n          # Example: run tests inside the container\n          - script: |\n              docker run --rm $(imageName):$(Build.BuildId) npm test\n            displayName: Run tests\n\n  - stage: Push\n    jobs:\n      - job: Push\n        pool:\n          vmImage: 'ubuntu-latest'\n        steps:\n          - checkout: self\n\n          - task: Docker@2\n            displayName: Login to ACR\n            inputs:\n              command: login\n              containerRegistry: '\u003Cyour-acr-service-connection>'\n\n          - task: Docker@2\n            displayName: Push image to ACR\n            inputs:\n              command: push\n              repository: $(imageName)\n              tags: |\n                $(Build.BuildId)\n\n```\n\n```yaml\n\n# .gitlab-ci.yml\n\nvariables:\n  imageName: myapp\n\nstages:\n  - build\n  - test\n  - push\n\nbuild:\n  stage: build\n  image: docker:latest\n  services:\n    - docker:dind\n  script:\n    - docker build -t $imageName:$CI_PIPELINE_ID -f $(find . -name Dockerfile) .\n  only:\n    - main\n\ntest:\n  stage: test\n  image: docker:latest\n  services:\n    - docker:dind\n  script:\n    - docker run --rm $imageName:$CI_PIPELINE_ID npm test\n  only:\n    - main\n\npush:\n  stage: push\n  image: docker:latest\n  services:\n    - docker:dind\n  before_script:\n    - docker login -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWORD $CI_REGISTRY\n  script:\n    - docker tag $imageName:$CI_PIPELINE_ID $CI_REGISTRY/$CI_PROJECT_PATH/$imageName:$CI_PIPELINE_ID\n    - docker push $CI_REGISTRY/$CI_PROJECT_PATH/$imageName:$CI_PIPELINE_ID\n  only:\n    - main\n\n```\n\n**Final checklist:**\n\n\n- Decide timeline and batch strategy.\n\n- Produce a full inventory of repositories, PRs, and contributors.\n\n- Choose Congregate or the built-in import based on scope (PRs and metadata vs. Git data only).\n\n- Decide who will run migrations and ensure tokens/permissions are configured.\n\n- Identify assets that must be migrated separately (pipelines, work items, artifacts, and hooks) and plan those efforts.\n\n- Run pilot migrations, validate results, then scale according to your plan.\n\n\n## Running your migrations\n\n\nAfter planning, execute migrations in stages, starting with trial runs. Trial migrations help surface org-specific issues early and let you measure duration, validate outcomes, and fine-tune your approach before production.\n\n\nWhat trial migrations validate:\n\n\n- Whether a given repository and related assets migrate successfully (history, branches, tags; plus MRs/comments if using Congregate)\n\n- Whether the destination is usable immediately (permissions, runners, CI/CD variables, integrations)\n\n- How long each batch takes, to set schedules and stakeholder expectations\n\n\nDowntime guidance:\n\n\n- GitLab's built-in Git import and Congregate do not inherently require downtime.\n\n- For production waves, freeze changes in ADO (branch protections or read-only) to avoid missed commits, PR updates, or work items created mid-migration.\n\n- Trial runs do not require freezes and can be run anytime.\n\n\nBatching guidance:\n\n\n- Run trial batches back-to-back to shorten elapsed time; let teams validate results asynchronously.\n\n- Use your planned group/subgroup structure to define batches and respect API rate limits.\n\n\nRecommended steps:\n\n\n1. Create a test destination in GitLab for trials:\n\n\n  - GitLab.com: create a dedicated group/namespace (for example, my-org-sandbox)\n\n  - Self-managed: create a top-level group or a separate test instance if needed\n\n\n2. Prepare authentication:\n\n\n  - Azure DevOps PAT with required scopes.\n\n  - GitLab Personal Access Token with api and read_repository (plus admin access for file-based imports used by Congregate).\n\n\n3. Run trial migrations:\n\n\n  - Repos only: use GitLab's built-in import (Repo by URL)\n\n  - Repos + PRs/MRs and additional assets: use Congregate\n\n\n4. Post-trial follow-up:\n\n\n  - Verify repo history, branches, tags; merge requests (if migrated), issues/epics (if migrated), labels, and relationships.\n\n  - Check permissions/roles, protected branches, required approvals, runners/tags, variables/secrets, integrations/webhooks.\n\n  - Validate pipelines (`.gitlab-ci.yml`) or converted pipelines where applicable.\n\n\n5. Ask users to validate functionality and data fidelity.\n\n6. Resolve issues uncovered during trials and update your runbooks.\n\n7. Network and security:\n\n\n  - If your destination uses IP allow lists, add the IPs of your migration host and any required runners/integrations so imports can succeed.\n\n\n8. Run production migrations in waves:\n\n\n  - Enforce change freezes in ADO during each wave.\n\n  - Monitor progress and logs; retry or adjust batch sizes if you hit rate limits.\n\n\n9. Optional: remove the sandbox group or archive it after you finish.\n\n\n\u003Cfigure class=\"video_container\">\n  \u003Ciframe src=\"https://www.youtube.com/embed/ibIXGfrVbi4?si=ZxOVnXjCF-h4Ne0N\" frameborder=\"0\" allowfullscreen=\"true\">\u003C/iframe>\n\u003C/figure>\n\n\n## Terminology reference for GitLab and Azure DevOps\n\n| GitLab                                                           | Azure DevOps                                 | Similarities & Key Differences                                                                                                                                          |\n| ---------------------------------------------------------------- | -------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| Group                                                            | Organization                                 | Top-level namespace, membership, policies. ADO org contains Projects; GitLab Group contains Subgroups and Projects.                                                   |\n| Group or Subgroup                                                | Project                                      | Logical container, permissions boundary. ADO Project holds many repos; GitLab Groups/Subgroups organize many Projects.                                                |\n| Project (includes a Git repo)                                    | Repository (inside a Project)                | Git history, branches, tags. In GitLab, a \"Project\" is the repo plus issues, CI/CD, wiki, etc. One repo per Project.                                                  |\n| Merge Request (MR)                                               | Pull Request (PR)                            | Code review, discussions, approvals. MR rules include approvals, required pipelines, code owners.                                                                     |\n| Protected Branches, MR Approval Rules, Status Checks             | Branch Policies                              | Enforce reviews and checks. GitLab combines protections + approval rules + required status checks.                                                                    |\n| GitLab CI/CD                                                     | Azure Pipelines                              | YAML pipelines, stages/jobs, logs. ADO also has classic UI pipelines; GitLab centers on .gitlab-ci.yml.                                                               |\n| .gitlab-ci.yml                                                   | azure-pipelines.yml                          | Defines stages/jobs/triggers. Syntax/features differ; map jobs, variables, artifacts, and triggers.                                                                   |\n| Runners (shared/specific)                                        | Agents / Agent Pools                         | Execute jobs on machines/containers. Target via demands (ADO) vs tags (GitLab). Registration/scoping differs.                                                         |\n| CI/CD Variables (project/group/instance), Protected/Masked       | Pipeline Variables, Variable Groups, Library | Pass config/secrets to jobs. GitLab supports group inheritance and masking/protection flags.                                                                          |\n| Integrations, CI/CD Variables, Deploy Keys                       | Service Connections                          | External auth to services/clouds. Map to integrations or variables; cloud-specific helpers available.                                                                 |\n| Environments & Deployments (protected envs)                      | Environments (with approvals)                | Track deploy targets/history. Approvals via protected envs and manual jobs in GitLab.                                                                                 |\n| Releases (tag + notes)                                           | Releases (classic or pipelines)              | Versioned notes/artifacts. GitLab Release ties to tags; deployments tracked separately.                                                                               |\n| Job Artifacts                                                    | Pipeline Artifacts                           | Persist job outputs. Retention/expiry configured per job or project.                                                                                                  |\n| Package Registry (NuGet/npm/Maven/PyPI/Composer, etc.)           | Azure Artifacts (NuGet/npm/Maven, etc.)      | Package hosting. Auth/namespace differ; migrate per package type.                                                                                                     |\n| GitLab Container Registry                                        | Azure Container Registry (ACR) or others     | OCI images. GitLab provides per-project/group registries.                                                                                                             |\n| Issue Boards                                                     | Boards                                       | Visualize work by columns. GitLab boards are label-driven; multiple boards per project/group.                                                                         |\n| Issues (types/labels), Epics                                     | Work Items (User Story/Bug/Task)             | Track units of work. Map ADO types/fields to labels/custom fields; epics at group level.                                                                              |\n| Epics, Parent/Child Issues                                       | Epics/Features                               | Hierarchy of work. Schema differs; use epics + issue relationships.                                                                                                   |\n| Milestones and Iterations                                        | Iteration Paths                              | Time-boxing. GitLab Iterations (group feature) or Milestones per project/group.                                                                                       |\n| Labels (scoped labels)                                           | Area Paths                                   | Categorization/ownership. Replace hierarchical areas with scoped labels.                                                                                              |\n| Project/Group Wiki                                               | Project Wiki                                 | Markdown wiki. Backed by repos in both; layout/auth differ slightly.                                                                                                  |\n| Test reports via CI, Requirements/Test Management, integrations  | Test Plans/Cases/Runs                        | QA evidence/traceability. No 1:1 with ADO Test Plans; often use CI reports + issues/requirements.                                                                     |\n| Roles (Owner/Maintainer/Developer/Reporter/Guest) + custom roles | Access levels + granular permissions         | Control read/write/admin. Models differ; leverage group inheritance and protected resources.                                                                          |\n| Webhooks                                                         | Service Hooks                                | Event-driven integrations. Event names/payloads differ; reconfigure endpoints.                                                                                        |\n| Advanced Search                                                  | Code Search                                  | Full-text repo search. Self-managed GitLab may need Elasticsearch/OpenSearch for advanced features.                                                                   |\n","2025-12-03","2026-01-16","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749658924/Blog/Hero%20Images/securitylifecycle-light.png",[737,738],"Evgeny Rudinsky","Michael Leopard","Guide: Migrate from Azure DevOps to GitLab","Learn how to carry out the full migration from Azure DevOps to GitLab using GitLab Professional Services migration tools — from planning and execution to post-migration follow-up tasks.",{"featured":29,"template":12,"slug":742},"migration-from-azure-devops-to-gitlab",{"promotions":744},[745,759,770],{"id":746,"categories":747,"header":749,"text":750,"button":751,"image":756},"ai-modernization",[748],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":752,"config":753},"Get your AI maturity score",{"href":754,"dataGaName":755,"dataGaLocation":241},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":757},{"src":758},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":760,"categories":761,"header":762,"text":750,"button":763,"image":767},"devops-modernization",[23,557],"Are you just managing tools or shipping innovation?",{"text":764,"config":765},"Get your DevOps maturity score",{"href":766,"dataGaName":755,"dataGaLocation":241},"/assessments/devops-modernization-assessment/",{"config":768},{"src":769},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":771,"categories":772,"header":773,"text":750,"button":774,"image":778},"security-modernization",[25],"Are you trading speed for security?",{"text":775,"config":776},"Get your security maturity score",{"href":777,"dataGaName":755,"dataGaLocation":241},"/assessments/security-modernization-assessment/",{"config":779},{"src":780},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":782,"blurb":783,"button":784,"secondaryButton":789},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":785,"config":786},"Get your free trial",{"href":787,"dataGaName":48,"dataGaLocation":788},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":493,"config":790},{"href":52,"dataGaName":53,"dataGaLocation":788},1772652092698]