✨ If you want to become good at AWS in 2025, then learn these use cases:


1️⃣ Hexagonal Architecture in AWS
🔣 https://lnkd.in/gwJ3UmYm


2️⃣ Implementing AWS Single Sign-On (SSO) Crash Course
🔣 https://lnkd.in/grYZhjhu


3️⃣ CloudFront Signed URL vs S3 Pre Signed URL - When to Use What?
🔣 https://lnkd.in/g2ypcPeA


4️⃣ How Provisioned Concurrency Cuts AWS Lambda Cold Starts by 98%
🔣 https://lnkd.in/gkjzhEsv


5️⃣ How to Use S3 Buckets Securely for Public Data Storage
🔣 https://lnkd.in/gUJ7c_-R


6️⃣ Solve AWS Lambda Cost Performance Imbalance with Power Tuning
🔣 https://lnkd.in/gmyKXf_6


7️⃣ How AWS Handled 2024 Prime Day’s Record Breaking Traffic
🔣 https://lnkd.in/g9RQ2fVc


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

▶️ Bloated vs. Optimized Docker 🐬 Image

Let’s talk Docker images – nobody likes them big and slow, right? I had an image that was 879MB (way too big!), and I got it down to 150MB. Here’s how I did it:

[🔢] Multi-Stage Builds – Think of this like packing only what you need. You build everything in one stage, then copy over just the essentials to the final image. This keeps things simple and small.

[🔢] Use Slim Base Images – I switched to node:14-slim, which has everything you need to run the app but without the extra stuff. It made a big difference.

[🔢] Clean Up as You Go – I removed any files or packages I didn’t need after installing. Less clutter = smaller image!

[🔢] Skip Dev Dependencies – For production, you only need what’s required to run the app, not to build it. So, I left out the development tools.

[🔢] Try Alpine Images – If you’re looking to save even more, Alpine images are tiny. They need a bit more setup, but they’re worth it if you want to go super light.

Making Docker images smaller isn’t hard, and it’s worth it.

Faster builds, quicker deployments, and less storage needed. Give it a try!

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

⚡️ Before spending hours on YouTube Videos/Courses, just know what you are signing up for.

➡️ 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲: Spend 25% of the time dealing with Infrastructure from provisioning to preventing configuration drift and being cloud agnostic.

➡️ 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆: Shift left the security. From removing unwanted binaries to enforcing runtime security.

➡️ 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: Write 100s of shell scripts or Ansible Playbooks or build a pipeline to automate the workflow.

➡️ 𝗢𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆: Make sure Logging + Profiling + Tracing + Monitoring are in sync.

➡️ 𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻: Write tons of docs for releases, post-mortems and internal operations.

➡️ 𝗧𝗿𝗼𝘂𝗯𝗹𝗲𝘀𝗵𝗼𝗼𝘁𝗶𝗻𝗴: Do the RCA and spend days cluelessly staring at the screen.


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

🔣 Levels of Kubernetes. 🔣

➡️ Level 1
➖ Knows basic concepts.
➖ Limited troubleshooting skill.

➡️Level 2
➖ Can manage deployments, scaling apps & namespaces well.
➖ Troubleshoots issues with pods and deployments.

➡️ Level 3
➖ Deep understanding of Kubernetes & automate deployments.
➖ Debug advanced issues. (Including cluster level ones.)

➡️ Level 4
➖ Designs & implements secure and scalable clusters.
➖ Optimizes cluster performance and resource utilization.
➖ Good understanding of Kubernetes security best practices.

➡️ Level 5
😎 Ability to say - "We don't need Kubernetes for this problem."


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

🚀 Unlock the Power of Kubernetes Scaling Strategies! 🚀

Looking to optimize your Kubernetes deployment for peak performance? Explore these cutting-edge scaling strategies:

1⃣. Horizontal Pod Autoscaling (HPA): Effortlessly adjust pod counts based on CPU usage and more.
2⃣. Vertical Pod Autoscaling (VPA): Fine-tune CPU and memory resources for optimal efficiency.
3⃣. Cluster Autoscaling: Dynamically scale your cluster to meet workload demands in real-time.
4⃣. Manual Scaling: Take control with manual replica adjustments using simple commands.
5⃣. Predictive Scaling: Harness AI to predict future demands and scale proactively with tools like PredictKube.
6⃣. Custom Metrics Based Scaling: Tailor scaling based on custom metrics beyond CPU and memory.


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

☁️ AWS Cloud All End-to-End Content 2024 ⚡️


➡️ This Includes:
- All AWS Content
- AWS Realtime scenarios
- All AWS Exercises with solutions
- No More AWS PDFs needed
- Easy to Learn from anywhere
- Detailed Explanation guide
- All AWS services for DevOps Engineer

🖥 Link : https://github.com/NotHarshhaa/into-the-devops/tree/master/topics/aws

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


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

The general process of using Docker. 🐬

Give it a read.

⚡️𝐃𝐨 𝐲𝐨𝐮 𝐤𝐧𝐨𝐰?

Docker emerged from dotCloud, a Platform-as-a-Service (PaaS) company.

It started as an internal project by Solomon Hykes in France, aimed at simplifying application deployment.

2013 => Docker was first unveiled at PyCon.

It quickly gained popularity due to its innovative approach to containerization.

Docker was released as open-source in March 2013.

⚡️𝐃𝐫𝐢𝐯𝐢𝐧𝐠 𝐅𝐨𝐫𝐜𝐞𝐬 -
◾️ Developer Pain Points => developers struggled with inconsistent application environments across different stages
◾️ Operational Efficiency
◾️ Cloud Adoption

Alright,

🔖 Let's understand the 𝐃𝐨𝐜𝐤𝐞𝐫 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰 -

[1.] Develop
◾️ Write your application code.

[2.] Dockerfile
◾️ Create a Dockerfile that defines the environment and dependencies for your application.

[3.] Build Image
◾️ Use docker build to create a Docker image from your Dockerfile.

[4.] Run Container
◾️ Use docker run to launch a container from your image.
◾️ The container is an isolated instance of your application.

[5.] Test
◾️ Test your application within the container.
◾️ If you make changes, rebuild the image and recreate the container.

[6.] Push => This is Optional
◾️ Use docker push to share your image on a registry (e.g. Docker Hub).

[7.] Pull => This is Optional
◾️ Others can use docker pull to download your image and run your application in their own environments.


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

👉 Writing Ansible playbooks involves more than just defining tasks. Here are best practices to follow when creating effective and maintainable Ansible playbooks:

1. Modularity and Reusability:
Break down your playbook into smaller roles and tasks. Each role should have a specific purpose (e.g., installing packages, configuring services). This makes it easier to reuse and maintain code.
Use Ansible roles to organize your tasks. Roles allow you to encapsulate functionality and share it across different playbooks.

2. Idempotence:
Ansible playbooks should be idempotent, meaning they can be run multiple times without causing unintended changes.
Use Ansible modules that support idempotence (most built-in modules do).
Avoid using shell commands directly unless necessary.

3. Use YAML Syntax Correctly:
YAML indentation matters! Be consistent with spaces (preferably 2 spaces) and avoid tabs.
Use proper YAML syntax for lists, dictionaries, and variables.

4. Separate Variables from Playbooks:
Store variables in separate files (e.g., vars\.yml, defaults/main\.yml within roles).
Avoid hardcoding values directly in playbooks.

5. Use Descriptive Variable Names:
Choose meaningful variable names that convey their purpose.
Avoid generic names like var1, var2, etc.

6. Document Your Playbooks:
Add comments to explain the purpose of each task.
Use # for single-line comments and | for multiline comments.

7. Error Handling and Failure Conditions:
Include error handling tasks (using failed_when or ignore_errors) to gracefully handle failures.
Use block and rescue to group tasks and handle exceptions.

8. Secrets and Sensitive Data:
Use Ansible Vault to encrypt sensitive data (passwords, API keys, etc.) within playbooks.
Never hardcode secrets directly in playbooks.

9. Testing and Validation:
Test your playbooks in a safe environment (e.g., staging) before deploying to production.
Use --check mode to validate changes without applying them.

10. Inventory Management:
- Maintain a well-organized inventory file (hosts) with clear host groups.
- Use dynamic inventories if your infrastructure is dynamic (e.g., AWS, Azure).

11. Use Roles for Common Tasks:
- Create reusable roles for common tasks (e.g., setting up Nginx, configuring databases).
- Roles allow you to share functionality across different playbooks.

12. Version Control and Git:
- Store your playbooks in version control (e.g., Git).
- Commit frequently and write meaningful commit messages.

13. Testing Frameworks:
- Explore testing frameworks like Molecule or Ansible Test Kitchen for automated testing of your playbooks.

14. Performance Optimization:
- Optimize playbooks for performance by minimizing unnecessary tasks.
- Use async and poll for long-running tasks.

15. Keep Playbooks Simple:
- Avoid complex logic within playbooks. If needed, move it to custom Ansible modules or scripts.

Remember that practice and experience are key to mastering Ansible playbooks. Happy automating! 🚀🔧

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

🌟 25 Essential DevOps Real-Time Interview Questions 🌟

Are you gearing up for a DevOps interview? Here are 25 critical questions that will help you shine! 💼💻

1.What is CI/CD and why is it important?
2. Explain the difference between Docker and Kubernetes.
3. How do you ensure high availability in a cloud environment?
4. What are the different stages in a DevOps pipeline?
5. How do you monitor and troubleshoot application performance?
6. Describe a situation where you had to resolve a production issue.
7. What are some best practices for infrastructure as code (IaC)?
8. How do you handle security in a DevOps workflow?
9. What tools do you use for configuration management and why?
10. Explain the concept of blue-green deployment.
11. How does container orchestration work?
12. What is the role of a reverse proxy in a DevOps environment?
13. How do you implement logging and monitoring for microservices?
14. What is a service mesh and why is it useful?
15. Can you explain the concept of immutable infrastructure?
16. How do you manage secrets and sensitive data in your deployments?
17. What are the key metrics you monitor in a DevOps environment?
18. How do you handle load balancing and scaling in Kubernetes?
19. What is a canary deployment and how is it different from blue-green deployment?
20. How do you ensure disaster recovery and backup in cloud infrastructure?
21. What are the common challenges in a DevOps transformation?
22. Explain the use of Ansible/Puppet/Chef in DevOps.
23. How do you integrate security practices into your CI/CD pipeline?
24. What is the significance of automated testing in DevOps?
25. How do you manage and optimize costs in a cloud environment?

💡 Tip: Be ready to discuss real-world scenarios and your hands-on experience with various DevOps tools and practices.

Good luck! 🍀


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

❄️If you want to become good at Kubernetes in ❄️❄️❄️❄️, then learn these use cases:


❄️ Kubernetes Architecture Crash Course
❄️ https://lnkd.in/gmRDrusm

❄️ How a Pod is Deleted - Behind the Scenes Breakdown
❄️ https://lnkd.in/geW8kaQm

❄️ pod.yaml File Structure Breakdown
❄️ https://lnkd.in/g7yhk_tS

❄️ Kubernetes ImagePullBackOff Explained
❄️ https://lnkd.in/gzCTSWRG

❄️ KubeConfig Bloat Problem and Remedy
❄️ https://lnkd.in/gavqgk5n

❄️ How To Fix Kubernetes Node Not Ready
❄️ https://lnkd.in/gksPqZYF

❄️ Hidden Risk Of Relying On Labels In Kubernetes Security
❄️ https://lnkd.in/gahmCwBB


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

🔖90% of 𝐃𝐞𝐯𝐎𝐩𝐬 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬 Come From These Topics:


Preparing for a DevOps interview? Focus on these core areas to boost your chances, especially for those with 0-4 years of experience.

🔻 𝐋𝐢𝐧𝐮𝐱 𝐁𝐚𝐬𝐢𝐜𝐬: Shell scripting, basic commands, file systems, process management

🔻 𝐆𝐢𝐭 & 𝐕𝐞𝐫𝐬𝐢𝐨𝐧 𝐂𝐨𝐧𝐭𝐫𝐨𝐥: Branching, merging, conflict resolution

🔻 𝐂𝐈/𝐂𝐃 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬: Get familiar with Jenkins or GitLab CI. Understand how automated testing and deployment work.

🔻 𝐂𝐥𝐨𝐮𝐝 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦𝐬: Whether it's AWS, GCP, or Azure, make sure you know core services like EC2, S3, VPC and IAM.

🔻 𝐂𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫𝐬 & 𝐊8𝐬: Basics of containers, K8s networking, and volumes

🔻 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 𝐚𝐬 𝐂𝐨𝐝𝐞 (𝐈𝐚𝐂): Terraform or CloudFormation.

🔻 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 & 𝐋𝐨𝐠𝐠𝐢𝐧𝐠: Prometheus, Grafana, ELK stack. Learn the basics.

🔻 𝐍𝐞𝐭𝐰𝐨𝐫𝐤𝐢𝐧𝐠 𝐁𝐚𝐬𝐢𝐜𝐬: DNS, TCP/IP, load balancing, and firewalls. Don't overlook this

⚡️𝐏𝐫𝐨 𝐓𝐢𝐩: Build a small project, deploy it on the cloud, and automate the process. Hands-on experience is invaluable in interviews!

With 4+ 𝐲𝐞𝐚𝐫𝐬 of DevOps experience, I can confidently say mastering these topics will set you up for success.


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

♾ Continuous Delivery vs. Continuous Deployment


➡️ Continuous Delivery: It ensures that your code changes are always deployable, providing a reliable and automated process for building, testing, and preparing for release. However, the deployment to production is a manual step, allowing for human intervention and control over when changes go live.

➡️ Continuous Deployment: It takes automation to the next level by automatically deploying every successful change to production. This means that once code passes all tests and checks, it's automatically pushed into production without the need for manual intervention.


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

⭐️ 𝘼𝙡𝙡 𝙞𝙣 𝙊𝙣𝙚 𝙗𝙪𝙙𝙙𝙡𝙚 𝙤𝙛 𝙆𝙪𝙗𝙚𝙧𝙣𝙚𝙩𝙚𝙨 ⭐️


📱 SOURCE LINK: https://github.com/NotHarshhaa/Kubernetes

🛑 This Repository includes:-

- Deployment manifest files
- Jenkins deployments & configurations
- Kubernetes Ingress files
- Realtime projects manifest files
- Helm charts for any application
- End to End Manifest files for any applications
- Includes AWS ELK Stack (Elasticsearch, Logstash, Kibana)
- Network service configurations templates
- Application monitoring templates for any applications
- Complete application launch manifest files for Realtime projects


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

🔤 𝐀𝐜𝐜𝐞𝐥𝐞𝐫𝐚𝐭𝐞 𝐘𝐨𝐮𝐫 𝐒𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐏𝐫𝐨𝐜𝐞𝐬𝐬 𝐰𝐢𝐭𝐡 𝐉𝐞𝐧𝐤𝐢𝐧𝐬

Jenkins is a powerful tool for revolutionizing software delivery, not merely a CI/CD tool.

🔤Here's a fresh take on using Jenkins efficiently if you want to speed up deployments and beat the competition.

1️⃣. 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐞 𝐌𝐮𝐥𝐭𝐢-𝐄𝐧𝐯𝐢𝐫𝐨𝐧𝐦𝐞𝐧𝐭 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭𝐬
Tired of manually configuring environments? Jenkins pipelines allow you to set up workflows for multi-environment deployments (e.g., dev, staging, production) with ease.
• Use parameterized builds to dynamically deploy to specific environments.
• Leverage environment-specific configurations using tools like Ansible or Helm.

2️⃣. 𝐈𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭 𝐅𝐞𝐚𝐭𝐮𝐫𝐞-𝐁𝐚𝐬𝐞𝐝 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭𝐬 𝐰𝐢𝐭𝐡 𝐁𝐥𝐮𝐞-𝐆𝐫𝐞𝐞𝐧 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐞𝐬
Jenkins simplifies feature-based rollouts using Blue-Green Deployment Pipelines:
• Create two identical environments (blue and green).
• Use Jenkins to seamlessly route traffic to the “green” environment once the new version is stable.

3️⃣. 𝐄𝐦𝐩𝐨𝐰𝐞𝐫 𝐓𝐞𝐚𝐦𝐬 𝐰𝐢𝐭𝐡 𝐒𝐞𝐥𝐟-𝐒𝐞𝐫𝐯𝐢𝐜𝐞 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭
Stop the bottleneck of centralized deployment processes.
•Use Jenkins with developer portals like Backstage to enable self-service deployments for teams.
•Integrate RBAC (Role-Based Access Control) to ensure that only authorized users can trigger specific pipelines.

4️⃣. 𝐌𝐨𝐧𝐢𝐭𝐨𝐫 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐇𝐞𝐚𝐥𝐭𝐡 𝐢𝐧 𝐑𝐞𝐚𝐥 𝐓𝐢𝐦𝐞
Don’t wait for failures to escalate-track them in real time.
•Integrate Jenkins with monitoring tools like Prometheus, Grafana, or Splunk to visualize pipeline metrics.
•Use custom notifications (Slack, email, or Teams) to alert teams about deployment performance or anomalies.

5️⃣. 𝐔𝐬𝐞 𝐉𝐞𝐧𝐤𝐢𝐧𝐬 𝐟𝐨𝐫 𝐏𝐫𝐨𝐠𝐫𝐞𝐬𝐬𝐢𝐯𝐞 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐲
Implement modern delivery techniques like:
• 𝐂𝐚𝐧𝐚𝐫𝐲 𝐑𝐞𝐥𝐞𝐚𝐬𝐞𝐬: Gradually expose new features to a subset of users and expand after validation.
•𝐂𝐚𝐧𝐚𝐫𝐲 𝐑𝐞𝐥𝐞𝐚𝐬𝐞𝐬:Manage feature visibility dynamically during or after deployment.

6️⃣. 𝐂𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫-𝐍𝐚𝐭𝐢𝐯𝐞 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭𝐬 𝐰𝐢𝐭𝐡 𝐉𝐞𝐧𝐤𝐢𝐧𝐬
Accelerate containerized application deployment by integrating Jenkins with Kubernetes and Docker.
•Automate container builds and push them to registries like Docker Hub or Amazon ECR.
•Deploy containers directly to Kubernetes clusters using plugins like Kubernetes Continuous Deploy.

7️⃣. 𝐃𝐫𝐢𝐯𝐞 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧 𝐰𝐢𝐭𝐡 𝐆𝐢𝐭𝐎𝐩𝐬
Jenkins can supercharge GitOps workflows by syncing deployments with code repositories.
•Trigger pipelines based on Git commits or pull requests.
•Validate changes automatically through linting, testing, and security scans.


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

☄️ 𝗕𝗲𝘀𝘁 𝐘𝐨𝐮𝐭𝐮𝐛𝐞 📱 𝐜𝐡𝐚𝐧𝐧𝐞𝐥𝐬 𝗧𝗼 𝗟𝗲𝗮𝗿𝗻 𝗗𝗲𝘃𝗢𝗽𝘀 ♾


🌐 LogicOps Lab by Ravish Rawat ( Real time Interview's )
🔗 https://lnkd.in/g3rtbjHb

🌐 Real time projects @mr.cloudbook
🔗 https://lnkd.in/gWWqHnJx

🌐 Train With Shubham by Shubham Londhe
🔗 https://lnkd.in/g9SwADkB

🌐 Tech Tutorials with Piyush by Piyush sachdeva (Azure and GCP cloud)
🔗 https://lnkd.in/g4iWpScc

🌐 TechWorld With Nana by Nana Janashia
🔗 https://lnkd.in/g7iFKKb9

🌐 KodeKloud by Mumshad Mannambeth
🔗 https://lnkd.in/g2jdc__p

🌐 Stéphane Maarek
🔗 https://lnkd.in/gzSbeKFt

🌐 Technical Guftgu by Bhupinder Rajput l भूपिंदर राजपूत l بھوپندر راجپوت In Hindi
🔗 https://lnkd.in/g8FYMCAS

🌐 Cloud Advocate by Krishna Chaitanya Gadhiraju (GK)
🔗 https://lnkd.in/giNb536Y

🌐 Abhishek Veeramalla
🔗 https://lnkd.in/gMfRacqy

🌐 Cloud Champ by Nasiullha Chaudhari
🔗 https://lnkd.in/gYUQ4r5x

🌐 Praveen Singampalli
🔗 https://lnkd.in/gVAeX8dZ


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

Whether you are automating with Ansible, deploying with Terraform, or scaling with Kubernetes, Linux is the core that keeps DevOps running.

It is not just a preference; it is the heart of DevOps.

1. Basics

- Linux for Noobs (Hands-on)
https://lnkd.in/dsi3rZD2

- Intro to Linux Fundamentals - What is Linux?
https://lnkd.in/dc-fVvfq

- Practice on Linux fundamentals
https://linuxjourney.com/

- Learn the Linux Fundamentals - Part 1
https://lnkd.in/dF67i8KP

2. Editing Files - Learn Vim Progressively
https://lnkd.in/dpHcCrJ9

3. Working with Files
https://lnkd.in/dpHcCrJ9

4. Master Linux Text Processing Commands with Our Comprehensive Guide
https://lnkd.in/djdXTi7y

5. Server Review

- Uptime Load
https://lnkd.in/dVfRieuJ

- Auth Logs
https://lnkd.in/d2u_7UrK

- Services Running
https://lnkd.in/dyrGDBC4

- Evaluating Available Memory
https://lnkd.in/dREPwPAF

6. Understanding Linux Process Management
https://lnkd.in/d7MhqPE6

7. User Management
https://lnkd.in/dXEEqzAZ

8. Service Management
start, stop, restart Linux services (daemon HUNTING!!)
https://lnkd.in/df5JUVpi

9. Package Management
https://lnkd.in/dZsXHF6X

10. Linux Disks Filesystems
https://lnkd.in/dJitXYbB

11. Booting Linux
https://lnkd.in/dnJ7nRXB

12. Networking
https://lnkd.in/dRiKdXGQ

13. Shell Programming
https://lnkd.in/d58tjyBU

14. Troubleshooting
https://lnkd.in/dF26NVzN


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

➡️ 𝐏𝐫𝐨𝐦𝐞𝐭𝐡𝐞𝐮𝐬 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 🔬

Prometheus is an open-source monitoring and alerting toolkit designed for reliability and scalability. Below is a an overview of the Prometheus architecture:

🏮 Components:
🖥 Prometheus Server:
- Core for collecting, storing, and querying time-series data.
- It’s pull-based and scrapes metrics from targets at regular intervals.
- Stores data in a local time-series database.
❤️ Metrics (Targets/Exporters):
- Apps or services expose metrics.
- Prometheus scrapes metrics from these targets.
📶 Data Model:
- Time-series data with metric names and labels.
- Example: `http_requests_total{method="GET", status="200"}`.
⚠️ PromQL:
- Query language for time-series data.
- Allows filtering, grouping, and math operations on metrics.
⚠️ Alertmanager:
- Handles alerts from Prometheus.
- Manages notifications and integrates with third-party channels.
☁️ Storage:
- Uses local on-disk storage.
- Data retention policies.
- Data is organized in blocks and compacted over time.

🏮 Workflow:
🌐 Configuration:
- Targets and scrape intervals defined in Prometheus config files.
- Relabeling allows modifying or filtering metrics before storage.
📚 Scraping:
- Prometheus Server scrapes metrics from configured targets.
- Targets expose metrics typically at /metrics endpoint.
☁️ Storage:
- Scraped metrics stored in the local time-series database.
- Data organized by metric name and labels.
📚 Querying:
- Users utilize PromQL to query and analyze stored metrics.
- Grafana or Prometheus's UI visualizes query results.
⚠️ Alerting:
- Prometheus evaluates alerting rules based on queries.
- Alerts sent to Alertmanager if conditions are met.
⚠️ Alertmanager Handling:
- Alertmanager receives alerts and manages their lifecycle.
- Handles deduplication, grouping, and sends notifications to configured channels.


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

🔖 Surprising but true: Many Cloud Engineers are unaware of VPC limits and its components!

Know your limits before they limit you.

1️⃣ VPC & Subnets
🚫 VPCs per Region = 05 (You can increase this limit so that you can have hundreds of VPCs per Region.)
🚫 Subnets per VPC = 200
🚫 IPv4 CIDR blocks per VPC = 05 (Adjustable up to 50)
🚫 IPv6 CIDR blocks per VPC = 05 (Adjustable up to 50)

2️⃣ Elastic IP addresses
🚫 Elastic IP addresses per Region = 05 (Adjustable = Yes)
🚫 Elastic IP addresses per public NAT gateway = 02 (Adjustable = Yes)

3️⃣ Gateways
🚫 Egress-only internet gateways per Region = 05 (Adjustable = Yes)
🚫 Internet gateways per Region = 05 (Adjustable = Yes)
🚫 NAT gateways per Availability Zone = 05 (Adjustable = Yes)
🚫 Private IP address quota per NAT gateway = 08 (Adjustable = Yes)
🚫 Carrier gateways per VPC = 01 (Adjustable = No)

4️⃣ Network ACLs
🚫 Network ACLs per VPC = 200 (Adjustable = Yes)
🚫 Rules per network ACL = 20 (Adjustable = Yes)

5️⃣ Network interfaces
🚫 Network interfaces per instance = Varies by instance type (Adjustable = No)
🚫 Network interfaces per Region = 5,000 (Adjustable = Yes)

6️⃣ Route tables
🚫 Route tables per VPC = 200 (Adjustable = Yes)
🚫 Routes per route table (non-propagated routes) = 50 (Adjustable = Yes)
🚫 Propagated routes per route table = 100 (Adjustable = No)

7️⃣ Security groups
🚫 VPC security groups per Region = 2,500 (Adjustable = Yes)
🚫 Inbound or outbound rules per security group = 60 (Adjustable = Yes)
🚫 Security groups per network interface = 05 (Adjustable = up to 16)

8️⃣ VPC subnet sharing
🚫 Participant accounts per VPC = 100 (Adjustable = Yes)
🚫 Subnets that can be shared with an account = 100 (Adjustable = Yes)

9️⃣ Network Address Usage
🚫 Network Address Usage = 64,000 (Adjustable up to to 256,000)
🚫 Peered Network Address Usage = 128,000 (Adjustable up to 512,000))

🔟 VPC peering connection
🚫 Active VPC peering connections per VPC = 50 (Adjustable up to 125)
🚫 Outstanding VPC peering connection requests = 25 (Adjustable = Yes)

1️⃣ 1️⃣ Site-to-Site VPN resources
🚫 Customer gateways per Region = 50 (Adjustable = Yes)
🚫 Virtual private gateways per Region = 05 (Adjustable = Yes)
🚫 Site-to-Site VPN connections per Region = 50 (Adjustable = Yes)
🚫 Site-to-Site VPN connections per virtual private gateway = 10 (Adjustable = Yes)

1️⃣ 2️⃣ AWS Client VPN quotas
🚫 Authorization rules per Client VPN endpoint = 50 (Adjustable = Yes)
🚫 Client VPN endpoints per Region = 05 (Adjustable = Yes)


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

▶️ Azure DevOps project ideas that can enhance your skills and showcase your ability to implement DevOps practices:


🔢. Continuous Integration/Continuous Deployment (CI/CD) Pipeline:
- Build a CI/CD pipeline for a web application using Azure DevOps.
- Integrate automated testing and deployment to Azure App Service.

🔢. Infrastructure as Code (IaC):
- Use Azure Resource Manager (ARM) templates or Terraform to provision and manage Azure resources.
- Automate the deployment of an application with all required services (like databases, storage).

🔢. Monitoring and Logging Solution:
- Implement a monitoring solution using Azure Monitor and Application Insights.
- Create dashboards to visualize application performance and logs.

🔢. Microservices Architecture:
- Develop a microservices-based application using Azure Kubernetes Service (AKS).
- Set up CI/CD pipelines for individual microservices and manage them with Helm charts.

🔢. Serverless Application:
- Create a serverless application using Azure Functions.
- Integrate with Azure Logic Apps for orchestrating workflows.

🔢. Automated Testing Framework:
- Develop a test automation framework using Selenium or Cypress.
- Integrate the framework with Azure DevOps for automated testing during builds.

🔢. ChatOps Implementation:
- Use Azure DevOps with Microsoft Teams to automate build notifications and issue tracking via chat commands.

🔢. Data Pipeline Project:
- Create a data processing pipeline using Azure Data Factory.
- Implement data ingestion, transformation, and loading into a data warehouse or lake.

🔢. Security and Compliance:
- Set up Azure DevOps to include security scans (using tools like SonarCloud) and compliance checks in the CI/CD process.

🔢🔢. Integrate Third-Party Services:
- Build a project that integrates third-party APIs (e.g., GitHub, Jira) into Azure DevOps workflows for enhanced collaboration.

➡️ These projects can be tailored according to your interests and expertise level, allowing you to explore various features of Azure DevOps while building practical applications.


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