🔍 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗖𝗜/𝗖𝗗?


🔘 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 (𝗖𝗜): The practice of frequently integrating code changes into a shared repository. This helps catch errors early, reducing integration issues later.

🔘 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 (𝗖𝗗): Automates the deployment process, enabling your application to move smoothly from development to production with minimal manual intervention.


💥 𝗕𝗲𝗻𝗲𝗳𝗶𝘁𝘀 𝗼𝗳 𝗮 𝗖𝗜/𝗖𝗗 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲

✅ 𝗙𝗮𝘀𝘁𝗲𝗿 𝗥𝗲𝗹𝗲𝗮𝘀𝗲𝘀: Automating the deployment process ensures quick and reliable releases with minimal manual work.

✅ 𝗜𝗺𝗽𝗿𝗼𝘃𝗲𝗱 𝗖𝗼𝗱𝗲 𝗤𝘂𝗮𝗹𝗶𝘁𝘆: Frequent code integrations and automated tests ensure fewer defects and a smoother development cycle.

✅ 𝗥𝗲𝗱𝘂𝗰𝗲𝗱 𝗛𝘂𝗺𝗮𝗻 𝗘𝗿𝗿𝗼𝗿: By eliminating manual intervention, the pipeline minimizes the chances of errors during the build or deployment process.

✅ 𝗖𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝗰𝘆: Automated builds ensure that every environment is set up the same way, reducing inconsistencies between stages.


⚙️ 𝗞𝗲𝘆 𝗖𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁𝘀 𝗼𝗳 𝗮 𝗖𝗜/𝗖𝗗 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲

➡️𝗦𝗼𝘂𝗿𝗰𝗲 𝗖𝗼𝗻𝘁𝗿𝗼𝗹: Code is stored in version control systems like Git.

➡️𝗕𝘂𝗶𝗹𝗱: Code is compiled, dependencies are resolved and artifacts are generated.

➡️𝗧𝗲𝘀𝘁: Automated tests (unit tests, integration tests, etc.) are run to ensure code quality.

➡️𝗗𝗲𝗽𝗹𝗼𝘆: The application is deployed to staging and production environments.

➡️𝗠𝗼𝗻𝗶𝘁𝗼𝗿: Continuous monitoring helps track performance and detect issues early.


🔑 𝗕𝗲𝘀𝘁 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀 𝗳𝗼𝗿 𝗮 𝗦𝘂𝗰𝗰𝗲𝘀𝘀𝗳𝘂𝗹 𝗖𝗜/𝗖𝗗 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲

1️⃣ 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲 𝗘𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴: From builds to tests and deployments make sure the pipeline is as automated as possible.

2️⃣ 𝗙𝗮𝗶𝗹 𝗙𝗮𝘀𝘁: Ensure that failing tests immediately notify developers, so they can address issues early.

3️⃣ 𝗨𝘀𝗲 𝗩𝗲𝗿𝘀𝗶𝗼𝗻𝗶𝗻𝗴: Use semantic versioning to track application changes.

4️⃣ 𝗜𝘁𝗲𝗿𝗮𝘁𝗲 𝗢𝗳𝘁𝗲𝗻: Keep improving and fine-tuning your pipeline for better performance and efficiency.


📱 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

📛 𝗪𝗵𝘆 𝗶𝘀 𝗡𝗚𝗜𝗡𝗫 𝘀𝗼 𝗽𝗼𝗽𝘂𝗹𝗮𝗿? 📛

✨ 𝑺𝒖𝒓𝒑𝒓𝒊𝒔𝒊𝒏𝒈 𝑭𝒂𝒄𝒕𝒔 𝑨𝒃𝒐𝒖𝒕 𝑵𝑮𝑰𝑵𝑿:

1️⃣ 𝑵𝑮𝑰𝑵𝑿 𝒘𝒂𝒔𝒏’𝒕 𝒐𝒓𝒊𝒈𝒊𝒏𝒂𝒍𝒍𝒚 𝒄𝒓𝒆𝒂𝒕𝒆𝒅 𝒇𝒐𝒓 𝒃𝒊𝒈 𝒄𝒐𝒓𝒑𝒐𝒓𝒂𝒕𝒊𝒐𝒏𝒔—it started as a personal project to solve the C10k problem (handling 10,000 simultaneous connections).

2️⃣ 𝑰𝒕’𝒔 𝒏𝒐𝒕 𝒋𝒖𝒔𝒕 𝒇𝒐𝒓 𝒘𝒆𝒃 𝒉𝒐𝒔𝒕𝒊𝒏𝒈—NGINX is a favorite in microservices and containerized environments.

3️⃣ Many cloud-native services like 𝑲𝒖𝒃𝒆𝒓𝒏𝒆𝒕𝒆𝒔 𝒓𝒆𝒍𝒚 𝒐𝒏 𝑵𝑮𝑰𝑵𝑿 as an Ingress Controller for routing traffic.

Why NGINX powers over 30% of the world's websites and is a favorite among cloud enthusiasts?

💡 𝐊𝐞𝐲 𝐂𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬 𝐨𝐟 𝐍𝐆𝐈𝐍𝐗

🌐 𝐇𝐢𝐠𝐡-𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐖𝐞𝐛 𝐒𝐞𝐫𝐯𝐞𝐫:
NGINX excels at handling millions of requests per second while serving static and dynamic content effortlessly.

🔄 𝗥𝗲𝘃𝗲𝗿𝘀𝗲 𝗣𝗿𝗼𝘅𝘆 & 𝗟𝗼𝗮𝗱 𝗕𝗮𝗹𝗮𝗻𝗰𝗲𝗿:
It ensures traffic is distributed evenly across backend servers, improving performance and minimizing downtime.

🔐 𝗦𝗦𝗟 𝗧𝗲𝗿𝗺𝗶𝗻𝗮𝘁𝗶𝗼𝗻:
NGINX takes care of the complex encryption/decryption process, offloading this from your backend servers for faster response times.

⚡️ 𝗖𝗼𝗻𝘁𝗲𝗻𝘁 𝗖𝗮𝗰𝗵𝗶𝗻𝗴:
Its caching mechanism serves content from memory, reducing latency and improving page load speeds.

🛠𝗠𝗮𝘀𝘁𝗲𝗿-𝗪𝗼𝗿𝗸𝗲𝗿 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲:
NGINX uses a scalable process model, ensuring optimal utilization of system resources under high traffic.


📱 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

⚡ 𝗠𝗮𝘀𝘁𝗲𝗿𝗶𝗻𝗴 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗲𝘀! ⚡

Kubernetes offers a variety of deployment strategies to ensure smooth and efficient application updates. Here are some of the key strategies every DevOps engineer should know:

1️⃣ 𝑹𝒆𝒄𝒓𝒆𝒂𝒕𝒆 𝑫𝒆𝒑𝒍𝒐𝒚𝒎𝒆𝒏𝒕
Process: Terminates all old pods before creating new ones.
Use Case: Suitable for stateful applications where downtime is acceptable.

2️⃣ 𝑹𝒐𝒍𝒍𝒊𝒏𝒈 𝑼𝒑𝒅𝒂𝒕𝒆
Process: Gradually replaces old pods with new ones.
Use Case: Ideal for stateless applications to ensure zero downtime during updates.

3️⃣ 𝑩𝒍𝒖𝒆-𝑮𝒓𝒆𝒆𝒏 𝑫𝒆𝒑𝒍𝒐𝒚𝒎𝒆𝒏𝒕
Process: Runs two identical environments (blue and green) and switches traffic from blue to green.
Use Case: Ensures quick rollback if issues are detected, perfect for critical applications.

4️⃣ 𝑪𝒂𝒏𝒂𝒓𝒚 𝑫𝒆𝒑𝒍𝒐𝒚𝒎𝒆𝒏𝒕
Process: Releases new versions to a small subset of users before full rollout.
Use Case: Mitigates risk by testing updates on a limited scale.


🛫 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

🐧 The Linux file system isn't just a bunch of folders - it's the organizational bedrock of your entire system.

Mastering it can take your tech career to the next level. Here's why:
⏩ 𝗞𝗲𝘆 𝗗𝗶𝗿𝗲𝗰𝘁𝗼𝗿𝗶𝗲𝘀 & 𝗧𝗵𝗲𝗶𝗿 𝗥𝗼𝗹𝗲𝘀:
➡️ Root (/): The central hub, connecting everything.
➡️ Bin & Sbin: Essential tools for basic system operation and advanced tasks.
➡️ Etc: Configuration files that make your system tick.
➡️ Home: Your personal storage space for files and documents.
➡️ Var: Holds dynamic data like logs and emails, constantly changing.
➡️ Usr: A vast library of applications, libraries, and data used by the system.
➡️ Lib & Opt: Support files for other programs and optional software.
➡️ Tmp: Temporary storage for the system's ongoing work.
➡️ Boot & Dev: Responsible for booting the system and interacting with hardware.
➡️ Proc & Root: Special directories for system information and the root user.
➡️ Run & Srv: Temporary files for running processes and data for system services.
➡️ Sys & Mnt: Virtual system info and mount points for external storage.
➡️ Media: Where removable media like CDs and cameras connect.

⏩ 𝗪𝗵𝘆 𝗦𝗵𝗼𝘂𝗹𝗱 𝗬𝗼𝘂 𝗖𝗮𝗿𝗲?
Linux powers countless technologies, and familiarity with its file system gives you an edge in various tech fields:
✔️ Software Engineering: Navigating codebases and system files with ease.
✔️ DevOps: Automating tasks and managing infrastructure efficiently.
✔️ Data Engineering: Working with data stored on Linux systems.
✔️ AI: Understanding where data and resources are located.
✔️ System Administration: Maintaining and troubleshooting Linux systems like a pro.

⏩ 𝗞𝗻𝗼𝘄𝗶𝗻𝗴 𝘁𝗵𝗲 𝗳𝗶𝗹𝗲 𝘀𝘆𝘀𝘁𝗲𝗺:
🔶 Saves you time by finding files quickly.
🔶 Empowers you to troubleshoot issues effectively.
🔶 Makes you a valuable asset to any team.

⏩ 𝗚𝗼 𝗕𝗲𝘆𝗼𝗻𝗱 𝘁𝗵𝗲 𝗕𝗮𝘀𝗶𝗰𝘀:
This is just a starting point. Dive deeper, explore each directory, and unlock your tech potential. Share your questions in the comments, and let's learn together!


✉️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy & @devopsdocs 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀

Docker 🏖

🔖 Official
https://www.docker.com/

🔖 Introduction to Containers - AWS Skill Builder
https://lnkd.in/drHegvBN

🔖 Understanding containers
https://lnkd.in/dfb_x4YJ

🔖 Docker: Beginner to Pro
https://lnkd.in/dbBeqgrN

🔖 How does Docker ACTUALLY work? The Hard Way: A Comprehensive Technical Deep Diving
https://lnkd.in/dv8YvSWr

🔖 Data Persistence - Docker Documentation
https://lnkd.in/dfGaBZnT

🔖 Docker Hub Registry
https://hub.docker.com/

🔖 Docker Samples
https://lnkd.in/din2CZPH


✈️ 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

𝗢𝘂𝘁𝗱𝗮𝘁𝗲𝗱 𝗗𝗲𝘃𝗢𝗽𝘀 𝗧𝗼𝗼𝗹𝘀 🔠 𝗩𝘀. 𝗠𝗼𝗱𝗲𝗿𝗻 𝗔𝗹𝘁𝗲𝗿𝗻𝗮𝘁𝗶𝘃𝗲𝘀 🔠

🔠Ditch the old:
🔠 Jenkins
🔠 Maven
🔠 Puppet
🔠 Chef
🔠 Nagios
🔠 Docker Swarm

🔠Embrace the new:
🔠 GitLab & GitHub Actions for CI/CD
🔠 Ansible for configuration management
🔠 Terraform for IaC
🔠 Gradle for faster builds
🔠 Red Hat OpenShift > Kubernetes
🔠 Grafana for monitoring
🔠 Vector & Fluent Bit for log forwarding
🔠 ELK or Loki for log storage
🔠 Prometheus or InfluxDB for metrics


🛫 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

🔠Let's talk about Linux 🐧 File System🔠


◾️ The top-level directory, the starting point of the entire file system.

🔠/bin (Binaries)
◾️ Essential command binaries used by both the system and all users.
◾️ Contains executable programs like ls, cat, cp, mv, and more.

🔠/boot (Boot)
◾️ Files required for the system to boot up.
◾️ Includes the kernel (vmlinuz or similar), bootloader (grub) and initrd/initramfs.

🔠/dev (Devices)
◾️ Special files representing devices connected to the system.
◾️ Includes files for terminals, storage devices, network interfaces, etc.

🔠/etc (Etcetera)
◾️ Configuration files for the system and applications.
◾️ Includes files for network settings, user accounts, system services, etc.

🔠/home (Home)
◾️ Contains home directories for each user on the system.
◾️ Each user's home directory stores their personal files, settings and configurations.

🔠/lib (Library)
◾️ Essential shared libraries and kernel modules.
◾️ Libraries are used by multiple programs and provide common functions.

🔠/media (Media)
◾️ Mount point for removable media like USB drives, CDs and DVDs.
◾️ Automatically mounted when the device is plugged in.

🔠/mnt (Mount)
◾️ Temporary mount point for manually mounted filesystems.
◾️ Used to access filesystems from other devices or network shares.

🔠/opt (Optional)
◾️ Reserved for add-on application software packages.

🔠/proc (Process)
◾️ A virtual filesystem providing information about running processes.
◾️ Each process is represented by a numbered directory containing details like memory usage, environment variables, etc.

🔠/root (Root User)
◾️ Home directory of the root user (the system administrator).
◾️ Not to be confused with the root directory (/).

🔠/run (Run-time variable data)
◾️ Stores volatile runtime data, including process IDs, sockets and other temporary files.
◾️ This directory is cleared on boot.

🔠/sbin (System Binaries)
◾️ Essential system binaries used for system administration.
◾️ Contains commands for booting, repairing, restoring the system, etc.

🔠/srv (Service)
◾️ Data for services provided by the system.

🔠/sys (System)
◾️ A virtual filesystem containing information about the system and hardware devices.

🔠/tmp (Temporary)
◾️ Holds temporary files created by programs and users.

🔠/usr (Unix System Resources)
◾️ Secondary hierarchy for read-only user data.

🔠/var (Variable)
◾️ Variable data files like log files, spool files and cache data.
◾️ Content changes frequently, so it's separated from /usr.


🛫 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

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🔹 SLO – Target reliability/performance goal
🔹 SLA – Customer-facing reliability commitment
🔹 SLI – Metrics measuring service performance
🔹 Error Budget – Acceptable failure within SLO
🔹 Toil – Repetitive, automatable manual work
🔹 Incident Management – Handling outages efficiently
🔹 Observability – Logging, metrics, tracing for insights
🔹 Chaos Engineering – Failure injection for resilience
🔹 Blameless Postmortem – Learn from failures, not blame
🔹 Capacity Planning – Scaling resources for future demand
🔹 Auto Remediation – Self-healing systems via automation
🔹 Blue-Green Deployment – Zero-downtime releases
🔹 Canary Releases – Gradual feature rollouts for safety
🔹 Progressive Delivery – Controlled deployments with feature flags
🔹 Service Mesh – Secure, reliable service-to-service communication
🔹 Runbooks & Playbooks – Standardized incident response guides
🔹 RTO & RPO – Recovery Time & Recovery Point Objectives
🔹 MTTR & MTBF – Time to recover & failure intervals
🔹 Circuit Breakers – Prevent cascading failures in services
🔹 Feature Flags – Toggle features without redeploying
🔹 Game Days – Simulating outages to test response readiness
🔹 Load Balancing – Distributing traffic for high availability
🔹 Rate Limiting – Controlling request flow to prevent overload
🔹 Shadow Traffic Testing – Running live traffic on test infra
🔹 Failover Strategies – Switchover mechanisms for redundancy
🔹 Distributed Tracing – End-to-end request tracking across microservices
🔹 Cell-Based Architecture – Fault isolation for high availability
🔹 Error Budgets Policy – Defining risk tolerance for deployments
🔹 Adaptive Paging – Smart alerting to reduce burnout
🔹 Operational Maturity – Measuring reliability processes
🔹 Dependency Management – Ensuring service reliability across dependencies
🔹 Platform Engineering – Building reliable internal dev platforms


🛫 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

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⚡️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

➡️ 𝐃𝐨𝐜𝐤𝐞𝐫𝐟𝐢𝐥𝐞 𝐈𝐧𝐬𝐭𝐫𝐮𝐜𝐭𝐢𝐨𝐧𝐬:
- FROM: Sets the base image.
- RUN: Executes commands in the container.
- MAINTAINER: Identifies the image creator.
- LABEL: Adds metadata.
- ADD: Copies files (supports URLs).
- COPY: Copies files (no URLs).
- VOLUME: Creates a shared mount point.
- EXPOSE: Specifies listening port.
- WORKDIR: Sets the working directory.
- USER: Defines the user for processes.
- STOPSIGNAL: Specifies stop signal.
- ENTRYPOINT: Sets the start command.
- CMD: Sets the default command.
- ENV: Sets environment variables.

➡️ 𝐃𝐨𝐜𝐤𝐞𝐫 𝐑𝐮𝐧 𝐂𝐨𝐦𝐦𝐚𝐧𝐝𝐬:
- --name: Names the container.
- -v, --volume: Mounts a volume.
- --network: Connects to a network.
- -d, --detach: Runs in background.
- -i, --interactive: Keeps STDIN open.
- -t, --tty: Allocates a pseudo-TTY.
- --rm: Auto-removes container on exit.
- -e, --env: Sets environment variables.
- --restart: Sets restart policy.

➡️ 𝐂𝐨𝐫𝐞 𝐃𝐨𝐜𝐤𝐞𝐫 𝐂𝐨𝐧𝐜𝐞𝐩𝐭𝐬:
- Docker Image: Read-only snapshot of a container.
- Docker Container: Executable package with software and dependencies.
- Docker Client: Tool to interact with Docker.
- Docker Daemon: Service managing Docker objects.
- Docker Registry: Storage for Docker images.


✈️ 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

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📱 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

Basic 📱 Git Flow in DevOps ♾ CI-CD!

1️⃣. Developer Creates Feature Branch: The developer creates a new feature branch and is used to work on a new feature or a specific task.

2️⃣. Developer Writes Code: The developer writes the necessary code for the feature in their local development environment.

3️⃣. Developer Commits Changes: Once the developer is satisfied with the changes, they commit the changes to the feature branch in the local Git repository.

4️⃣. Developer Creates Pull Request: The developer pushes the committed changes by creating a pull request to merge the feature branch into the main branch.

5️⃣. Code Review by Team: The pull request initiates a code review process where team members review the changes.

6️⃣. Approval of Pull Request: After addressing any feedback and making necessary adjustments, the pull request is approved by the reviewers.

7️⃣. Merge to Main Branch: The approved pull request is merged into the main branch of the Git repository.

8️⃣. Triggers CI/CD Pipeline: This automation ensures that the changes are continuously integrated and deployed.

9️⃣. Then we follow the procedure for building and testing the code, deploying to staging env. Once the tests in the staging environment pass, a manual approval is required to deploy the changes to the production environment. Once the code is deployed to production env, the prod env is monitored using Prometheus to track the performance and health of the application. The collected metrics are visualized using Grafana. Finally alerts are configured.


❤️ 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

🚀 Terraform Commands for DevOps Engineers 🌍

Mastering Terraform can greatly enhance your infrastructure management. Here’s a quick reference to essential Terraform commands:


1️⃣ terraform init - Initialize a Terraform working directory.

2️⃣ terraform validate - Check the configuration for syntax errors.

3️⃣ terraform plan - Generate and show an execution plan.

4️⃣ terraform apply - Apply the changes required to reach the desired state.

5️⃣ terraform destroy - Destroy the Terraform-managed infrastructure.

6️⃣ terraform show - Show the current state or a saved plan.

7️⃣ terraform output - Extract the value of an output variable from the state file.

8️⃣ terraform state - Advanced state management commands:
- terraform state list - List resources in the state.
- terraform state show - Show a resource in the state.
- terraform state rm - Remove a resource from the state.

9️⃣ terraform fmt - Reformat configuration files to the canonical format.

1️⃣0️⃣ terraform taint - Manually mark a resource for recreation.

1️⃣1️⃣ terraform untaint - Manually unmark a resource as tainted.

1️⃣2️⃣ terraform import - Import existing infrastructure into your Terraform state.

1️⃣3️⃣ terraform refresh - Update the state file with the real infrastructure.

📘 Helpful Links:
- Terraform Documentation: https://www.terraform.io/docs/index.html
- Terraform Best Practices: https://www.terraform-best-practices.com

Keep this cheat sheet handy and automate your infrastructure with confidence! 💡

✈️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

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📱 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

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🔖 HashiCorp Vault Tutorial for Beginners - What, Why and How
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🔖 Proxy vs Reverse Proxy vs Load Balancer | Simply Explained
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🔖 What is Infrastructure as Code? Difference of Infrastructure as Code Tools
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📱 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

How Docker 🐬 Works Explained

Docker is a platform that simplifies application development and deployment through containerization.

➡️Here's a brief overview of how it works:

1. Developer: Writes code and prepares a Dockerfile with instructions to build an image.
2. Client: Uses Docker commands (docker build, docker pull, docker run, docker push) to interact with Docker.
3. Dockerfile: Script containing instructions to create an image, specifying base images and configurations.
4. Registry: Stores Docker images, which can be pulled or pushed by developers.
5. Docker Host: Runs the Docker daemon, managing images and containers.
6. Docker Daemon: Background service that manages the lifecycle of containers.
7. Images: Templates for creating containers, containing applications and dependencies.
8. Containers: Isolated environments where applications run, sharing the host system's kernel.

➡️Workflow:
- Build: Developer creates an image from a Dockerfile.
- Push: Image is uploaded to a registry.
- Pull: Image is downloaded from the registry.
- Run: Container is created and started from the image.

Docker ensures applications are portable and consistent across different environments, simplifying deployment and scaling.

❤️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

A Dockerfile 🐬 is a text-based document that provides instructions for creating a container image. Let's walk through the basics of writing one:

1. Choose a Base Image:
Start by specifying the base image you want to use. It serves as the foundation for your custom image. For example:

FROM node:14

2. Set the Working Directory:
Use the WORKDIR instruction to define the working directory inside the container:

WORKDIR /usr/src/app

3. Copy Files:
Use COPY or ADD to copy files from your local machine into the image:

COPY package\.json package-lock\.json \./

4. Install Dependencies:
Run any necessary commands to install dependencies (e.g., using RUN npm install for Node.js):

RUN npm install

5. Expose Ports:
Specify which ports your application will listen on using EXPOSE:

EXPOSE 3000

6. Define Startup Command:
Finally, set the command that runs when the container starts:

CMD ["npm", "start"]

Remember, this is just a basic example. You can customize your Dockerfile based on your specific application and requirements.

For a hands-on tutorial, check out this Dockerfile tutorial from Docker's official documentation. [1]

➡️Reference links: [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14]


📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs