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𝐌𝐋𝐎𝐩𝐬 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 The world of Machine Learning (ML) is booming, and DevOps engineers have a golden opportunity to expand their skillset with MLOps. Here's why: 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 -> https://lnkd.in/gj-tfEyH 1. 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐟𝐨𝐫 𝐌𝐋 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬: MLOps is like DevOps, but for ML. You already automate software pipelines – MLOps lets you do the same for ML models, streamlining everything from data collection to training and deployment. 2. 𝐑𝐞𝐥𝐢𝐚𝐛𝐥𝐞 𝐌𝐋 𝐰𝐢𝐭𝐡 𝐂𝐈/𝐂𝐃: Remember how CI/CD ensures robust software? MLOps extends that to ML models. It guarantees your models are just as reliable as any other software you deploy. 3. 𝐊𝐞𝐞𝐩𝐢𝐧𝐠 𝐌𝐋 𝐌𝐨𝐝𝐞𝐥𝐬 𝐒𝐡𝐚𝐫𝐩: Unlike traditional software, ML models can "drift" over time and lose accuracy. Your DevOps expertise in monitoring and maintenance is invaluable here – you can ensure ML systems stay stable and performant. 4. 𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐁𝐫𝐢𝐝𝐠𝐞𝐬: Just like DevOps connected development and operations, MLOps fosters collaboration between data scientists and operations teams. This smoother workflow leads to better ML projects. 5. 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 𝐚𝐬 𝐂𝐨𝐝𝐞 𝐟𝐨𝐫 𝐌𝐋:  MLOps relies heavily on IaC, a familiar concept for DevOps engineers. You can leverage your infrastructure management skills to create consistent and repeatable ML environments. By embracing MLOps, DevOps engineers can play a pivotal role in the exciting world of ML. It's a chance to not only expand your skillset but also contribute to the future of AI-powered applications. 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 -> https://lnkd.in/gj-tfEyH #devops #engineering #softwareengineering #kubernetes #docker

𝐆𝐢𝐭𝐇𝐮𝐛 𝐂𝐡𝐞𝐚𝐭𝐬𝐡𝐞𝐞𝐭 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 -> https://lnkd.in/gj-tfEyH 1. 𝐑𝐞𝐩𝐨𝐬𝐢𝐭𝐨𝐫𝐲 𝐁𝐚𝐬𝐢𝐜𝐬: - Clone a Repository: Command: git clone <repository_url> - Initialize a Repository: Command: git init 2. 𝐖𝐨𝐫𝐤𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐁𝐫𝐚𝐧𝐜𝐡𝐞𝐬: - Create a New Branch: Command: git branch <branch_name> - Switch to a Branch: Command: git checkout <branch_name> - Create and Switch to a New Branch: Command: git checkout -b <new_branch_name> - List Branches: Command: git branch 3. 𝐂𝐨𝐦𝐦𝐢𝐭𝐭𝐢𝐧𝐠 𝐂𝐡𝐚𝐧𝐠𝐞𝐬: - Stage Changes: Command: git add <file_name> - Stage All Changes: Command: git add . - Commit Changes: Command: git commit -m "Commit message" 4. 𝐏𝐮𝐥𝐥𝐢𝐧𝐠 𝐚𝐧𝐝 𝐏𝐮𝐬𝐡𝐢𝐧𝐠: - Pull Changes from Remote: Command: git pull origin <branch_name> - Push Changes to Remote: Command: git push origin <branch_name> 5. 𝐌𝐞𝐫𝐠𝐢𝐧𝐠 𝐂𝐡𝐚𝐧𝐠𝐞𝐬: - Merge Branch into Current Branch: Command: git merge <branch_name> 6. 𝐖𝐨𝐫𝐤𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐑𝐞𝐦𝐨𝐭𝐞𝐬: - Add a Remote Repository: Command: git remote add <remote_name> <repository_url> - List Remote Repositories: Command: git remote -v 7. 𝐇𝐚𝐧𝐝𝐥𝐢𝐧𝐠 𝐂𝐨𝐧𝐟𝐥𝐢𝐜𝐭𝐬: - Check for Conflicts: Command: git diff - Resolve Conflicts and Continue Merge: Command: git add <file_name> git merge --continue 8. 𝐆𝐢𝐭𝐇𝐮𝐛 𝐀𝐜𝐭𝐢𝐨𝐧𝐬: - Workflow Syntax Checking: Command: git pull origin <branch_name> git push origin <branch_name> 9. 𝐌𝐢𝐬𝐜𝐞𝐥𝐥𝐚𝐧𝐞𝐨𝐮𝐬: - Check Git Status: Command: git status - View Commit History: Command: git log - Ignore Files (Add to `.gitignore`): Command: echo "<file_name>" >> .gitignore 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 -> https://lnkd.in/gj-tfEyH #git #softwareengineer #engineering #programming #github

𝐏𝐫𝐨𝐦𝐞𝐭𝐡𝐞𝐮𝐬 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 -> https://lnkd.in/gj-tfEyH 1. 𝐇𝐢𝐠𝐡-𝐋𝐞𝐯𝐞𝐥 𝐏𝐫𝐨𝐦𝐞𝐭𝐡𝐞𝐮𝐬 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞: Imagine Prometheus as a central hub that collects data from various sources and stores it for later analysis. It uses a pull-based model, meaning it actively scrapes this data at regular intervals. 2. 𝐏𝐫𝐨𝐦𝐞𝐭𝐡𝐞𝐮𝐬 𝐒𝐞𝐫𝐯𝐞𝐫: This is the brain of the operation. It scrapes data from targets (more on that in a bit!), stores it, and lets you analyze it using PromQL (a special query language). 3. 𝐓𝐢𝐦𝐞-𝐒𝐞𝐫𝐢𝐞𝐬 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 (𝐓𝐒𝐃𝐁): This is where Prometheus stores all the collected data over time, allowing you to see trends and historical information. 4. 𝐏𝐫𝐨𝐦𝐞𝐭𝐡𝐞𝐮𝐬 𝐓𝐚𝐫𝐠𝐞𝐭𝐬: These are the sources of data Prometheus scrapes. They can be servers, applications, or anything else that exposes metrics (measurable data points). 5. 𝐏𝐫𝐨𝐦𝐞𝐭𝐡𝐞𝐮𝐬 𝐄𝐱𝐩𝐨𝐫𝐭𝐞𝐫𝐬: Some targets don't natively provide metrics in a format Prometheus understands. Exporters act as translators, converting the target's data into Prometheus-friendly metrics. 6. 𝐏𝐫𝐨𝐦𝐞𝐭𝐡𝐞𝐮𝐬 𝐒𝐞𝐫𝐯𝐢𝐜𝐞 𝐃𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲: In large systems with many targets, keeping track of them all can be a hassle. Service discovery helps Prometheus automatically find new targets and scrape them. 7. 𝐏𝐫𝐨𝐦𝐞𝐭𝐡𝐞𝐮𝐬 𝐏𝐮𝐬𝐡𝐠𝐚𝐭𝐞𝐰𝐚𝐲: For short-lived jobs or situations where Prometheus can't directly scrape data, the Pushgateway acts as a middleman. Targets can push their data to the Pushgateway, which Prometheus can then pull. 8. 𝐏𝐫𝐨𝐦𝐞𝐭𝐡𝐞𝐮𝐬 𝐂𝐥𝐢𝐞𝐧𝐭 𝐋𝐢𝐛𝐫𝐚𝐫𝐢𝐞𝐬: These libraries make it easier to write applications that can be monitored by Prometheus. They provide a way to expose the application's metrics in the correct format. 9. 𝐏𝐫𝐨𝐦𝐞𝐭𝐡𝐞𝐮𝐬 𝐀𝐥𝐞𝐫𝐭 𝐌𝐚𝐧𝐚𝐠𝐞𝐫: Prometheus itself doesn't send alerts. The Alertmanager takes care of that. It receives alerts from Prometheus, groups them, and sends them out to your preferred notification channels (like email or chat). 10. 𝐏𝐫𝐨𝐦𝐐𝐋: This is the language you use to query and analyze the data stored by Prometheus. It allows you to ask specific questions about your system's performance and health. By understanding these components and how they work together, you can leverage Prometheus to effectively monitor your systems and ensure everything is running smoothly! 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 -> https://lnkd.in/gj-tfEyH #devops #engineering #softwareengineering #kubernetes #docker

𝐎𝐯𝐞𝐫𝐯𝐢𝐞𝐰 𝐨𝐟 𝐃𝐞𝐯𝐨𝐩𝐬 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 -> https://lnkd.in/gj-tfEyH DevOps - The Teamwork Foundation: - DevOps is a way of working together. - It joins developers and operations teams to work better and faster. - DevOps uses automation and keeps an eye on the software all the time. 𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐨𝐮𝐬 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 (𝐂𝐈) - Smooth Code Integration: - CI means putting code changes together often. - It tests the code automatically to catch mistakes early. - This helps make sure the software is always ready to be used. 𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐨𝐮𝐬 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 (𝐂𝐃) - Automated Code Delivery: - CD goes beyond CI by sending code changes to where people use the software automatically. - This makes releasing software faster and more reliable. - CD reduces manual work and mistakes in putting new code into action. 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 & 𝐃𝐨𝐜𝐤𝐞𝐫   - Tools for Easier Software Use: - Docker packs software and its parts into containers for consistent use. - Kubernetes helps put these containers to work automatically. - They make sure software runs the same everywhere and can handle lots of users. Practical Tips for Success: 1. Use Version Control (like Git): Track code changes and work better together. 2. Automate Everything: Make computers do repetitive tasks to save time and avoid errors. 3. Containerize with Docker and Use Kubernetes: Keep software in containers and let Kubernetes manage them for you. 4. Monitor and Measure Performance: Check how well your software works and fix problems early. 5. Prioritize Security: Make sure your software is safe by adding security from the start. 6. Document Your Work: Write down how you build and use your software so others can understand and fix things. 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 -> https://lnkd.in/gj-tfEyH #Engineering #DevOps #CI/CD #Kubernetes #Docker #SoftwareEngineer #SoftwareDeveloper #Tech #Automation #Collaboration #SoftwareEngineering #CodeIntegration

𝐃𝐞𝐯𝐎𝐩𝐬 𝐑𝐨𝐚𝐝𝐦𝐚𝐩 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 -> https://lnkd.in/gj-tfEyH Programming Language Choose a language that aligns with your project needs and team expertise. Master at least one scripting language (e.g., Python, Ruby) for automation. Version Control Learn Git for efficient and collaborative code management. Understand branching strategies and best practices. Automation Tools Explore configuration management tools (e.g., Ansible, Puppet) for infrastructure as code. Familiarize yourself with tools like Jenkins for continuous integration. Management Tool & Deployment Utilize tools like Docker for containerization. Learn about deployment strategies and orchestration tools (e.g., Kubernetes). CI/CD Tools Implement continuous integration with Jenkins or GitLab CI. Build automated deployment pipelines for continuous delivery. Test Automation Tools Master testing frameworks like JUnit or NUnit. Use tools like Selenium for end-to-end testing. Monitoring Tools Understand monitoring concepts and tools (e.g., Prometheus, Grafana). Set up alerts and create dashboards for effective monitoring. DBMS Gain expertise in one or more database systems (e.g., MySQL, PostgreSQL). Understand database scaling and optimization. Containerization Tools Dive into containerization tools like Docker. Learn about container networking and storage. Container Orchestration Explore container orchestration tools such as Kubernetes. Understand service discovery and load balancing. Cloud Computing Familiarize yourself with cloud platforms (e.g., AWS, Azure, GCP). Learn how to deploy and manage applications in the cloud. Follow TheAlpha.Dev for more such content. 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 -> https://lnkd.in/gj-tfEyH #DevOps #Programming #Automation #CI#CloudComputing #TechSkills #DevOpsRoadmap

𝗣𝘆𝘁𝗵𝗼𝗻 𝗠𝗮𝘀𝘁𝗲𝗿𝘆 𝗥𝗼𝗮𝗱𝗺𝗮𝗽: 𝗙𝗿𝗼𝗺 𝗕𝗮𝘀𝗶𝗰𝘀 𝘁𝗼 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 -> https://lnkd.in/gj-tfEyH Unlock the power of Python with this concise roadmap, catering to both beginners and seasoned developers.  𝗕𝗮𝘀𝗶𝗰𝘀: 𝟭. 𝗦𝘆𝗻𝘁𝗮𝘅 𝗮𝗻𝗱 𝗩𝗮𝗿𝗶𝗮𝗯𝗹𝗲𝘀:    - Master Python's basic syntax and variable handling. 𝟮. 𝗗𝗮𝘁𝗮 𝗧𝘆𝗽𝗲𝘀 𝗮𝗻𝗱 𝗖𝗼𝗻𝗱𝗶𝘁𝗶𝗼𝗻𝘀:    - Explore data types, type conversion, and conditional statements. 𝟯. 𝗟𝗼𝗼𝗽𝘀 𝗮𝗻𝗱 𝗘𝘅𝗰𝗲𝗽𝘁𝗶𝗼𝗻𝘀:    - Efficiently use 'for' and 'while' loops, and handle exceptions. 𝟰. 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀:    - Grasp the concept of functions for modular coding.  𝗗𝗮𝘁𝗮 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝘀: 𝟱. 𝗟𝗶𝘀𝘁𝘀, 𝗧𝘂𝗽𝗹𝗲𝘀, 𝗦𝗲𝘁𝘀, 𝗗𝗶𝗰𝘁𝗶𝗼𝗻𝗮𝗿𝗶𝗲𝘀:    - Understand Python's versatile data structures.  𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀: 𝟲. 𝗢𝗢𝗣, 𝗢𝗦 𝗖𝗼𝗺𝗽𝗮𝘁𝗶𝗯𝗶𝗹𝗶𝘁𝘆, 𝗮𝗻𝗱 𝗘𝗱𝗶𝘁𝗼𝗿𝘀:    - Delve into OOP, Python's compatibility with various OS, and popular code editors. 𝟳. 𝗦𝗰𝗿𝗶𝗽𝘁𝗶𝗻𝗴 𝗮𝗻𝗱 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻:    - Learn Python scripting for task automation.  𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗮𝗻𝗱 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀: 𝟴. 𝗗𝗮𝘁𝗮 𝗪𝗿𝗮𝗻𝗴𝗹𝗶𝗻𝗴, 𝗗𝗦𝗔, 𝗮𝗻𝗱 𝗩𝗲𝗿𝘀𝗶𝗼𝗻 𝗖𝗼𝗻𝘁𝗿𝗼𝗹:    - Prepare and analyze data, delve into DSA, and use Git for version control. 𝟵. 𝗪𝗲𝗯 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀 𝗮𝗻𝗱 𝗜𝗗𝗘𝘀:    - Familiarize yourself with web frameworks, and explore IDEs like PyCharm and Jupyter. 𝟭𝟬. 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 𝗮𝗻𝗱 𝗣𝗮𝗰𝗸𝗮𝗴𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗿𝘀:     - Discover testing frameworks (Beautiful Soup, Scrapy, URLLIB) and package managers (pip, conda). 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 -> https://lnkd.in/gj-tfEyH #python#engineering#softwareengineering#devops#computerscience

𝐋𝐢𝐧𝐮𝐱 𝐂𝐡𝐞𝐚𝐭𝐬𝐡𝐞𝐞𝐭 𝐅𝐨𝐫 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐬 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 -> https://lnkd.in/gj-tfEyH 𝐅𝐢𝐥𝐞 𝐒𝐲𝐬𝐭𝐞𝐦 𝐎𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬 ls - List directory contents cd - Change directory mkdir - Make directories rm - Remove files or directories 𝐅𝐢𝐥𝐞 𝐏𝐞𝐫𝐦𝐢𝐬𝐬𝐢𝐨𝐧𝐬 chmod - Change file mode bits chown - Change file owner and group chgrp - Change group ownership of files 𝐏𝐫𝐨𝐜𝐞𝐬𝐬 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 ps - Report a snapshot of current processes kill - Send a signal to a process top - Display Linux processes 𝐍𝐞𝐭𝐰𝐨𝐫𝐤𝐢𝐧𝐠 ifconfig - Configure network interfaces ping - Send ICMP ECHO_REQUEST to network hosts netstat - Display network connections, routing tables, interface statistics 𝐒𝐲𝐬𝐭𝐞𝐦 𝐈𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 uname - Display system information hostname - Display the system's hostname df - Display disk space usage 𝐏𝐚𝐜𝐤𝐚𝐠𝐞 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 apt - Package manager for Debian-based systems yum - Package manager for RPM-based systems dpkg - Package manager for Debian-based systems 𝐒𝐡𝐞𝐥𝐥 𝐒𝐜𝐫𝐢𝐩𝐭𝐢𝐧𝐠 bash - GNU Bourne-Again SHell echo - Display a line of text grep - Search file(s) for lines that match a given pattern 𝐔𝐬𝐞𝐫 𝐚𝐧𝐝 𝐆𝐫𝐨𝐮𝐩 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 useradd - Create a new user or update default new user information userdel - Delete a user account and related files passwd - Change user password 𝐅𝐢𝐥𝐞 𝐓𝐫𝐚𝐧𝐬𝐟𝐞𝐫 scp - Securely copy files between hosts rsync - Remote file synchronization wget - Retrieve files from the web 𝐒𝐲𝐬𝐭𝐞𝐦 𝐒𝐞𝐫𝐯𝐢𝐜𝐞𝐬 systemctl - Control the systemd system and service manager service - Run a System V init script chkconfig - Tool for enabling and disabling system services 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 -> https://lnkd.in/gj-tfEyH #linux #devops #engineering

 𝐆𝐢𝐭𝐇𝐮𝐛 𝐂𝐡𝐞𝐚𝐭𝐬𝐡𝐞𝐞𝐭 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 -> https://lnkd.in/gj-tfEyH  1. 𝐑𝐞𝐩𝐨𝐬𝐢𝐭𝐨𝐫𝐲 𝐁𝐚𝐬𝐢𝐜𝐬: - Clone a Repository:   Command:   git clone <repository_url>   - Initialize a Repository:   Command:   git init    2. 𝐖𝐨𝐫𝐤𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐁𝐫𝐚𝐧𝐜𝐡𝐞𝐬: - Create a New Branch:   Command:   git branch <branch_name>   - Switch to a Branch:   Command:   git checkout <branch_name>   - Create and Switch to a New Branch:   Command:   git checkout -b <new_branch_name>   - List Branches:   Command:   git branch   3. 𝐂𝐨𝐦𝐦𝐢𝐭𝐭𝐢𝐧𝐠 𝐂𝐡𝐚𝐧𝐠𝐞𝐬: - Stage Changes:   Command:   git add <file_name>   - Stage All Changes:   Command:   git add .   - Commit Changes:   Command:   git commit -m "Commit message"    4. 𝐏𝐮𝐥𝐥𝐢𝐧𝐠 𝐚𝐧𝐝 𝐏𝐮𝐬𝐡𝐢𝐧𝐠: - Pull Changes from Remote:   Command:   git pull origin <branch_name>   - Push Changes to Remote:   Command:   git push origin <branch_name>    5. 𝐌𝐞𝐫𝐠𝐢𝐧𝐠 𝐂𝐡𝐚𝐧𝐠𝐞𝐬: - Merge Branch into Current Branch:   Command:   git merge <branch_name>    6. 𝐖𝐨𝐫𝐤𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐑𝐞𝐦𝐨𝐭𝐞𝐬: - Add a Remote Repository:   Command:   git remote add <remote_name> <repository_url>   - List Remote Repositories:   Command:   git remote -v    7. 𝐇𝐚𝐧𝐝𝐥𝐢𝐧𝐠 𝐂𝐨𝐧𝐟𝐥𝐢𝐜𝐭𝐬: - Check for Conflicts:   Command:   git diff   - Resolve Conflicts and Continue Merge:   Command:   git add <file_name>   git merge --continue    8. 𝐆𝐢𝐭𝐇𝐮𝐛 𝐀𝐜𝐭𝐢𝐨𝐧𝐬: - Workflow Syntax Checking:   Command:   git pull origin <branch_name>   git push origin <branch_name>    9. 𝐌𝐢𝐬𝐜𝐞𝐥𝐥𝐚𝐧𝐞𝐨𝐮𝐬: - Check Git Status:   Command:   git status   - View Commit History:   Command:   git log   - Ignore Files (Add to `.gitignore`):   Command:   echo "<file_name>" >> .gitignore   𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 -> https://lnkd.in/gj-tfEyH #git #softwareengineer #engineering #programming #github

𝑫𝒆𝒗𝑶𝒑𝒔 𝑳𝒊𝒇𝒆𝒄𝒚𝒄𝒍𝒆 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 ->https://app.thealpha.dev/ 1. 𝑪𝒐𝒅𝒆: - Developers create the software code. - They use tools like Git to work together and keep track of changes. - Code is like the digital building blocks of the software. 2. 𝑩𝒖𝒊𝒍𝒅: - Turns the written code into a form the computer can understand. - Automated tools like Jenkins or Travis CI help speed up this process and reduce mistakes. - This step ensures the software is ready for the next phases. 3. 𝑻𝒆𝒔𝒕: - Software is tested for bugs and other issues. - Automated testing tools like JUnit or Selenium make sure the software works well. - This phase helps catch problems early on, ensuring quality. 4. 𝑹𝒆𝒍𝒆𝒂𝒔𝒆: - Puts the tested software into action. - Continuous integration and delivery (CI/CD) practices automate this for speed and reliability. - Users get to experience the new or updated software. 5. 𝑴𝒐𝒏𝒊𝒕𝒐𝒓: - Teams keep an eye on how the software is doing after release. - Monitoring tools like Prometheus help catch problems early and keep things running smoothly. - This phase ensures a good user experience. 6. 𝑶𝒑𝒆𝒓𝒂𝒕𝒆: - Manages the day-to-day running of the software in real-time. - Automation and optimization strategies help keep everything working well for users. - This phase ensures the software stays reliable and responsive. 7. 𝑷𝒍𝒂𝒏: - Planning is a key part of DevOps. - Teams use tools like Jira or Trello to plan and prioritize what needs to be done next. - Agile methodologies help teams adapt to changing requirements. 8. 𝑫𝒆𝒑𝒍𝒐𝒚: - Makes the software ready to handle more users. - Infrastructure as code (IaC) automates this process for a smooth and scalable deployment. - This phase sets the stage for future improvements and expansions. 9. 𝑺𝒄𝒂𝒍𝒆: - Involves making the software capable of handling more users and data. - Infrastructure is expanded, and resources are scaled to meet growing demands. - Scalability ensures the software can grow with the organization's needs. 10. 𝑭𝒆𝒆𝒅𝒃𝒂𝒄𝒌 𝑳𝒐𝒐𝒑: - DevOps is about continuous improvement. - Teams gather feedback from users and operations to make future development cycles better. - This loop helps in adapting to changes and delivering value consistently. 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 ->https://app.thealpha.dev/ #devops #engineering

𝐂𝐨𝐦𝐩𝐨𝐧𝐞𝐧𝐭𝐬 𝐨𝐟 𝐌𝐨𝐝𝐞𝐫𝐧 𝐓𝐞𝐫𝐫𝐚𝐟𝐨𝐫𝐦 𝐒𝐭𝐚𝐜𝐤 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 -> https://lnkd.in/gj-tfEyH 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 𝐚𝐬 𝐂𝐨𝐝𝐞 (𝐈𝐚𝐂) 𝐑𝐞𝐩𝐨𝐬𝐢𝐭𝐨𝐫𝐲 - Store all your Terraform code in a version-controlled repository. - Enables collaboration and tracking changes over time. 𝐓𝐞𝐫𝐫𝐚𝐟𝐨𝐫𝐦 𝐂𝐨𝐧𝐟𝐢𝐠𝐮𝐫𝐚𝐭𝐢𝐨𝐧 𝐅𝐢𝐥𝐞𝐬 - Written in HashiCorp Configuration Language (HCL). - Define the desired state of your infrastructure. 𝐒𝐭𝐚𝐭𝐞 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 - Tracks the current state of your infrastructure. - Stores information about resources managed by Terraform. 𝐏𝐫𝐨𝐯𝐢𝐝𝐞𝐫 𝐏𝐥𝐮𝐠𝐢𝐧𝐬 - Extend Terraform's capabilities to manage different cloud providers. - Allow seamless integration with AWS, Azure, Google Cloud, etc. 𝐌𝐨𝐝𝐮𝐥𝐞𝐬 - Encapsulate reusable infrastructure components. - Promote modularity and maintainability in Terraform code. 𝐑𝐞𝐦𝐨𝐭𝐞 𝐁𝐚𝐜𝐤𝐞𝐧𝐝 - Store Terraform state remotely for better collaboration. - Provides locking mechanisms to prevent concurrent modifications. 𝐂𝐈 / 𝐂𝐃 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞 - Automate the process of building, testing, and deploying infrastructure changes. - Ensures consistency and reliability in infrastructure deployments. 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 𝐓𝐞𝐬𝐭𝐢𝐧𝐠 𝐅𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤 - Validate infrastructure changes before applying them. - Helps prevent misconfigurations and downtime. 𝐒𝐞𝐜𝐫𝐞𝐭 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 - Securely manage sensitive information like API keys and passwords. - Integrates with tools like HashiCorp Vault or AWS Secrets Manager. 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 𝐚𝐧𝐝 𝐋𝐨𝐠𝐠𝐢𝐧𝐠 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 - Monitor the health and performance of your infrastructure. - Capture and analyze logs to troubleshoot issues efficiently. 𝐂𝐨𝐦𝐩𝐥𝐢𝐚𝐧𝐜𝐞 𝐚𝐧𝐝 𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 - Enforce compliance policies and regulatory requirements. - Automate governance tasks to maintain security and compliance standards. 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐃𝐨𝐜𝐮𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 𝐓𝐨𝐨𝐥𝐬 - Facilitate communication and knowledge sharing among team members. - Document infrastructure changes, decisions, and best practices. 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 -> https://lnkd.in/gj-tfEyH #Terraform #devops