Log Analyzer Built with Bash Scripting for DevOps Tasks

Day 18 of #90DaysOfDevOps 💻🔥 Today I leveled up my Shell Scripting skills by learning how to write cleaner and reusable scripts. ✔ Created and used functions ✔ Worked with return values & local variables ✔ Learned strict mode (set -euo pipefail) for safer scripts ✔ Built intermediate scripts for real scenarios 💡 Biggest learning: Using strict mode helps catch errors early and makes scripts production-ready. ⚡ Real-world DevOps use: Functions + strict scripting are used in automation scripts, CI/CD pipelines, and system monitoring tools. Slowly moving from basic commands to real automation 🚀 #DevOps #Linux #ShellScripting #Automation #90DaysOfDevOps

Efficiency through Automation: My latest DevOps project! I tired of manual server checks, so I built a System Health Audit Tool using Bash. It provides instant pass/fail vitals on SSH, Firewall status, and Disk Usage ensuring server reliability in seconds. What I learned: 🛠 Bash Logic: Implementing if/else checks for service validation. 🔍 Debugging: Navigating EOF errors and refining script syntax. 📁 Git Workflow: Maintaining a professional, documented repository. Check out the slides below to see the logic in action! #DevOps #BashScripting #Automation #LinuxAdmin #SystemsAdministration #Git

Day 19 of #90DaysOfDevOps 💻🔥 Today I built my first real-world automation scripts using Shell Scripting. ✔ Created a log rotation script (cleanup + compression) ✔ Built a server backup script using .tar.gz ✔ Automated tasks using crontab scheduling 💡 Biggest learning: Automation isn’t just writing scripts — it’s about making systems run without manual effort. ⚡ Real-world DevOps use: These concepts are used in log management, server backups, and scheduled maintenance in production systems. From learning → to building → to automating 🚀 #DevOps #Linux #ShellScripting #Automation #Crontab #90DaysOfDevOps

🚀 Building a Mini CI Pipeline Using Bash (From Scratch) Over the past few days, I’ve been deepening my understanding of Linux by moving beyond isolated commands and focusing on practical automation. What started as a simple exercise—parsing log files with grep—evolved into building a structured, pipeline-like workflow using Bash. Here’s what I implemented: 🔹 Input validation to ensure robustness (handling missing/invalid directories) 🔹 Dynamic log scanning across multiple .log files 🔹 Error and warning aggregation using grep and wc 🔹 Identification of recurring issues using: cut → sort → uniq → sort -nr 🔹 Stage-based execution to simulate pipeline behavior: [STAGE 1] → [STAGE 4] 🔹 Status classification (OK / WARNING / CRITICAL) based on thresholds 🔹 Exit codes (0, 1, 2) to represent machine-level decisions 🔹 Dual output handling using tee (terminal + report file) 💡 A key insight from this exercise: There’s a fundamental distinction between: • Human-readable output → “STATUS: WARNING” • Machine-readable signals → exit 1 This is precisely how CI/CD systems determine whether to proceed, warn, or halt execution. ⚠️ One subtle but important lesson: Using tee -a without resetting the file led to duplicated reports — a small oversight, but a valuable reminder of how state management impacts automation reliability. What this project reinforced for me is that: DevOps is not about memorizing tools. It’s about designing workflows, enforcing logic, and enabling systems to make decisions autonomously. Next, I’ll be extending this into a basic alerting system, moving closer to real-world monitoring scenarios. If you’re on a similar path, I’d strongly recommend: Don’t just learn commands — engineer processes with them. #DevOps #Linux #Bash #Automation #CICD #Scripting #LearningInPublic

"It works on my machine" is still one of the most dangerous sentences in software. Because working locally is not the real finish line, production is. A feature may look fine in development and still fail after deployment because of environment differences, bad configuration, missing monitoring, weak rollout process, or simply because nobody checked how it behaves outside a laptop. That is why I like the mindset of "you build it, you run it." For me, writing the code is only part of the work. The job also includes thinking about the container, the pipeline, the deployment flow, the logs, the metrics, and what the team will do if something breaks at 2 a.m. Docker, CI/CD, Kubernetes, cloud infrastructure, Linux, Grafana, dashboards, alerts — none of that is "extra." That is part of delivering software in a serious way. Observability is also a big part of this. A service is not healthy just because it is up. You need to see what is happening, understand the signals, and react before small issues become production incidents. Good engineering is not only about making something run. It is about making it run reliably in the real world. #Java #SoftwareEngineer #DevOps #Grafana #CICD #Docker #Kubernetes #AWS #Observability #Linux #Git

Day 20 of learning and practicing DevOps 🔁 Worked on scripting project — building a log analyzer and report generator Worked on: • Reading and validating log file input • Counting errors (ERROR, Failed) using grep • Extracting critical events with line numbers • Finding top 5 recurring errors using awk, sort, uniq • Generating a structured report file • Archiving processed logs automatically Important part: Instead of manually reading logs, I built a script that analyzes everything and gives a summary in seconds. Learning today--> logs tell the story turning raw logs into useful insights. Here are my notes: https://lnkd.in/ga8xUT6U 📍 #DevOps #Linux #ShellScripting #Automation #LogAnalysis #LearningInPublic #90DaysOfDevOps #TrainWithShubham

🚀 Day 19 of #90DaysOfDevOps journey with Shubham Londhe Today, I worked on a practical DevOps-style project focused on automation and system maintenance using Bash scripting. Instead of manually managing logs and backups, I built a system that handles everything automatically. 🔧 What I built: 📁 Log Rotation Script - Compresses logs older than 7 days - Deletes archives older than 30 days 💾 Backup Script - Creates timestamped backups - Verifies backup success using size output - Maintains a 14-day retention policy ⏱ Crontab Automation - Log rotation runs daily - Backups run weekly - Health checks run every 5 minutes 🧩 Maintenance Wrapper Script - Combines all tasks into one workflow - Logs everything for easier debugging 📚 Key Learnings: - Importance of validation to avoid script failures - Using "find -mtime" for automated cleanup - Redirecting logs ("2>&1") for better troubleshooting - Understanding the power of cron jobs in real-world automation This project gave me a deeper understanding of how real systems handle logs, backups, and reliability without manual effort. Step by step, I’m becoming more confident in Linux, Bash, and DevOps fundamentals 💪 #90DaysOfDevOps #DevOpsKaJosh #Linux #BashScripting #Automation #Crontab #LearningJourney #TrainWithShubham

One thing I’m learning recently: 👉 DevOps is not just about tools… it’s about automation. While going through Shell Scripting for DevOps, I saw how simple scripts can automate powerful tasks like: 🔹 Server setup and package installation 🔹 Monitoring system performance 🔹 Managing backups and logs 🔹 Automating deployments with tools like Docker, Jenkins, and Kubernetes. What really stood out to me? A few lines of Bash can: ✔ Restart failed services automatically ✔ Monitor CPU, memory, and disk usage ✔ Trigger CI/CD pipelines ✔ Deploy applications without manual intervention For example: 👉 A simple script can check if a service like NGINX is down and restart it instantly 👉 Another script can back up databases daily without human input This made me realize: 👉 The real power in DevOps is automation at scale. 💡 MY TAKEAWAY If you want to get into DevOps: 👉 Learn Linux 👉 Learn Shell scripting 👉 Learn how systems actually work Because: 🚫 Manual work doesn’t scale ✅ Automation does #DevOps #ShellScripting #Linux #Automation #CloudComputing #TechSkills #Engineering #SoftwareEngineering #STEM #CareerGrowth

Day 11 of My DevOps Journey 🚀 Today I learned about Variables in Shell Scripting 🧠💻 🔹 What I learned: ✔️ Variables are used to store values (key-value format) ✔️ No data types in shell scripting ✔️ System variables → SHELL, USER, PATH ✔️ User-defined variables for custom use 🔹 Hands-on: ✔️ Created variables using export ✔️ Accessed values using echo ✔️ Removed variables using unset 🔹 Important Concepts: ✔️ Temporary vs Permanent variables ✔️ Used .bashrc to store variables permanently ✔️ Learned how to set variables for all users 🔹 Rules: ✔️ No numbers at the start ✔️ Avoid special characters (-, @, #) ✔️ Prefer uppercase variable names Learning step by step and building consistency 💪🔥 #DevOps #Linux #ShellScripting #AWS #LearningJourney

💻 Exploring Shell Scripting: Small Commands, Big Impact Another step forward in my DevOps journey 🚀 Shell scripting is more than just writing commands — it’s about: ✔️ Automating repetitive tasks ✔️ Improving efficiency ✔️ Building scalable workflows 🔑 Key areas I worked on: • Bash scripting & execution • Variables and arguments • Control structures (if, for, while) • Automating daily tasks 💡 Why it matters? Because automation is the backbone of DevOps — saving time, reducing errors, and ensuring consistency. “The best way to predict the future is to automate it.” #ShellScripting #DevOps #Automation #Linux #ContinuousLearn