🔥 Cloud Comparison sheet 2023

➡️ This guide compares key features and services across top providers like AWS, Azure, Google Cloud, and Oracle.


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➡️ The best way to become a DevOps Engineer is to work on practical projects.

➡️ Just watching tutorials or reading ebooks will not make you employable.

➡️ You do not have a job to gain practical exposure.

➡️ Just create a cloud account and spin up a Kubernetes Cluster.

➡️ Deploy a sample application and play with it.

➡️ Then Build CI/CD pipelines using Github Actions and ArgoCD or Flux CD.

✅ Always the best approach to learning a new technology or concept is by using the technology to build something useful.


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🔥 AWS Cloud ☁️ 🆓 Videos 📷


🟡 Part 1: https://drive.google.com/drive/folders/17Q3Tf3PEfmq_cGM97brqO3oCR0EPLFC8?usp=sharing

🟡 Part 2: https://drive.google.com/drive/folders/1bl8WhtUkWUXQh4XSm8_Nhf6Ykqu5rY-3?usp=sharing


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🔥 10 DevOps projects
❤️‍🔥 Step-by-Step Implementation (Beginners to Advance Level):

1⃣. Jenkins CI/CD pipeline with GitHub webhook integration for Deploying Docker application on EC2 instances using the declarative pipeline.
🔗 : https://lnkd.in/dbpafr7z

🔢. Jenkins Declarative Pipeline.
🔗 : https://lnkd.in/dkE6Wv89

🔢. Host a static website using the AWS S3 bucket.
🔗 : https://lnkd.in/dK82dbrF

🔢. Deploy web app using Jenkins master and worker node.
🔗 : https://lnkd.in/dU2a7CgW

🔢. Deploying web app using Docker Swarm. (Production Ready).
🔗 : https://lnkd.in/dyE_79Gg

🔢. Deploy the Reddit clone web app, on the Kubernetes cluster.
🔗 : https://lnkd.in/dUKe5hch

🔢. Installation and setup of Grafana on the local environment - Part -1.
🔗 : https://lnkd.in/dB7z7wSK

🔢. Grafana Setup and How to monitor resources - Part -2.
🔗 : https://lnkd.in/dJx9w7Ge

🔢. Mount AWS S3 Bucket on Amazon EC2 Linux Using S3FS.
🔗 : https://lnkd.in/dr2wbxRQ

1⃣0⃣. Deploy React Django web app, using AWS ECR and ECS.
🔗 : https://lnkd.in/deMKn_7Z

📣 Credit To :- Chetan R ☁️
Thanks for Sharing valuable information.
#freelearning #freeknowledge #devops #devopscommunity


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🐬 Docker is a software platform that allows you to build, test, and deploy applications quickly.

𝗕𝗲𝘀𝘁 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀 𝗳𝗼𝗿 𝗗𝗼𝗰𝗸𝗲𝗿
✔️ Always use a specific version for the base image for Dockerfile.
✔️Optimize your docker image by using a smaller base image.
✔️Specify the correct working directory in Dockerfile.
✔️Always use the .dockerignore fi…
✔️Copying package.json Separate from Source Code.
✔️Use non root user.
✔️Multistage build for production.
✔️Exposing port in Dockerfile.


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𝐃𝐞𝐯𝐎𝐩𝐬 𝐚𝐧𝐝 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐚𝐫𝐞 𝐭𝐰𝐨 𝐨𝐟 𝐭𝐡𝐞 𝐦𝐨𝐬𝐭 𝐢𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐫𝐨𝐥𝐞𝐬 𝐢𝐧 𝐭𝐡𝐞 𝐭𝐞𝐜𝐡 𝐢𝐧𝐝𝐮𝐬𝐭𝐫𝐲 𝐭𝐨𝐝𝐚𝐲.

But what's the difference between the two? 🤔

DevOps is a set of practices that combines software development (Dev) and IT operations (Ops) to shorten the systems development life cycle and provide continuous delivery with high software quality. ⚙️

Platform Engineering is a discipline that focuses on building, managing, and maintaining the platforms that developers use to build and deploy applications. ⬆️

In short, DevOps is all about the process of building and delivering software, while Platform Engineering is about the tools and infrastructure that make that process possible. ⚒


𝐖𝐡𝐢𝐜𝐡 𝐨𝐧𝐞 𝐢𝐬 𝐫𝐢𝐠𝐡𝐭 𝐟𝐨𝐫 𝐲𝐨𝐮? 🤔

If you're interested in the process of building and delivering software, then DevOps is a great career path. If you're more interested in the tools and infrastructure that make that process possible, then Platform Engineering is a good choice


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🔥 YOUTUBE CHANNELS TO LEARN DEVOPS 🔥

❓ Note: This tutorial should be followed, the way I numbered it.

⚡️ COMPLETE DEVOPS TUTORIAL:

➡️ 1. DevOps Pre-requisite
https://lnkd.in/dD9Z_5qA

➡️ 2. Networking
https://lnkd.in/dEmZ8zhY

https://lnkd.in/dwfmwmA9

➡️ 3. Linux
https://lnkd.in/d7gzxH5z

https://lnkd.in/dr4pjCV3

https://lnkd.in/dzTQE4b7

➡️ 4. Shell scripting
https://lnkd.in/dKrD_up7

https://lnkd.in/dJVqMt3Y

https://lnkd.in/d7VVbbNJ

➡️ 5. Git & GitHub
https://lnkd.in/dEp3KrTJ

https://lnkd.in/d6aM7Ek7

https://lnkd.in/duksFRgG

https://lnkd.in/ddpKXxqt

➡️ 6. Databases
https://lnkd.in/duMVr4bn

https://lnkd.in/dnUQ_uGe

➡️ 7. Artifact Repository Manager
https://lnkd.in/dgNHs7WD

➡️ 8. Docker
https://lnkd.in/dPddbJTf

https://lnkd.in/dnjHdxPR

➡️ 9. Jenkins
https://lnkd.in/dMHv9T8U

https://lnkd.in/dcynPYYH

➡️ 10. AWS
https://lnkd.in/dz7d5qEc

https://lnkd.in/dmi-TMv9

https://lnkd.in/dx-iqVNe

➡️ 11. SSH
🟢 Mobaxterm :
https://lnkd.in/ds7nUhbx

🟢 Putty :
https://lnkd.in/gGgW7Ns9

➡️ 12. Yaml
https://lnkd.in/dNqrXjmV

https://lnkd.in/dNqrXjmV

➡️ 13. Kubernetes
https://lnkd.in/duGZwHYX

https://lnkd.in/de84ESNv

➡️ 14. Helm
https://lnkd.in/ds_8WB7G

➡️ 15. Terraform
https://lnkd.in/dvpzNT5M

https://lnkd.in/dRs3YFu3

https://lnkd.in/d8nkTj3n

➡️ 16. Python
https://lnkd.in/d-EhshQz

https://lnkd.in/dYjay9ia

https://lnkd.in/dFtNz_9D

https://lnkd.in/dcYq8nE2

➡️ 17. Ansible
https://lnkd.in/dGKkrXrA

https://lnkd.in/dNugwtVW

https://lnkd.in/dhknHJXp

➡️ 18. Prometheus
https://lnkd.in/dpXhmVqs

https://lnkd.in/dStQbpRX

➡️ 19. Grafana
https://lnkd.in/ddAV7_-p

https://lnkd.in/dRwfE7A4

HAPPY LEARNING 📌

©: @prodevopsguy

Kubernetes, the leading container orchestration platform, provides a powerful mechanism for monitoring and managing the health of your pods and containers through the use of probes.

𝐖𝐡𝐚𝐭 𝐚𝐫𝐞 𝐏𝐫𝐨𝐛𝐞𝐬?

Probes are executable programs that Kubernetes utilizes to assess the health of pods and containers. They serve as essential tools for determining whether a pod or container is ready to receive traffic or needs to be restarted or terminated.

There are two main types of probes: liveness probes and readiness probes.

𝐋𝐢𝐯𝐞𝐧𝐞𝐬𝐬 𝐏𝐫𝐨𝐛𝐞𝐬:

➡️ Determine if a container is alive and functioning properly.

➡️ Failure triggers container restart, assuming a crash or critical error.

➡️ Ideal for ensuring continuous availability of long-running processes like database servers or application backends.

𝐑𝐞𝐚𝐝𝐢𝐧𝐞𝐬𝐬 𝐏𝐫𝐨𝐛𝐞𝐬:

➡️ Assess whether a container is ready to receive traffic.

➡️ Failure prevents the pod from receiving traffic, ensuring only healthy containers handle external requests.

➡️ Useful for containers needing initialization or configuration before handling incoming traffic, such as web servers or application frontends.

𝐓𝐲𝐩𝐞𝐬 𝐨𝐟 𝐏𝐫𝐨𝐛𝐞𝐬:

✅ Exec Probes: Execute a command or script within the container to determine its health.

✅ HTTP Probes: Send HTTP requests to the container's exposed ports to check responsiveness.

✅ TCP Probes: Attempt to establish a TCP connection to the container's exposed ports to verify availability.

Kubernetes versatility supports various probe types tailored to specific use cases and application requirements. It is crucial for maintaining a responsive containerized environment.


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🔥When becoming a DevOps Engineer, prioritize learning fundamental concepts before technologies.

❌ Just learning technologies and adding them to your resume won't cut it.

✔️ You need to understand the basic concepts.

➡️ For example, before learning docker, learn about Linux Kernel cgroups and namespaces.

✔️ Learn the basics, then learn the technology.


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1️⃣. Tutorial for Kubernetes

🌐 Introduction to Kubernetes
➡️https://lnkd.in/gz4-zvdC

🌐 Kubernetes tutorials: Hands-on labs with certification
➡️https://lnkd.in/g_2SVjvs

🌐 Networking with Kubernetes | Basics of Kubernetes Networking
➡️https://lnkd.in/gb7UpM6N

🌐 Kubernetes Full Course | Kubernetes Architecture
➡️https://lnkd.in/g8NATDPQ

🌐 what is Kubernetes (playlist)
➡️https://lnkd.in/gACGJzAq

🌐 Docker Containers and Kubernetes Fundamentals - Full Hands-On Course
➡️https://lnkd.in/gwtEN6hS

🌐 Kubernetes for Beginner
➡️https://lnkd.in/gdYZ4bgQ

🌐 Kubernetes Tutorial for Beginners
➡️https://lnkd.in/duGZwHYX

🌐 Kubernetes Tutorial For Beginners - Learn Kubernetes
➡️ https://lnkd.in/gmjRkGSJ

🌐 Kubernetes Full Course
➡️https://lnkd.in/gqr2nzYT

🌐 Kubernetes Course - Full Beginners Tutorial
➡️ https://lnkd.in/de84ESNv

🌐 Kubernetes Tutorial For Beginners
➡️https://lnkd.in/gSRYYGPG

2️⃣. Labs

1. Kubernetes Hands-on Lab #1 – Setting up 5-Node K8s Cluster

2. Kubernetes Hands-on Lab #2 – Running Our First Nginx Cluster

3. Kubernetes Hands-on Lab #3 –
🌐 Deploy Istio Mesh on K8s Cluster
➡️ https://lnkd.in/gpB4DNs6

🌐 Kubernetes 101 workshop - complete hands-on
➡️https://lnkd.in/gUCeEjFF

🌐 Build a Kubernetes Home Lab from Scratch step-by-step!
➡️https://lnkd.in/gM-kRUEh

🌐 Kubernetes Hands on
➡️https://lnkd.in/guhw9iKa

🌐 Hands-on with Kubernetes on Cloud
➡️ https://lnkd.in/gTcKi2Fq

🌐 Kubernetes Project for beginners
https://lnkd.in/gSc2KDAb

3️⃣. Book
🌐 https://lnkd.in/gM7ts9XC


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How to Learn Kubernetes 🚀

🔴 In this Kubernetes learning roadmap,

I have added prerequisites and complete Kubernetes learning path covering basic to advanced Kubernetes concepts.

Learning Kubernetes can seem overwhelming. It’s a complex container orchestration system, that has a steep learning curve.

But with the right roadmap and understanding of the foundational concepts, it’s something that any developer or ops person can learn.

🔗 𝗞𝟴𝘀 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗥𝗼𝗮𝗱𝗺𝗮𝗽: https://github.com/NotHarshhaa/kubernetes-learning-path


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🚀 Becoming a Certified Kubernetes Administrator, an EXPERT in K8s from scratch, and much MORE!

🔗 Link: https://github.com/NotHarshhaa/Certified_Kubernetes_Administrator

If you want to become a Certified Kubernetes Administrator, or you want to become an EXPERT in Kubernetes, learn Kubernetes from scratch and understand everything, this repo is a good choice.

Table of Contexts:

🔢. Kubernetes
🔢. Helm
🔢. Operator
🔢. Prometheus
🔢. EKS

☁️ Follow me on GitHub: https://www.github.com/NotHarshhaa


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🆘 Here is every AWS Certification you can earn

📝 Sorted By 4 Categories:

🟡 Foundational
➡️ AWS Certified Cloud Practitioner
https://lnkd.in/gQq_EERV

🟡 Associate
➡️ AWS Certified Solutions Architect
https://lnkd.in/g7RBTgKW
➡️ AWS Certified Developer
https://lnkd.in/g2F5UFHg
➡️ AWS Certified SysOps Administrator
https://lnkd.in/giM_2_Qj
➡️ AWS Certified Data Engineer
https://lnkd.in/g687nbeH

🟡 Professional
➡️ AWS Certified Solutions Architect Pro
https://lnkd.in/gUqrz8X3
➡️ AWS Certified DevOps Engineer Pro
https://lnkd.in/gbPWeUuR

🟡 Specialty
➡️ Advanced Networking
https://lnkd.in/ggdVTA2C
➡️ Data Analytics
https://lnkd.in/gnr_BvKH
➡️ Database
https://lnkd.in/gN64Xv49
➡️ Machine Learning
https://lnkd.in/g9fVgwCp
➡️ Security
https://lnkd.in/gwHscntY
➡️ SAP on AWS
https://lnkd.in/gMMpuhZM


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🔥 Here is a list of some Resume Ready DevOps projects.

1⃣ 𝗝𝗲𝗻𝗸𝗶𝗻𝘀 𝗖𝗜𝗖𝗗 𝘄𝗶𝘁𝗵 𝗚𝗶𝘁𝗛𝘂𝗯 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻
🔗 https://lnkd.in/gbDBEASe

🔢 𝗗𝗲𝗽𝗹𝗼𝘆 𝗝𝗮𝘃𝗮 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝘄𝗶𝘁𝗵 𝗖𝗼𝗺𝗽𝗹𝗲𝘁𝗲 𝗖𝗜/𝗖𝗗 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗝𝗲𝗻𝗸𝗶𝗻𝘀
🔗 https://lnkd.in/gSJaF4VN

🔢 𝗗𝗲𝘃𝗢𝗽𝘀 𝗖𝗜𝗖𝗗 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗦𝗲𝘁𝘂𝗽 𝗧𝗵𝗿𝗼𝘂𝗴𝗵 { 𝗝𝗲𝗻𝗸𝗶𝗻𝘀 | 𝗡𝗲𝘅𝘂𝘀 | 𝗦𝗼𝗻𝗮𝗿𝗾𝘂𝗯𝗲 | 𝗧𝗼𝗺𝗰𝗮𝘁 | 𝗠𝗮𝘃𝗲𝗻 }
🔗 https://lnkd.in/gvDYKMxV

🔢 𝗝𝗲𝗻𝗸𝗶𝗻𝘀 𝗖𝗜𝗖𝗗 𝘄𝗶𝘁𝗵 𝗚𝗶𝘁𝗛𝘂𝗯 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻
🔗 https://lnkd.in/g-eaM_EA

🔢 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝘆 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗳𝗼𝗿 𝗔𝗺𝗮𝘇𝗼𝗻 𝗘𝗖𝗦 𝗨𝘀𝗶𝗻𝗴 𝗝𝗲𝗻𝗸𝗶𝗻𝘀, 𝗚𝗶𝘁𝗛𝘂𝗯, 𝗮𝗻𝗱 𝗔𝗺𝗮𝘇𝗼𝗻 𝗘𝗖𝗥
🔗 https://lnkd.in/gN7WXAnX

🔢 𝗣𝗿𝗼𝘃𝗶𝘀𝗶𝗼𝗻𝗶𝗻𝗴 𝟮-𝘁𝗶𝗲𝗿𝘀 𝗮𝗻𝗱 𝟯-𝘁𝗶𝗲𝗿𝘀 𝗔𝗪𝗦 𝗩𝗣𝗖 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝘂𝘀𝗶𝗻𝗴 𝗧𝗲𝗿𝗿𝗮𝗳𝗼𝗿𝗺
🔗 https://lnkd.in/g2Y_Nk6N

🔢 𝗕𝗲𝘀𝘁 𝗝𝗲𝗻𝗸𝗶𝗻𝘀 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗧𝘂𝘁𝗼𝗿𝗶𝗮𝗹 𝗙𝗼𝗿 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿𝘀
🔗 https://lnkd.in/gF93WwrB

🔢 𝗘𝗻𝗱 𝘁𝗼 𝗘𝗻𝗱 𝗖𝗜/𝗖𝗗 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝘂𝘀𝗶𝗻𝗴 𝗚𝗶𝘁𝗛𝘂𝗯 𝗔𝗰𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗔𝗻𝗱𝗿𝗼𝗶𝗱 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻
🔗 https://lnkd.in/gB-Vvi7r

🔢 𝗖𝗿𝗲𝗮𝘁𝗲, 𝗽𝘂𝗯𝗹𝗶𝘀𝗵, 𝗮𝗻𝗱 𝘀𝘁𝗼𝗿𝗲 𝗡𝗴𝗶𝗻𝘅 𝗗𝗼𝗰𝗸𝗲𝗿 𝗶𝗺𝗮𝗴𝗲 𝗶𝗻 𝗔𝗪𝗦 𝗦𝟯 𝘂𝘀𝗶𝗻𝗴 𝗗𝗼𝗰𝗸𝗲𝗿 𝗮𝗻𝗱 𝗕𝗮𝘀𝗵
🔗 https://lnkd.in/g4iUncv9


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🔔 Here is a list of some Resume Ready DevOps projects (Part-II)

➡️ Real-Time CI CD Pipeline From Scratch with Jenkins:-
🔗 https://lnkd.in/day6k4GE

➡️ Creating AWS EKS Cluster using Terraform:-
🔗 https://lnkd.in/gjtjHuw4

➡️ Cost Optimization through AWS Lambda Function:-
🔗 https://lnkd.in/drDazJ9E

➡️ AWS Ninja — Convert EBS Volume from gp2 to gp3:-
🔗 https://lnkd.in/d6mUFdEK

➡️ Real-World CI/CD DevSecOps Pipeline for Deployment of Python Web-app:-
🔗 https://lnkd.in/d-TJisDn

➡️ AWS S3 Event Triggering Shell Script Used by Netflix, Airbnb, Adobe, Expedia, and Others :-
🔗 https://lnkd.in/dXhzdwP8

➡️ Deploy Multi Stage CICD Pipeline with Amazon EKS :-
🔗 https://lnkd.in/dEn7Vexj

➡️ Deploying Spring Boot application on K8S :-
🔗 https://lnkd.in/d8E_N_eg

➡️ Netflix Clone application via K8's:-
🔗 https://lnkd.in/d2zBUdMG
🔗 https://lnkd.in/dPVTDK9r

➡️ Deploy a Flask Application to a EKS Cluster using Jenkins and ArgoCD :-
🔗 https://lnkd.in/dn8WtnWj


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🔔 𝐇𝐞𝐫𝐞 𝐚𝐫𝐞 𝐬𝐨𝐦𝐞 𝐜𝐨𝐦𝐦𝐨𝐧 𝐞𝐫𝐫𝐨𝐫𝐬 𝐚𝐧𝐝 𝐢𝐬𝐬𝐮𝐞𝐬 𝐰𝐞 𝐨𝐟𝐭𝐞𝐧 𝐞𝐧𝐜𝐨𝐮𝐧𝐭𝐞𝐫 𝐰𝐡𝐞𝐧 𝐰𝐨𝐫𝐤𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐃𝐨𝐜𝐤𝐞𝐫:

➡️ 1.𝐈𝐦𝐚𝐠𝐞 𝐍𝐨𝐭 𝐅𝐨𝐮𝐧𝐝: You might encounter this error when trying to run a container with an image that doesn't exist locally or on the specified Docker registry. Ensure that you've pulled the image or that the image name and tag are correct.

➡️ 2.𝐏𝐞𝐫𝐦𝐢𝐬𝐬𝐢𝐨𝐧 𝐃𝐞𝐧𝐢𝐞𝐝: Docker containers often run as non-root users for security reasons. If your application requires access to certain resources or directories, make sure you've set the appropriate file permissions and user/group settings within the container.

➡️ 3.𝐏𝐨𝐫𝐭 𝐂𝐨𝐧𝐟𝐥𝐢𝐜𝐭𝐬: Trying to run multiple containers that use the same host port can lead to port conflicts. Ensure that the ports you specify in the docker run command do not conflict with existing ports in use on your host system.

➡️ 4.𝐎𝐮𝐭 𝐨𝐟 𝐃𝐢𝐬𝐤 𝐒𝐩𝐚𝐜𝐞: Docker uses disk space for images, containers, and logs. Over time, this can consume a significant amount of disk space. Periodically clean up unused images and containers using the docker system prune command.

➡️ 5.𝐂𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫 𝐂𝐫𝐚𝐬𝐡: Containers may crash for various reasons, such as misconfiguration or application issues. Use docker logs <container_name> to check the container logs for error messages that can help diagnose the problem.

➡️ 6.𝐃𝐨𝐜𝐤𝐞𝐫 𝐁𝐮𝐢𝐥𝐝 𝐅𝐚𝐢𝐥𝐮𝐫𝐞𝐬: Issues may arise during the build process of a Docker image. Common problems include incorrect Dockerfile syntax, missing files or dependencies, and network problems while downloading packages during the build.

➡️ 7.𝐍𝐞𝐭𝐰𝐨𝐫𝐤𝐢𝐧𝐠 𝐏𝐫𝐨𝐛𝐥𝐞𝐦𝐬: Docker containers can have connectivity problems if not properly configured. Ensure that the container is attached to the correct network, that firewalls are not blocking required ports, and that DNS settings are correct.

➡️ 8.𝐕𝐨𝐥𝐮𝐦𝐞 𝐌𝐨𝐮𝐧𝐭 𝐄𝐫𝐫𝐨𝐫𝐬: Failing to properly mount volumes can result in data loss or incorrect behavior. Double-check the paths and permissions when using the -v flag in docker run or docker-compose.

➡️ 9.𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞 𝐂𝐨𝐧𝐬𝐭𝐫𝐚𝐢𝐧𝐭𝐬: Docker containers can consume significant CPU and memory resources. Make sure you allocate appropriate resources using the --cpu and --memory flags when running containers.

➡️ 10.𝐈𝐦𝐚𝐠𝐞 𝐕𝐮𝐥𝐧𝐞𝐫𝐚𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬: Using outdated or insecure base images can introduce security vulnerabilities. Regularly update your Docker images and use tools like Clair or Trivy to scan for vulnerabilities.

➡️ 11.𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞 𝐋𝐞𝐚𝐤𝐬: Containers should clean up after themselves when they exit. Be cautious about resource leaks, such as leaving behind orphaned processes or unreleased file handles.


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➡️ Docker Architecture and Components

1. Docker Daemon (dockerd):
- 𝗥𝗼𝗹𝗲: Manages Docker containers on a system.
- 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀: Building, running, and managing containers.

2. Docker Client (docker):
- 𝗥𝗼𝗹𝗲: Interface through which users interact with Docker.
- 𝗖𝗼𝗺𝗺𝗮𝗻𝗱𝘀: build, pull, run, etc.

3. Docker Images:
- 𝗗𝗲𝗳𝗶𝗻𝗶𝘁𝗶𝗼𝗻: Read-only templates used to create containers.
- 𝗥𝗼𝗹𝗲: Serve as the basis for creating containers.
- 𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝘆/𝗛𝘂𝗯: A storage and distribution system for Docker images.

4. Docker Containers:
- 𝗗𝗲𝗳𝗶𝗻𝗶𝘁𝗶𝗼𝗻: Runnable instances of Docker images.
- 𝗥𝗼𝗹𝗲: Encapsulate the application and its environment.

5. Docker Registry:
- 𝗥𝗼𝗹𝗲: Store Docker images.
- 𝗣𝘂𝗯𝗹𝗶𝗰 𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝘆: Docker Hub.
- 𝗣𝗿𝗶𝘃𝗮𝘁𝗲 𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝘆: Can be hosted by users.


➡️ Docker Workflow

📌 A. Development Phase

1. 𝗪𝗿𝗶𝘁𝗲 𝗖𝗼𝗱𝗲:
- Developers write code locally.

2. 𝗕𝘂𝗶𝗹𝗱 𝗗𝗼𝗰𝗸𝗲𝗿 𝗜𝗺𝗮𝗴𝗲:
- 𝗗𝗼𝗰𝗸𝗲𝗿𝗳𝗶𝗹𝗲: A script with instructions to create a Docker image.
- 𝗖𝗼𝗺𝗺𝗮𝗻𝗱: docker build -t my-image .

3. 𝗧𝗲𝘀𝘁 𝗟𝗼𝗰𝗮𝗹𝗹𝘆:
- Run the application inside a Docker container locally.
- 𝗖𝗼𝗺𝗺𝗮𝗻𝗱: docker run my-image

📌 B. Share/Deploy Phase

4. 𝗣𝘂𝘀𝗵 𝗜𝗺𝗮𝗴𝗲 𝘁𝗼 𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝘆:
- Push the Docker image to a registry (Docker Hub, AWS ECR, etc.).
- 𝗖𝗼𝗺𝗺𝗮𝗻𝗱: docker push my-image

5. 𝗗𝗲𝗽𝗹𝗼𝘆 𝗼𝗻 𝗮 𝗦𝗲𝗿𝘃𝗲𝗿/𝗖𝗹𝘂𝘀𝘁𝗲𝗿:
- Pull the Docker image from the registry.
- 𝗖𝗼𝗺𝗺𝗮𝗻𝗱: docker pull my-image
- Run the container on a server or a cluster (like Kubernetes).
- 𝗖𝗼𝗺𝗺𝗮𝗻𝗱: docker run my-image

📌 C. CI/CD Integration

6. 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 (𝗖𝗜):
- Integrate code changes and build the Docker image.
- Push the built image to a registry.

7. 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 (𝗖𝗗):
- Deploy the Docker image from the registry to production environments.

📌 D. Scaling & Management

8. 𝗦𝗰𝗮𝗹𝗶𝗻𝗴:
- Increase or decrease the number of running containers based on demand.

9. 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 & 𝗟𝗼𝗴𝗴𝗶𝗻𝗴:
- Track the performance and logs of running containers.

10. 𝗨𝗽𝗱𝗮𝘁𝗲 & 𝗥𝗼𝗹𝗹𝗯𝗮𝗰𝗸:
- Deploy updates by pushing new Docker images to the registry and updating running containers.
- Rollback to a previous version if needed by running containers from an older Docker image.

📌 E. Networking & Storage

11. 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝗶𝗻𝗴:
- Manage communication between containers and the outside world.

12. 𝗦𝘁𝗼𝗿𝗮𝗴𝗲:
- Manage data and persist state using volumes.


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🚀 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲 𝗺𝘂𝗹𝘁𝗶𝘀𝘁𝗮𝗴𝗲 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝘀𝗲𝘁𝘂𝗽 𝗶𝗻 𝗔𝘇𝘂𝗿𝗲🌐💼

Here's a breakdown of our Dataflow process:

1️⃣ 𝗩𝗶𝘀𝘂𝗮𝗹 𝗦𝘁𝘂𝗱𝗶𝗼 𝗞𝗶𝗰𝗸-𝗼𝗳𝗳:
Developers initiate projects using predefined templates, like the .NET Angular workload. This setup includes an Azure Resource Group project deploying key elements via an ARM template – Azure App Service plan, App Service instance, and Application Insights.

2️⃣ 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗗𝗲𝗳𝗶𝗻𝗶𝘁𝗶𝗼𝗻 𝘄𝗶𝘁𝗵 𝗬𝗔𝗠𝗟:
A YAML file outlines our multistage pipeline, guiding solution building and publication.

3️⃣ 𝗚𝗶𝘁 𝗣𝘂𝘀𝗵 𝘁𝗼 𝗔𝘇𝘂𝗿𝗲 𝗥𝗲𝗽𝗼𝘀:
Utilizing 'git push' to transfer the solution into Azure Repos repository.

4️⃣ 𝗔𝘇𝘂𝗿𝗲 𝗗𝗲𝘃𝗢𝗽𝘀 𝗡𝗼𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻:
Triggered by the Git command, Azure DevOps Services dispatches notifications through webhooks.

5️⃣ 𝗟𝗼𝗴𝗶𝗰 𝗔𝗽𝗽 𝗔𝗰𝘁𝗶𝘃𝗮𝘁𝗶𝗼𝗻:
Webhook triggers a logic app to further process the notification.

6️⃣ 𝗟𝗼𝗴𝗶𝗰 𝗔𝗽𝗽 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀:
Logic app assesses the repository branch - whether it's the main branch or a feature branch. In case of a main branch commit, it looks for corresponding pipelines.

7️⃣ 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁:
If a pipeline exists in Azure Pipelines, the logic app uses Azure DevOps Services REST API to update it. Otherwise, it dynamically creates one.

8️⃣ 𝗠𝘂𝗹𝘁𝗶𝘀𝘁𝗮𝗴𝗲 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻:
This pipeline builds, publishes, and deploys an artifact to Azure resources. The artifact comprises a .NET Angular zip folder for App Service instance deployment and ARM templates with parameter files for Azure infrastructure provisioning.

9️⃣ 𝗦𝘁𝗮𝗴𝗶𝗻𝗴 𝗘𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁:
Artifact deployment to Azure staging environment.

🔟 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗘𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁:
Subsequent deployment to Azure production environment.

Result? ⏱
Reduced labor through automated pipeline provisioning and Azure infrastructure setup. 🛠


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🔥Most Useful DevOps/Cloud GitHub Repositories to Learning and Become a DevOps Engineer ♾


1️⃣. DevOps Realtime Projects (Beginner to Experienced): Link

2️⃣. Into The DevOps of Every tools: Link

3️⃣. DevOps Setup-Installations Guides: Link

4️⃣. Roadmap to learn Kubernetes so easy: Link

5️⃣. List of Best DevOps Tools with Detailed: Link

6️⃣. End to End CI/CD Pipeline Deployment on AWS EKS: Link

7️⃣. Becoming a Kubernetes Administrator Learning path: Link

8️⃣. Azure All-in-one Guide: Link

9️⃣. Terraform: Deploy an EKS Cluster-Like a Boss!: Link

1️⃣0️⃣. All In one Buddle of Kubernetes: Link

1️⃣1️⃣. Kubernetes Dashboard with integrated Health checks: Link

1️⃣2️⃣. AWS Billing Alert terraform module: Link


♥️Credits: @NotHarshhaa ✅

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