➡️ Ways to practice Azure for Free

- Make a trail account (30 days validity)
- Use different CC/Email/Phone no for next
- Make student Azure account (.edu mail id)
- Student account valid for 1 year
- Check hacks on YouTube to get .edu mail id
- Check telegram for Azure prepaid pass (vouchers)

Options are many, any more excuse for not practicing?


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

Are you optimizing your kubernetes workloads for efficiency? One key aspect is controlling resource usage within pods to ensure optimal performance and resources utilization.

🔍 Resource Requests:
➖ Specify minimum CPU and memory requirements for pods.
➖ Helps Kubernetes scheduler make informed placement decisions.
➖ Ensures pods have necessary resources to run effectively.

📈 Resource Limits:
➖ Set upper bounds on CPU and memory usage.
➖ Prevents pods from monopolizing resources.
➖ Maintains stability and reliability across the cluster.


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

➡️ Why ArgoCD is so Popular ?

↳ In GitOps world everyone is aware about the ArgoCD.

It's has tremendous features due to which its first choice of almost every DevOps engineer.

1. 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 of applications to specified target environment in multiple clusters
Support for multiple config management/templating tools-->
• Kustomize
• Helm
• Ksonnet
• Jsonnet
• Plain-YAML

2. 𝗦𝗦𝗢 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 :
• OIDC
• OAuth2
• LDAP
• SAML 2.0
• GitHub
• GitLab
• Microsoft
• LinkedIn

3. 𝗠𝘂𝗹𝘁𝗶-𝘁𝗲𝗻𝗮𝗻𝗰𝘆 𝗮𝗻𝗱 𝗥𝗕𝗔𝗖 policies for authorization

4. 𝗥𝗼𝗹𝗹𝗯𝗮𝗰𝗸/𝗥𝗼𝗹𝗹-𝗮𝗻𝘆𝘄𝗵𝗲𝗿𝗲 to any application configuration committed in Git repository.
• Health status analysis of application resources

5. 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗰𝗼𝗻𝗳𝗶𝗴𝘂𝗿𝗮𝘁𝗶𝗼𝗻 𝗱𝗿𝗶𝗳𝘁 detection and visualization

6. Out-of-the-box Prometheus metrics

7. Audit trails for application events and API calls

8. PreSync, Sync, PostSync hooks:
• Support complex application rollouts
-> blue/green
-> canary upgrades

9. Web-hook integration
-> GitHub
-> BitBucket
-> GitLab

10. CLI and access tokens for automation and Cl integration

11. Web UI which provides real-time view of application activity

12. Automated or manual syncing of applications to its desired state


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

📌 https://harshhaa.hashnode.dev/deploying-an-app-to-aks-using-azure-devops-azure-cloud-shell

🔗 More DevOps Projects : HERE

🔗 More DevOps Blogs : HERE

🔥🔥🔥🔥🔥🔥🔥🔥

Follow 🍩 Like 👍 Share 👍 Comment Your thoughts 💬

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

🔣 𝐔𝐧𝐥𝐨𝐜𝐤𝐢𝐧𝐠 𝐭𝐡𝐞 𝐏𝐨𝐰𝐞𝐫 𝐨𝐟 𝐂𝐥𝐨𝐮𝐝-𝐍𝐚𝐭𝐢𝐯𝐞 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧! 🚀 🚀

Ever wondered how to transition your system to embrace cloud-native architecture?

🌐 Check out this action spectrum and adoption roadmap - it's your blueprint to success!

➡️ Here's what you need to focus on:

1️⃣ Application definition development
2️⃣ Orchestration and management
3️⃣ Runtime optimization
4️⃣ Efficient provisioning
5️⃣ Enhanced observability
6️⃣ Harnessing the power of serverless computing


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

➡️𝗔𝗪𝗦 𝟑-𝐭𝐢𝐞𝐫 𝐚𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐑𝐞𝐟𝐞𝐫𝐞𝐧𝐜𝐞 𝐚𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞

Crafting secure and scalable cloud applications on AWS requires a solid foundation. This post explores the essential building blocks that form a typical AWS end-to-end application architecture.

🔶 𝗘𝘀𝘀𝗲𝗻𝘁𝗶𝗮𝗹 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗕𝗹𝗼𝗰𝗸𝘀:

✔️ AWS VPC (Virtual Private Cloud): A secure, isolated neighborhood within the cloud is your VPC, housing all your application resources and providing a private network.

✔️ Subnets: These are sub-divisions within your VPC. They segment your network further, allowing you to isolate public-facing components from private ones.

✔️ Servers: The workhorses of your application. Web servers handle requests, application servers handle the logic. Run them on EC2 instances (flexible, separate, or combined).

✔️ RDS: This manages service stores your application's data. It offers a variety of database engine options and ensures reliability and scalability.

✔️ Load Balancer: It distributes incoming user requests across multiple EC2 instances, ensuring your application remains available and performs fine under heavy traffic.

✔️ Auto Scaling Group: An Auto Scaling Group scales your EC2 instances up or down based on predefined rules, ensuring your application can handle fluctuating loads with ease.

✔️ Security Groups: These are virtual firewalls for your EC2 instances. They control incoming and outgoing traffic, enforcing security and access restrictions.

✔️ Route 53: This is your domain name manager in the cloud. Route 53 directs users to your application's endpoint (often a Load Balancer) and allows you to register and manage your domain names.

🔶 𝗕𝗲𝗻𝗲𝗳𝗶𝘁𝘀 𝗼𝗳 𝗮 𝗪𝗲𝗹𝗹-𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝗲𝗱 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻

By leveraging these core components, you can design an AWS architecture that's:

✔️ Scalable: Easily adapts to accommodate growth in traffic and data.

✔️ Secure: Provides robust security measures to protect your application and data.

✔️ Highly Available: Ensures your application remains accessible even during failures.


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

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


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

👉 🆘 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!!!

🤔 Learn Kubernetes from scratch (Beginner to Advanced level) 2024 🤔

🔗 Link: https://github.com/NotHarshhaa/kubernetes-learning-path

🪑 NOTE: The Kubernetes Learning Roadmap is constantly updated with new content.

⏩ Table of Contents ⏪
1. Kubernetes Learning Roadmap
2. Kubernetes Certification Coupon
3. Kubernetes Learning Prerequisites
4. Learn Kubernetes Architecture
5. $1000+ Free Cloud Credits to Launch Clusters
6. Learn Kubernetes Cluster Setup & Administration
7. Understand KubeConfig File
8. Understand Kubernetes Objects And Resources
9. Learn About Pod & Associated Resources
10. Learn About Pod Dependent Objects
11. Deploy End to End Application on Kubernetes
12. Learn About Securing Kubernetes Cluster
13. Learn About Kubernetes Operator Pattern
14. Learn Important Kubernetes Configurations
15. Learn Kubernetes Best Practices
16. Real-World Kubernetes Case Studies
17. Kubernetes Failures/Learnings
18. Kubernetes Deployment Tools (GitOps Based)


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

Hiring for these positions and fully remote work:
Send your resume : brinchitech@consultant.com

while sending resume, please mention position name

➡️ DevOps Engineer:
💻 Design and deployment of software systems.

➡️ Site Reliability Engineer (SRE):
💻 Ensuring the reliability of software systems.

➡️ Infrastructure Engineer:
💻 Design & implementation of infrastructure.

➡️ Cloud Engineer:
💻 Designing & implementing cloud-based infrastructure & services for software systems.

➡️ Systems Administrator:
💻 Administration & maintenance of computer systems.

➡️ Build and Release Engineer:
💻 Managing the build, testing, & release of software systems.

➡️ Configuration Management Engineer:
💻 Managing & maintaining software system configurations.

➡️ Continuous Integration/Continuous Deployment (CI/CD) Engineer:
💻 Implementing & maintaining processes & tools for continuous integration & deployment of software systems.

➡️ Operations Engineer:
💻 Operation & maintenance of software systems

🌐 AWS Disaster Recovery strategies 🌐

1️⃣. Backup:
This is the most basic level of disaster recovery readiness. It involves regular backups of data and systems, often stored offsite or in the cloud. In this context, "Back" likely refers to backing up data and systems to restore them in case of data loss or system failure.

2️⃣. Pilot Light:
This refers to a disaster recovery setup where essential systems are kept in a minimal operational state
In the event of a disaster, additional resources can be quickly provisioned to bring the system to full operational capacity. It's a step up from basic backup, offering a faster recovery time.

3️⃣.Warm Standby:
A warm standby site is a disaster recovery setup where duplicate hardware and infrastructure are maintained, but they are not actively processing data or serving users.
The infrastructure is configured and ready to take over in case the primary site fails. This setup typically involves periodic synchronization of data and configurations to reduce recovery time.

➡️Hot Site:
A hot site is a fully operational secondary data center or environment that mirrors the primary production environment. It is continuously updated and synchronized with the primary site in real-time or near real-time.
In the event of a disaster, operations can seamlessly switch to the hot site with minimal disruption, offering the shortest recovery time objective (RTO) and recovery point objective (RPO).


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

👉Continuous deployment as sumes that every product change or update is deployed automatically to production without any manual supervision from a DevOps engineer.

💡 Continuous Delivery:
- Automates the release process.
- Ensures readiness for deployment at any time.
- Allows manual deployment when needed.

💡 Continuous Deployment:
- Automates deployment of every successful code change.
- Directly deploys to production without human intervention.
- Requires high confidence in automated testing.


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

🔖 𝐇𝐨𝐰 𝐭𝐨 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐞 𝐃𝐞𝐯𝐎𝐩𝐬 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞 𝐔𝐬𝐢𝐧𝐠 𝐉𝐞𝐧𝐤𝐢𝐧𝐬!

Jenkins is a popular automation server that can be used to automate the CI/CD pipeline. In this post we will learn how to use Jenkins to automate the following steps:

✅ Checkout code from version control: Jenkins can be configured to automatically checkout code from a version control system, such as GitHub.
✅ Compile code: Jenkins can use a variety of build tools, such as Maven or Gradle, to compile the code.
✅ Run unit tests: Jenkins can run unit tests to ensure that the code is working properly.
✅ Build a Docker image: Jenkins can build a Docker image from the compiled code.
✅ Push Docker image to registry: Jenkins can push the Docker image to a Docker registry, such as Docker Hub.
✅ Deploy to Kubernetes: Jenkins can notify Kubernetes of the new Docker image and deploy it to a Kubernetes cluster.


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

🐳 𝗗𝗼𝗰𝗸𝗲𝗿 𝗕𝗲𝘀𝘁 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀! 🐳

Docker has revolutionized the world of containerization, enabling scalable and efficient application deployment.

To make the most of this powerful tool, here are 10 essential Docker best practices:

✔️ 𝗦𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝗮 𝗟𝗶𝗴𝗵𝘁𝘄𝗲𝗶𝗴𝗵𝘁 𝗕𝗮𝘀𝗲 𝗜𝗺𝗮𝗴𝗲: Use minimalist base images to reduce container size and vulnerabilities.

✔️ 𝗦𝗶𝗻𝗴𝗹𝗲 𝗣𝗿𝗼𝗰𝗲𝘀𝘀 𝗽𝗲𝗿 𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿: Keep it simple - one process per container for better isolation and maintainability.

✔️ 𝗨𝘀𝗲 𝗗𝗼𝗰𝗸𝗲𝗿 𝗖𝗼𝗺𝗽𝗼𝘀𝗲: Define multi-container applications in a YAML file for easy management.

✔️ 𝗩𝗼𝗹𝘂𝗺𝗲 𝗠𝗼𝘂𝗻𝘁𝗶𝗻𝗴: Store data outside the container to preserve it, even if the container is removed.

✔️ 𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻: Consider Kubernetes or Docker Swarm for managing containers at scale.

✔️ 𝗩𝗲𝗿𝘀𝗶𝗼𝗻𝗶𝗻𝗴 𝗮𝗻𝗱 𝗧𝗮𝗴𝗴𝗶𝗻𝗴: Always tag images with version numbers to ensure reproducibility.

✔️ 𝗛𝗲𝗮𝗹𝘁𝗵 𝗖𝗵𝗲𝗰𝗸𝘀: Implement health checks to monitor container status and reliability.

✔️ 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲 𝗟𝗶𝗺𝗶𝘁𝘀: Set resource constraints to prevent one container from hogging resources.

✔️ 𝗗𝗼𝗰𝗸𝗲𝗿𝗳𝗶𝗹𝗲 𝗕𝗲𝘀𝘁 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀: Optimize Dockerfiles by minimizing layers and using caching effectively.

✔️ 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆: Regularly update images, scan for vulnerabilities, and follow security best practices.


🌐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

🔣 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝗖𝗼𝗺𝗺𝗼𝗻 𝗘𝗿𝗿𝗼𝗿𝘀 🔣

1️⃣.𝙄𝙢𝙖𝙜𝙚𝘽𝙖𝙘𝙠𝙋𝙪𝙡𝙡𝙊𝙛𝙛 :-
We face this issue when the image is not present in registry or the given image tag is wrong.
Make sure you provide correct registry url, image name and image tag.

We might face authentication failures, when image is being stored in a private registry, make sure to create secret with private registry credentials and add created secret in Kubernetes Deployment File to pull docker image.

2️⃣.𝘾𝙧𝙖𝙨𝙝𝙇𝙤𝙤𝙥𝘽𝙖𝙘𝙠𝙊𝙛𝙛 :-
We face this issue when the process deployed inside container not running then the POD will be moved to CrashLoopBackOff.
POD might be running out of CPU or memory, POD should get enough resources allocated that’s cpu and memory for an application to be up and running, to fix that check in Resources Requests and Resources Limits.

3️⃣.𝙊𝙊𝙈 𝙆𝙞𝙡𝙡𝙚𝙙 - 𝙊𝙪𝙩 𝙊𝙛 𝙈𝙚𝙢𝙤𝙧𝙮 :-
We face this issue when PODs tries to utilise more memory than the limits we have set.
We can resolve it by setting appropriate resource request and resource limit.

4️⃣.𝙋𝙊𝘿 𝙎𝙩𝙖𝙩𝙪𝙨 – 𝙋𝙚𝙣𝙙𝙞𝙣𝙜 :-
When nodes might not be ready and required resources like CPU and Memory may not be available in nodes for the PODs to be up and running.

5️⃣.𝙋𝙊𝘿 𝙎𝙩𝙖𝙩𝙪𝙨 – 𝙒𝙖𝙞𝙩𝙞𝙣𝙜 :-
POD will be scheduled to a node but POD won’t be running in scheduled node.
We can fix this by providing correct image name, image tag and authentication to registry.

6️⃣.𝙋𝙊𝘿 𝙬𝙞𝙡𝙡 𝙗𝙚 𝙪𝙥 𝙖𝙣𝙙 𝙧𝙪𝙣𝙣𝙞𝙣𝙜 𝙖𝙣𝙙 𝙖𝙥𝙥𝙡𝙞𝙘𝙖𝙩𝙞𝙤𝙣 𝙞𝙨 𝙣𝙤𝙩 𝙖𝙘𝙘𝙚𝙨𝙨𝙞𝙗𝙡𝙚.
We can fix this by creating appropriate service.
If service is already created and application is still not accessible, make sure application and service are deployed in same namespace.

7️⃣.𝙋𝙊𝘿 𝙎𝙩𝙖𝙩𝙪𝙨 – 𝙀𝙫𝙞𝙘𝙩𝙚𝙙 :-
We can resolve this by setting appropriate resource requests and resource limits for the PODs and having enough resources in worker nodes.


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

📌 Title: DevOps Engineer

➡️ Location: Remote

➡️ Job Description:

1-10 years of exp in DevOps (AWS/ Azure/ GCP).
Hands-on exp in deploying Kubernetes cluster using ELK/ GKE environment.
Creating CI/CD pipeline using Jenkins.
Using Monitoring tools like Prometheus/ Grafana/ Stack driver.
Docker
Infra Automation scripting

🖥 Interested upload resume with 100% details - https://lnkd.in/eFn7aja


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

🔴 Architecture of a Kubernetes Cluster ☸️

A production-ready Kubernetes cluster is vastly complex. There are many non-negotiable such as High Availability, Fault Tolerance, data backups and durability requirements.

Its architecture is divided into the Control Plane and Data Plane.
This is what they do 👇

➡️ DATA PLANE
The part of the cluster where all compute resources reside. This is where ultimately all your container applications run.

1️⃣Nodes
The worker machines that actually run container workloads. These could be EC2 servers (or other cloud provider equivalents), bare-metal servers or even just your personal computer.

2️⃣Pods
The smallest unit of compute that you can deploy in K8s. A Pod contains 1 or more containers running your application(s) and helper processes. A Pod runs inside a Node.

3️⃣Kubelet
An agent that runs on every Node. It takes Pod specifications provided by the user and ensures that the Containers described in them are running and healthy.

4️⃣Kube-proxy
Runs on every Node and manages network rules on the system to ensure network communication works smoothly between Pods and the outside world.

5️⃣Container Runtime
Runs on all nodes and manages the lifecycle of container(s) deployed on them. Eg- Docker, CRI-O, etc.

➡️ CONTROL PLANE
Does the administrative tasks of managing worker nodes, Pods and the cluster in general.
It is basically the “brains” of the cluster that makes all decisions like scheduling, always steering the cluster towards the desired state (eg- spin up new pods in response to some pods going down to maintain the desired number of them).

🔢Kube-apiserver
Exposes the Kubernetes API to the user. When you make an API request to Kubernetes or use a client like Kubectl, you request is handled by kube-apiserver and passed on for further processing.

🔢Etcd
A consistent and highly available Key-value store used by Kubernetes for storing all cluster data. You should have a strong backup strategy for this datastore as it tracks all state of the cluster.

🔢Scheduler
Responsible for placing Pods on to Nodes in the most optimal way possible. When a new Pod is requested, the scheduler looks for a suitable Node to run it in.
Takes many different factors into consideration while scheduling, such as resource requirements, priority, user-specified criteria, etc.

🔢Controller Manager
Runs Controllers. A Controller is a process that always steers the system toward a desired state. Eg- A Node controller monitors and responds when nodes go down.

🎄 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!