DevOps & Cloud (AWS, AZURE, GCP) Tech Free Learning

🐱 Git can be confusing at first. But trust me, once you grasp the basics, it's a game-changer. ▶️ Here's a quick rundown: ⚡️𝐘𝐨𝐮𝐫 𝐖𝐨𝐫𝐤𝐬𝐩𝐚𝐜𝐞: This is where you actually code. Simple. ⚡️𝐒𝐭𝐚𝐠𝐢𝐧𝐠 (𝐠𝐢𝐭 𝐚𝐝𝐝): Think of it as a prep area. You're telling Git, "Hey, these changes are important." ⚡️𝐋𝐨𝐜𝐚𝐥 𝐑𝐞𝐩𝐨 (𝐠𝐢𝐭 𝐜𝐨𝐦𝐦𝐢𝐭): This is your personal save point. Commit often, thank yourself later. ⚡️𝐑𝐞𝐦𝐨𝐭𝐞 𝐑𝐞𝐩𝐨 (𝐆𝐢𝐭𝐇𝐮𝐛, 𝐆𝐢𝐭𝐋𝐚𝐛 𝐞𝐭𝐜.): The cloud where your team's code lives. This is where the collaboration magic happens. ⚡️𝐊𝐞𝐲 𝐦𝐨𝐯𝐞𝐬: - 𝑷𝒖𝒔𝒉: Send your local commits to the remote repo. - 𝑷𝒖𝒍𝒍: Grab the latest changes from remote. It's actually fetch + merge in one go. - 𝑭𝒆𝒕𝒄𝒉: Download changes, but don't apply them yet. - 𝑴𝒆𝒓𝒈𝒆: Combine those fetched changes with your work. 🎄 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

🟡 𝗬𝗼𝘂 𝗠𝗨𝗦𝗧 𝗟𝗲𝗮𝗿𝗻 𝘁𝗵𝗲 🐧𝗟𝗶𝗻𝘂𝘅 𝗳𝗶𝗹𝗲 𝘀𝘆𝘀𝘁𝗲𝗺 Linux's file system is tree-like. The base is "/", with everything else branching off. ➡️ Core Directories: /bin 🛠: Essential binaries, e.g., bash, ls, grep. /boot 🚀: Boot items like kernel & bootloader. /dev 🔌: Device files for connected hardware. /etc 📜: System configuration files. /home 🏡: User home directories. /lib 📚: Shared libraries for programs. /media 💿: Mounts for removable media. /mnt 🧲: Temporary mounts. /opt 📦: Optional software. /proc 📊: System, process, memory info. /root 👑: Root user's home. /sbin 🔧: System admin tools, e.g., init. /srv 🌐: Data for services. /tmp 🌡: Temporary files. /usr 🖥: User software. /var 🔄: Variable data, logs, temp files. 🐧 Linux Commands: cd 🚶: Navigate. ls 📋: List contents. mkdir 📁: Create folder. rmdir 🗑: Delete folder. cp 📤: Copy. mv 🚚: Move. rm ❌: Delete. ⚠️ Note: Directories like /bin are crucial. Don't modify! 🔵 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs

⚡️ 𝐀𝐏𝐈 𝐆𝐚𝐭𝐞𝐰𝐚𝐲, 𝐋𝐨𝐚𝐝 𝐁𝐚𝐥𝐚𝐧𝐜𝐞𝐫, 𝐚𝐧𝐝 𝐑𝐞𝐯𝐞𝐫𝐬𝐞 𝐏𝐫𝐨𝐱𝐲: 𝐖𝐡𝐢𝐜𝐡 𝐎𝐧𝐞 𝐃𝐨 𝐘𝐨𝐮 𝐍𝐞𝐞𝐝? Traffic control in the digital world can feel like solving a complex puzzle. ✅API Gateway, Load Balancer, Reverse Proxy—they all seem to do the same thing at first glance. But the truth? Their purposes are unique, and understanding them can transform your architecture. Let's unravel the mystery! 📷 𝐑𝐞𝐯𝐞𝐫𝐬𝐞 𝐏𝐫𝐨𝐱𝐲: 𝐓𝐡𝐞 𝐆𝐚𝐭𝐞𝐤𝐞𝐞𝐩𝐞𝐫 A reverse proxy sits in front of your servers, handling client requests. Think of it as a middleman. 𝐊𝐞𝐲 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐬: ✅ Improves security by hiding internal server details. ✅ Enables caching for faster responses. ✅ Simplifies SSL termination and encryption. When to Use It: - You need to protect your backend infrastructure from direct exposure. - You’re managing HTTP/HTTPS traffic effectively. ⌛ 𝐋𝐨𝐚𝐝 𝐁𝐚𝐥𝐚𝐧𝐜𝐞𝐫: 𝐓𝐡𝐞 𝐓𝐫𝐚𝐟𝐟𝐢𝐜 𝐌𝐚𝐧𝐚𝐠𝐞𝐫 A load balancer ensures requests are spread across multiple servers to prevent overload. It's like directing traffic during rush hour. Key Features: ✅ Ensures high availability by distributing workloads. ✅ Provides failover to handle server outages. ✅ Supports scalability by managing increased traffic. When to Use It: - You have multiple servers and need to maintain consistent performance. - Uptime and reliability are your top priorities. 🔗 𝐀𝐏𝐈 𝐆𝐚𝐭𝐞𝐰𝐚𝐲: 𝐓𝐡𝐞 𝐀𝐏𝐈 𝐒𝐩𝐞𝐜𝐢𝐚𝐥𝐢𝐬𝐭 API Gateway acts as the single entry point for APIs, handling all the heavy lifting. It’s the concierge for your microservices. Key Features: ✅ Handles authentication, rate limiting, and logging. ✅ Simplifies API versioning and routing. ✅ Bridges communication between microservices. When to Use It: - You’re managing multiple APIs and need centralized control. - You want to offload cross-cutting concerns like security or monitoring. 🧩 𝐇𝐨𝐰 𝐭𝐨 𝐂𝐡𝐨𝐨𝐬𝐞? - Use Reverse Proxy if you need enhanced security and basic traffic forwarding. - Use Load Balancer to distribute traffic and ensure availability. - Use API Gateway for a powerful, API-first architecture, especially with microservices. 📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

Kubernetes Cluster Election 💡 Choosing the Right K8s Environment for Your Needs K8s offers various technologies tailored to different tasks, each with its own characteristics and advantages. Some popular options: 1️⃣ Minikube (https://lnkd.in/ePQKyEZ7) > Compatible with Linux, Windows, and macOS > Uses virtualization to deploy a cluster on a Linux virtual machine > Suitable for Linux without virtualization support 2️⃣ Kubeadm (https://lnkd.in/epyumfKZ) > The official CNCF tool for provisioning Kubernetes clusters > Offers flexibility for various cluster configurations (single node, multi-node, HA, self-hosted, etc.) > Ideal for launching minimal viable Kubernetes clusters 3️⃣ Kops (Kubernetes Operations) (https://lnkd.in/e7ApRVJP) > Provides tools for installing, operating, and removing Kubernetes clusters on cloud platforms like AWS, Google Cloud Platform, OpenStack, and DigitalOcean 4️⃣ Microk8s (https://microk8s.io) > Similar to Minikube, it creates single-node clusters > Features its own set of add-ons as configuration plugins > Exclusive to Linux environments 5️⃣ K3s (https://k3s.io) > Works on any Linux distribution without external dependencies > Replaces Docker with containerd as the container runtime and uses sqlite3 as the default database > Lightweight, consuming only 512MB of RAM and 200MB of disk space. 6️⃣ Kind (Kubernetes-in-Docker) (https://kind.sigs.k8s.io) > Runs Kubernetes clusters in Docker containers > Supports multi-node and High-Availability clusters > Compatible with Windows, Mac, and Linux as it runs on top of Docker 7️⃣ K3d (https://k3d.io) > A project aiming to dockerize K3s The choice of the Kubernetes environment depends on your project's specific needs.

Once you understand K8s basics, the next step is to create a cluster, which can be done both locally and in the cloud.

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