Unlocking Git's Power for DevOps Success

🚀 Day 7 of #100DaysOfDevOps Challenge Consistency is slowly turning into confidence! 💪 Today, I deepened my understanding of Git, one of the most essential tools in the DevOps ecosystem. Here’s what I explored: 🔹 Staging Changes with git add Learned how to stage specific files, multiple files, and entire directories before committing changes. 🔹 Staging vs Unstaging Understood how to move changes between the staging area and working directory using commands like git restore --staged. 🔹 Committing Changes Explored how to write meaningful commits and why good commit messages matter for collaboration and version tracking. 🔹 Best Practices for Commit Messages ✔️ Use imperative tone (e.g., “add”, “fix”) ✔️ Keep it short and descriptive ✔️ Focus on what and why, not how 🔹 Working with Remote Repositories git push to upload changes git pull to sync updates git clone to copy repositories 🔹 Branching in Git Learned how to create, switch, merge, and delete branches — a key concept for parallel development and team workflows. 💡 Git is not just about commands — it's about tracking progress, collaborating efficiently, and maintaining code integrity. Every command I learn is another step closer to becoming a better DevOps Engineer. 🌱 🔥 Keep learning. Keep building. Keep growing. #100DaysOfDevOps #DevOpsJourney #Git #VersionControl #LearnInPublic #TechLearning #CloudComputing #SoftwareEngineering #Linux #Automation #flm #ContinuousLearning #CareerGrowth #DevOpsEngineer #CodingJourney #BuildInPublic #TechCommunity #repost #DevSecOps #AIOps #MLOps #MultiCloud

👨💻 50-day journey to revisit and strengthen my DevOps engineering skills 📌 Day 2/50 📌 ⚙️ Tools I’ll be working with: Git | GitHub Actions Today, I focused on how local Git operations turn into real CI/CD execution using GitHub Actions. In production environments, every pipeline execution is a result of developer actions performed locally, making it critical to understand the complete flow from code creation to deployment trigger. 🔄 Flow Overview: 💠 Developer writes code locally 💠 Commits and pushes using Git 💠 Code is pushed to GitHub 💠 GitHub Actions workflow is triggered 💠 CI/CD pipeline executes (build, test, deploy) ➡️ Flow attached below 👇 📌 Note: Key CI/CD stability considerations as covered in Day 1 are critical. ➡️ For a more detailed understanding of GitHub Workflows and Actions, I’ve referred to the official documentation—feel free to explore it for deeper insights  🔗 https://lnkd.in/gm77PY7y 🚨 Possible Issue Scenario: A CI pipeline was set to trigger on every push to the main branch. A developer pushed changes without syncing with the latest remote updates, causing merge conflicts and pipeline failure due to inconsistent code. 🛠️ Resolution: Pulled latest changes from the repository Resolved conflicts locally Pushed updated code Pipeline re-triggered and executed successfully 💡 Always sync before pushing. ➡️ The key takeaway is that CI/CD pipelines are only as reliable as the version control practices behind them. Proper use of git pull, disciplined commits, and clean synchronization between local and remote repositories ensures smooth pipeline execution and avoids unnecessary failures. #DevOps #git #cicd #Github #skills #GithubCommands #Branchingstrategy #GithubActions #GithubDocs #Reskill #Workflow #Syntax

Understanding Git & GitHub Workflow as a DevOps Engineer 🚀 Here’s how I manage code efficiently using Git 👇 🔹 Basic Workflow: git clone → Copy repo to local git checkout -b feature-branch → Create new branch git add . → Stage changes git commit -m "message" → Save changes git push origin branch → Push to GitHub Create Pull Request (PR) Code review → Merge to main 🔹 Why this matters: ✅ Avoids code conflicts ✅ Enables team collaboration ✅ Keeps production stable ✅ Supports CI/CD pipelines 🔹 What I learned: Using proper branching strategy makes deployments safer and faster. Next step: Automating this workflow using Jenkins CI/CD 🚀 If you're learning DevOps, mastering Git is a must. #Git #GitHub #DevOps #CICD #LearningInPublic #AWS

What happens after you push your code to Git? 🤔 Day 16 of my DevOps Journey Today I started learning Jenkins and understood the backbone of DevOps — CI/CD ⚙️🚀 Until now, I was just pushing code… But what happens after that? That’s where CI/CD comes in. CI/CD explained simply: Continuous Integration (CI) → Combination of build + test Whenever a developer commits code to Git: • Code is automatically fetched • Build process starts • Unit tests are executed This helps us quickly know whether new code works with existing code or breaks it Continuous Delivery vs Continuous Deployment: • Continuous Delivery → Code is ready for deployment (manual approval needed) • Continuous Deployment → Code is automatically deployed to production after build & test CI/CD Pipeline stages: Version Control • Code is pushed using tools like Git Build • Code is compiled and prepared for execution Unit Testing • Code is tested to validate functionality Deploy • Application is deployed to environments (Dev/Test/Prod) After deployment, we can see the actual output of the application Tools used for CI/CD pipelines: Jenkins, GitHub Actions, GitLab CI, Azure Pipelines, AWS Pipelines, Travis CI, CircleCI, Harness Day 16 realization💡 Writing code is just the beginning. The real power lies in what happens after the commit. CI/CD makes sure: ✔ Code is tested instantly ✔ Issues are caught early ✔ Deployment becomes fast and reliable Now imagine: The moment code is committed It automatically builds → tests → deploys That’s CI/CD. That’s automation replacing manual effort. This is where DevOps actually begins⚡ Next — I’ll go deeper into Jenkins pipelines🔥 See you on Day 17 with Jenkins Installation and Access🚀 #DevOps #Jenkins #CICD #Automation #LearningInPublic #100DaysOfDevOps #Day16 #Git #Linux

☁️ Today’s DevOps Concept: Version Control in Infrastructure (Git + IaC) Continuing my 60‑day DevOps learning journey, today I built on yesterday’s Infrastructure as Code (IaC) concept by exploring how version control integrates with IaC. This connection is what truly transforms infrastructure into software. ✨ What I learned today: With IaC, every infrastructure change becomes a Git commit, and that unlocks some powerful advantages: 🔹 Traceability → Every change has a clear history 🔹 Collaboration → Multiple engineers can work on infrastructure safely 🔹 Review Process → Infra changes go through pull requests, just like code 🔹 Rollback Capabilities → Reverting infra becomes as easy as reverting a commit 🔹 Standardization → The entire organization follows the same templates & modules I practiced making small changes to a Terraform file, pushing it to Git, and watching how version control gives a complete picture of when and why each infrastructure change happened. Today’s biggest takeaway for me: “When your infrastructure is in Git, you gain control, visibility, and confidence.” Excited to dive into modules, state files, and automation next! #DevOps #IaC #Terraform #Git #CloudComputing #Automation #TechLearning

Understanding Workflow as a DevOps Engineer 🚀 Here’s how I manage code efficiently using Git 👇 🔹 Basic Workflow: git clone → Copy repo to local git checkout -b feature-branch → Create new branch git add . → Stage changes git commit -m "message" → Save changes git push origin branch → Push to GitHub Create Pull Request (PR) Code review → Merge to main 🔹 Why this matters: ✅ Avoids code conflicts ✅ Enables team collaboration ✅ Keeps production stable ✅ Supports CI/CD pipelines 🔹 What I learned: Using proper branching strategy makes deployments safer and faster. Next step: Automating this workflow using Jenkins CI/CD 🚀 If you're learning DevOps, mastering Git is a must. #Git #GitHub #DevOps #CICD #LearningInPublic #AWS

🚀 Day 2 – Git Learning Journey | Advanced Commands Continuing my DevOps preparation, today I explored some powerful Git commands that are widely used in real-time projects and interviews. 🔹 Key Concepts Covered: ⚙️ Git Config Used to set username and email for commits 🚫 .gitignore Helps exclude unnecessary files like logs, environment files, and dependencies ⏪ Git Reset Undo commits in different ways: Soft → keeps staged changes Mixed → keeps working directory Hard → removes everything ✏️ Git Amend Modify the last commit message or content 📜 Git Reflog Tracks all Git actions and helps recover lost commits 🍒 Git Cherry-pick Copy specific commits from one branch to another 💡 These concepts are extremely useful for troubleshooting, version control, and interview preparation. 🔥 Moving forward to Day 3 – Branching & Merging #Git #DevOps #AWS #LearningJourney #VersionControl #CloudComputing #CareerGrowth #frontlinesmedia #FLM

I used to think CI/CD was something only big companies with DevOps teams could have. Then I set up my first GitHub Actions pipeline in 20 minutes and shipped code to a server without touching it once. That's when it clicked. CI/CD isn't about the tools. It's about one thing: how fast do you find out something is broken? A bug caught in CI takes 5 minutes to fix. The same bug in production takes 5 hours, a post-mortem, and a very uncomfortable Slack thread. Here's what most tutorials skip: → A pipeline without tests is just a fancy way to deploy bugs faster → npm ci is NOT the same as npm install (use it in every pipeline) → Secrets in your YAML = secrets exposed to anyone who forks your repo → One massive job that does everything is the slowest way to get feedback → If nobody gets notified when the pipeline fails, the pipeline doesn't exist I put together a 12-page guide that breaks down exactly how CI/CD works, from first push to automated deployment. No fluff. No "it depends" answers. Real GitHub Actions YAML. Real pipeline stages. Common mistakes with the actual fixes. A cheat sheet you can keep open while building. If you've been putting off setting this up because it felt too complex, this is for you.

🚀 Day 13–15: Mastering Git & GitHub | DevOps Journey A little late in posting, but staying consistent with my learning journey 💪 Over the past few days, I focused on strengthening my understanding of Git & GitHub, which are essential tools for every developer and DevOps engineer. 🔹 What I Learned: Git fundamentals: version control, repositories, commits Complete workflow: working directory → staging → commit → push/pull Branching & merging for collaborative development Handling merge conflicts effectively Difference between git reset and git revert Importance of git reflog for recovering lost commits 🔹 Hands-on Practice: Initialized and cloned repositories Worked with branches for feature development Managed code changes using commits and pushes Simulated real-world workflows used in teams 🔹 Key Takeaways: Git is not just a tool, it’s a core skill for collaboration Writing meaningful commit messages improves project clarity Using branches ensures safe and scalable development Recovery tools like reflog are lifesavers in real projects 💡 This phase has helped me move closer to industry-level development and DevOps practices. 📌 Next Goal: Integrating Git with CI/CD pipelines and real-world projects #Git #GitHub #DevOps #LearningJourney #SoftwareDevelopment #Cloud #Engineering

If you are working with Git in DevOps, you need to understand Git LFS. Here is why 👇 There are use cases where you might need to push a large file to git. For example, - ML models - Datasets etc. But Git was designed for text files, not binaries. Every change stores the entire file again, which bloats your repository fast. GitHub also has a hard limit of 100MB per file. Also, large files make git clone slow and git pull heavy. This directly impacts your CI pipeline performance. This is exactly where Git Large File Storage (LFS) helps you. It is an open source Git extension for versioning large files. Instead of storing large files directly in your repo, Git LFS replaces them with a small pointer file. That pointer file contains the LFS version, a SHA-256 hash of the actual file, and the file size. The real file is stored separately in Git LFS storage, not inside your Git repository. So where does it actually store the file? If you are using GitHub, the large file is stored in GitHub’s managed storage, separate from your Git objects. If you're self-hosting, it can be stored in your own LFS server or object storage like S3. Tools like DVC use similar workflow for versioning data in MLOPS use cases. --- 19000+ engineers read our DevOps/MLOPS newsletter. 𝗦𝘂𝗯𝘀𝗰𝗿𝗶𝗯𝗲 𝗵𝗲𝗿𝗲 (𝗶𝘁’𝘀 𝗳𝗿𝗲𝗲): https://lnkd.in/guFma5_V #mlops