DevOps & Cloud (AWS, AZURE, GCP) Tech Free Learning
16.1K subscribers
1.33K photos
14 videos
501 files
1.28K links
https://projects.prodevopsguytech.com // https://blog.prodevopsguytech.com

• We post Daily Trending DevOps/Cloud content
• All DevOps related Code & Scripts uploaded
• DevOps/Cloud Job Related Posts
• Real-time Interview questions & preparation guides
Download Telegram
🥘Azure DevOps is a comprehensive platform that supports software development with cloud or on-premises services. It offers integrated tools for planning, tracking, coding, testing, building, and deploying applications. Here are the key components of Azure DevOps:

1. Azure Boards: This suite of Agile tools helps with planning and tracking work, code defects, and issues using Kanban and Scrum methods[1]. It facilitates collaboration among developers, project managers, and contributors.

2. Azure Repos: Provides Git repositories or Team Foundation Version Control (TFVC) for source control of your code. You can choose between Git and TFVC based on your team's needs[1].

3. Azure Pipelines: Offers build and release services to support continuous integration and delivery of your applications. It automates the process of building, testing, and deploying code to various environments[1].

4. Azure Test Plans: Provides tools for testing applications, including manual/exploratory testing and continuous testing[1]. It helps ensure the quality of your software.

5. Azure Artifacts: Allows teams to share packages (such as Maven, npm, NuGet, etc.) from public and private sources and integrate package sharing into your pipelines[1]. This component streamlines package management.

You can use Azure DevOps Services in the cloud or set up an on-premises environment with Azure DevOps Server. The choice depends on factors like ease of setup, collaboration, security, and scalability[1]. Additionally, Azure DevOps Services integrates with GitHub repositories, making it a versatile solution for DevOps teams[1].

In summary, Azure DevOps streamlines the entire software development lifecycle, enabling teams to deliver high-quality applications efficiently and continuously. Whether you're working in the cloud or on-premises, Azure DevOps provides the tools you need to succeed[1]. 🚀

➡️Reference links: [1] [2] [3] [4]


📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs
Please open Telegram to view this post
VIEW IN TELEGRAM
DevOps & Cloud (AWS, AZURE, GCP) Tech Free Learning
Photo
🚨 Let's compare Azure DevOps with other popular CI/CD tools:

1⃣. Jenkins:
➡️Type: Open-source automation server.
➡️Customizability: Highly customizable due to a vast plugin ecosystem.
➡️Ease of Use: Requires manual setup and configuration.
➡️Scalability: Scales well for small to large projects.
➡️Integration: Integrates with various tools and platforms.
➡️Community: Large community support.
➡️Hosted Option: Self-hosted or cloud-based (e.g., Jenkins X).
➡️Learning Curve: Moderate to steep.
➡️Cost: Free (open-source).

2⃣. GitLab CI/CD:
➡️Type: Integrated within GitLab platform.
➡️Ease of Use: User-friendly, especially for GitLab users.
➡️Pipeline Configuration: Defined in \.gitlab-ci\.yml.
➡️Scalability: Suitable for small to medium-sized projects.
➡️Integration: Tight integration with GitLab repositories.
➡️Hosted Option: GitLab offers a hosted solution.
➡️Learning Curve: Relatively straightforward.
➡️Cost: Free (self-hosted) or paid (GitLab SaaS).

3⃣. CircleCI:
➡️Type: Cloud-based CI/CD service.
➡️Ease of Use: Simple setup and configuration.
➡️Configuration: Defined in \.circleci/config\.yml.
➡️Scalability: Good for small to medium-sized projects.
➡️Integration: Integrates with GitHub and Bitbucket.
➡️Hosted Option: CircleCI provides a hosted service.
➡️Learning Curve: Low.
➡️Cost: Free tier available; paid plans for additional features.

4⃣. Travis CI:
➡️Type: Cloud-based CI/CD service.
➡️Ease of Use: Easy setup and minimal configuration.
➡️Configuration: Defined in \.travis\.yml.
➡️Scalability: Suitable for small projects.
➡️Integration: Integrates with GitHub repositories.
➡️Hosted Option: Travis CI offers a hosted service.
➡️Learning Curve: Very low.
➡️Cost: Free for open-source projects; paid plans available.

5⃣. Azure DevOps:
➡️Type: Integrated platform by Microsoft.
➡️Components: Azure Boards, Repos, Pipelines, Test Plans, Artifacts.
➡️Ease of Use: User-friendly, especially for Azure users.
➡️Integration: Integrates with Azure services and GitHub repositories.
➡️Scalability: Scales well for various project sizes.
➡️Hosted Option: Azure DevOps Services (cloud) or Azure DevOps Server (on-premises).
➡️Learning Curve: Moderate.
➡️Cost: Free tier available; paid plans based on usage.

Remember that the best choice depends on your team's specific needs, existing tools, and preferences. Evaluate factors like ease of setup, integration, scalability, and community support when making your decision! 🚀


📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs
Please open Telegram to view this post
VIEW IN TELEGRAM
As a DevOps engineer, mastering the Linux 🐧 command line is crucial for efficient system administration and management. Here are some essential Linux commands you should know:

1️⃣. File and Directory Management:
ls: List directory contents.
cd: Change directory.
pwd: Print working directory.
mkdir: Create a new directory.
rm: Remove files or directories.
cp: Copy files or directories.
mv: Move or rename files or directories.

2️⃣. User and Permission Management:
useradd: Add a new user.
passwd: Set or change user passwords.
chown: Change file ownership.
chmod: Modify file permissions.
su: Switch user.
sudo: Execute commands with superuser privileges.

3️⃣. Process and Service Management:
ps: Display running processes.
top: Monitor system processes.
kill: Terminate processes.
systemctl: Manage system services (systemd-based systems).
service: Manage services (init-based systems).

4️⃣. Networking and System Monitoring:
ifconfig or ip: Configure network interfaces.
netstat: Display network statistics.
ping: Test network connectivity.
df: Show disk space usage.
free: Display memory usage.
uptime: Show system uptime.


Remember that this is just a starting point, and there are many more Linux commands and utilities. Feel free to explore and deepen your knowledge as you work with Linux in your DevOps journey! 🐧 🚀


➡️Reference links: [1] [2] [3] [4]


📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs
Please open Telegram to view this post
VIEW IN TELEGRAM
😀😀 10 DevOps Real time Scenarios. 😀😀
🚀 Issues as well as their resolutions: 🚀

🔢. Continuous Integration Pipeline Failure and its Resolution.
🔗 https://lnkd.in/g9nBb79u

🔢. Application experiences performance degradation and becomes slow during high-traffic periods and its resolution.
🔗 https://lnkd.in/g9nBb79u

🔢. Deployments are error-prone and inconsistent across different environments and its resolution.
🔗 https://lnkd.in/gE6FYcBz

🔢. The application goes down in production due to an unforeseen issue and its resolution.
🔗 https://lnkd.in/gE6FYcBz

🔢. A security vulnerability is discovered in a component of the application stack and its resolution.
🔗 https://lnkd.in/gPtZ9_Ge

🔢. Production environments start to deviate from their desired configurations over time and its resolution.
🔗 https://lnkd.in/gPtZ9_Ge

🔢. A critical service experiences an outage, impacting users and business operations and its resolution.
🔗 https://lnkd.in/gvTtGYC7

🔢. Communication breakdowns between development and operations teams lead to misunderstandings and delays and its resolution.
🔗 https://lnkd.in/gvTtGYC7

🔢. A major release causes unexpected issues in the production environment.
🔗 https://lnkd.in/gYbFKPrv

🔢🔢. Cloud resource costs are increasing beyond budgeted limits.
🔗 https://lnkd.in/gYbFKPrv


🎄 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!
Please open Telegram to view this post
VIEW IN TELEGRAM
In Kubernetes, deployment strategies are essential for managing application updates while minimizing downtime. Let's explore some common strategies:

1⃣. Rolling Update:
Description: The default strategy in Kubernetes.
How It Works: Gradually replaces old Pods with new ones, ensuring a smooth transition.
Use Case: Ideal for stateless applications where downtime isn't critical[1].

🔢. Recreate Deployment:
Description: Shuts down the old version before deploying the new one.
How It Works: Stops all existing Pods and then creates new ones.
Use Case: Suitable for applications with minimal user impact during updates[2].

🔢. Blue/Green Deployment:
Description: Co-exists two versions (Blue and Green) of an application in separate environments.
How It Works: Routes traffic to either Blue or Green based on configuration.
Use Case: Useful for testing new features or rolling back quickly[3].

🔢. Canary Deployment:
Description: Gradually introduces new features to a subset of users.
How It Works: Deploys a small percentage of Pods with the new version.
Use Case: Minimizes risk by validating changes before full rollout[2].

🔢. Shadow Deployment:
Description: Runs a new version alongside the old one without affecting user traffic.
How It Works: Collects data and metrics from the shadow deployment.
Use Case: Useful for performance testing and monitoring[2].

Choose the strategy that best aligns with your application's requirements and risk tolerance. Happy deploying! 🚀🎉
More details

➡️Reference links: [1] [2] [3] [4] [5]


📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs
Please open Telegram to view this post
VIEW IN TELEGRAM
🖥 https://prodevopsguy.tech/posts/zomato-clone-secure-deployment-with-devsecops-cicd


📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs
Please open Telegram to view this post
VIEW IN TELEGRAM
🚨 Go from Zero to Hero with our Linux 🐧 System Administrator


Lesson 1 ➡️ https://lnkd.in/darzXURj

Lesson 2 ➡️ https://lnkd.in/dJStSRtn

Lesson 3 ➡️ https://lnkd.in/dRv9WYbr

Lesson 4 ➡️ https://lnkd.in/dAQ7DCmX


✔️ 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs
Please open Telegram to view this post
VIEW IN TELEGRAM
Tech News ‼️

➡️ Microsoft to lay off hundreds at Azure cloud unit.

➡️ Google lays off 100 Employees in its Cloud unit.

➡️ Instagram testing feature that stops users from skipping ads.

➡️ Truecaller AI Call Scanner can help you to prevent Voice call scams.

➡️ London hospitals cyber attack causing significant impact on services.

➡️ Intel launches new Xeon server processors amid competition with AMD.

Want more Tech News Like this? Join our WhatsApp group
https://chat.whatsapp.com/FndTPrJEkbq5RlKQE3jGp3
Please open Telegram to view this post
VIEW IN TELEGRAM
🌟 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁𝘀 𝘃𝘀. 𝗦𝘁𝗮𝘁𝗲𝗳𝘂𝗹𝗦𝗲𝘁𝘀 🌟

Making the right choice between Deployments and StatefulSets in Kubernetes can be a game-changer for your applications. It's not just a technical decision; it's about aligning your architecture with your application's needs!

🔍 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁𝘀 are the go-to for stateless applications. They shine when you need scalable, updatable, and replaceable containers. Think of front-end apps, RESTful APIs, or any service where the individual identity of a pod doesn't matter.

🔐 𝗦𝘁𝗮𝘁𝗲𝗳𝘂𝗹𝗦𝗲𝘁𝘀, on the other hand, are crucial for stateful applications. They maintain a sticky identity for each pod, perfect for databases or any application where data consistency and unique network identifiers are key.

The impact of this choice is huge:
🚀 Scalability: How your application scales under load.
💾 Data Management: How your application handles data persistence.
🔄 Updates: How updates and rollbacks are managed.

👨‍💻 As DevOps and cloud professionals, understanding these nuances ensures our applications are robust, resilient, and ready to scale.


✈️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs
Please open Telegram to view this post
VIEW IN TELEGRAM
Here are some common GitHub-related issues that DevOps engineers encounter, along with their solutions:

1️⃣. Merge Conflicts:
Issue: When multiple contributors modify the same file simultaneously, merge conflicts occur during pull requests.
Solution: Resolve conflicts by carefully reviewing conflicting changes and manually merging them.

2️⃣. Authentication Issues:
Issue: Improper authentication (SSH keys or personal access tokens) can lead to problems when pushing or pulling from repositories.
Solution: Ensure correct authentication methods to avoid issues.

3️⃣. Git Submodules:
Issue: Managing Git submodules can be challenging.
Solution: Understand how submodules work and handle them correctly.

4️⃣. Large Files and LFS:
Issue: GitHub has a file size limit. Large binary files can cause issues.
Solution: Use Git LFS (Large File Storage) for managing large files.

5️⃣. Branch Protection Rules:
Issue: Accidental force pushes or direct commits to protected branches.
Solution: Set up branch protection rules to prevent such actions.

6️⃣. Rate Limiting:
Issue: GitHub API requests are rate-limited.
Solution: Use tokens and avoid excessive requests.

7️⃣. Repository Permissions:
Issue: Incorrect permissions for collaborators.
Solution: Ensure proper permissions to avoid unauthorized access.

8️⃣. Webhooks and CI/CD Failures:
Issue: Debugging webhook and CI/CD failures.
Solution: Check logs and configurations to identify and fix issues.

Remember, addressing these challenges will enhance your DevOps skills! 😊🚀


📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs
Please open Telegram to view this post
VIEW IN TELEGRAM
https://prodevopsguy.tech/posts/common-ansible-errors-and-their-solutions-for-devops-engineer/


📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs
Please open Telegram to view this post
VIEW IN TELEGRAM
👉 🆘 A comprehensive collection of essential DevOps tools for development, deployment, monitoring, and more. 🆘

🔗 Link: https://github.com/NotHarshhaa/devops-tools 🔗

We Explained Each and Every Tools with Detailed Manner with their official site links 🔫

=> Table of Contents
1. Development Environment Tools
2. Source Code Management
3. Build Tools
4. Continuous Integration Tools
5. Artifact Management Tools
6. Code Analysis Tools
7. Continuous Delivery & GitOps Tools
8. Infrastructure Provisioning Tools
9. Cloud Cost Management Tools
10. Configuration Management Tools
11. Secret Management Tools
12. Config/Service Discovery Tools
13. Containerization Tools
14. Container Orchestration Tools
15. Container Security Tools
16. Policy Management Tools
17. Service Mesh Tools
18. Logging Tools
19. Monitoring & Observability Tools
20. Visualization Tools
21. Internal Developer Platform Tools
22. API Tools
23. Collaboration Tools
24. Backups and Restoration Tools
25. Cloud Providers



✉️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!
Please open Telegram to view this post
VIEW IN TELEGRAM
☄️ EXCLUSIVE WITH SOURCE CODE (SCRIPTS INCLUDED) ☄️

🔥 Zomato Clone: Secure Deployment with DevSecOps CI/CD

💎 Blog LINK : https://blog.prodevopsguy.xyz/zomato-clone-secure-deployment-with-devsecops-cicd

💎 Source Code LINK : https://github.com/NotHarshhaa/Zomato-Clone

🌐FORK THE REPO


🔵 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!
Please open Telegram to view this post
VIEW IN TELEGRAM
Resolving merge conflicts in Git ☁️ can be done using a text editor and Git commands. Here are the steps:

1. Identify the Conflict:
When you encounter a merge conflict, Git will mark the conflicting lines in your files.
Open the conflicted file in your favorite text editor (e.g., Visual Studio Code).

2. Review the Conflict:
➡️Look for conflict markers in the file:

<<<<<<< HEAD: This shows the changes from the base or HEAD branch.
=======: Separates your changes from the other branch's changes.
>>>>>>> BRANCH-NAME: Displays the changes from the other branch.

Decide which changes to keep or modify.

3. Resolve the Conflict:
Edit the file to incorporate the desired changes.
Remove the conflict markers (<<<<<<<, =======, and >>>>>>>).
Save the file.

4. Stage the Changes:
Use the following command to stage the resolved changes:
git add FILENAME


5. Commit the Changes:
Create a new commit with the resolved conflict:
git commit -m "Resolved merge conflict"


That's it! You've successfully resolved the merge conflict. For more details, you can refer to the GitHub Docs or other resources[1]. Let me know if you need further assistance! 🚀

➡️Reference links: [1] [2] [3] [4] [5]


📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs
Please open Telegram to view this post
VIEW IN TELEGRAM
If you're a DevOps engineer, you'll agree with this. Read below 👇

"automating manual tasks brings a unique pleasure"


Why?

Efficiency
- Automating tasks saves time and effort, allowing DevOps engineers to focus on more critical and challenging aspects of their work.

Consistency
- Automation ensures that tasks are performed consistently, reducing the chances of human error and enhancing reliability.

Innovation
- Automating manual processes often requires creative problem-solving and innovation, which can be intellectually stimulating and rewarding.

Scalability
- Automation enables DevOps teams to scale their operations efficiently, handling larger workloads without significant increases in manpower.

Empowerment
- Automating mundane tasks empowers DevOps engineers to take on more meaningful and impactful work, contributing to their professional growth and job satisfaction.


📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs
Please open Telegram to view this post
VIEW IN TELEGRAM
⚠️ Here are some Kubernetes projects that you might find interesting:

1. Minikube: This project implements a local Kubernetes cluster on macOS, Linux, and Windows, allowing you to practice and learn Kubernetes. It's great for beginners[1].

2. Quarkus: Although not exclusively a Kubernetes project, Quarkus is a Java framework that works well with Kubernetes. It's worth exploring if you're interested in Java development[2].

3. OpenTelemetry: Focusing on observability, OpenTelemetry provides tools for monitoring and tracing applications in a Kubernetes environment[2].

4. Argo CD and Keptn: These projects help with continuous delivery and GitOps workflows in Kubernetes[2].

5. Envoy and Contour: Envoy is a high-performance proxy, and Contour is an Ingress controller. Both are essential for managing traffic in Kubernetes clusters[2].

6. OKD 4, Fedora CoreOS, and CodeReady Containers: These projects enhance Kubernetes and provide additional features for developers and operators[2].

Remember to explore these projects based on your interests and skill level. Happy learning! 🚀👩‍💻


➡️Reference links: [1] [2] [3] [4] [5]


📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs
Please open Telegram to view this post
VIEW IN TELEGRAM
➡️ What is DevOps and what DevOps engineer do?


➡️ DevOps is a set of practices, cultural philosophies, and tools that aim to improve collaboration, communication, and integration between software development (Dev) and IT operations (Ops) teams.

The goal of DevOps is to enable Organization to deliver high-quality software products and services more rapidly, reliably, and efficiently.

➡️ DevOps engineers play a critical role in enabling organizations to embrace DevOps culture and practices, driving agility, innovation, and efficiency in software development and delivery.

🌟 DevOps engineer gaining expertise in tools and technologies related to DevOps practices, such as version control systems, continuous integration/continuous deployment (CI/CD) pipelines, containerization, and cloud computing platforms, is essential for a successful career in DevOps engineering.


✈️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs
Please open Telegram to view this post
VIEW IN TELEGRAM