😀 A Kubernetes service is a 𝗹𝗼𝗴𝗶𝗰𝗮𝗹 𝗰𝗼𝗹𝗹𝗲𝗰𝘁𝗶𝗼𝗻 𝗼𝗳 𝗽𝗼𝗱𝘀 in a Kubernetes cluster and 𝗲𝗮𝘀𝗶𝗹𝘆 𝗲𝘅𝗽𝗼𝘀𝗲 𝗮𝗻 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 deployed on a set of pods using a single endpoint.

➡️ If a service is keeping track of pods 𝘂𝘀𝗶𝗻𝗴 𝗹𝗮𝗯𝗲𝗹𝘀 𝗶𝗻𝘀𝘁𝗲𝗮𝗱 𝗼𝗳 𝗜𝗣 𝗮𝗱𝗱𝗿𝗲𝘀𝘀 and the label is always the same.

➡️ Labels are the 𝗽𝗿𝗼𝗽𝗲𝗿𝘁𝗶𝗲𝘀 attached to each item/object. Selector helps us to 𝗳𝗶𝗹𝘁𝗲𝗿 𝘁𝗵𝗲 𝗶𝘁𝗲𝗺𝘀/objects which have labels attached to them.

➡️ Each Pod gets its 𝗼𝘄𝗻 𝗶𝗻𝘁𝗲𝗿𝗻𝗮𝗹 𝗜𝗣 𝗮𝗱𝗱𝗿𝗲𝘀𝘀, but the Pods in K8s are ephemeral, meaning that they are destroyed frequently.

➡️ Pod restarts or when old one dies and the new one gets started in its place it 𝗴𝗲𝘁𝘀 𝗮 𝗻𝗲𝘄 𝗜𝗣 𝗮𝗱𝗱𝗿𝗲𝘀𝘀.

➡️ YAML is a human-friendly language. In the context of Kubernetes, YAML files are 𝗺𝗮𝗶𝗻𝗹𝘆 𝘂𝘀𝗲𝗱 𝗳𝗼𝗿 𝘁𝗵𝗲 𝗰𝗼𝗻𝗳𝗶𝗴𝘂𝗿𝗮𝘁𝗶𝗼𝗻 of K8 pods, services, and deployments.

In Kubernetes, YAML is a manifest file.

➡️ 𝗣𝗼𝗿𝘁 --> exposes the Kubernetes service on the 𝘀𝗽𝗲𝗰𝗶𝗳𝗶𝗲𝗱 𝗽𝗼𝗿𝘁 𝘄𝗶𝘁𝗵𝗶𝗻 𝘁𝗵𝗲 𝗰𝗹𝘂𝘀𝘁𝗲𝗿. Other pods within the cluster can communicate with this server on the specified port.

➡️ 𝗧𝗮𝗿𝗴𝗲𝘁𝗣𝗼𝗿𝘁 --> This is the port on the pod that the request gets 𝘀𝗲𝗻𝘁 𝘁𝗼 𝘆𝗼𝘂𝗿 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗻𝗲𝗲𝗱𝘀 𝘁𝗼 𝗯𝗲 𝗹𝗶𝘀𝘁𝗲𝗻𝗶𝗻𝗴 𝗳𝗼𝗿 𝗻𝗲𝘁𝘄𝗼𝗿𝗸 𝗿𝗲𝗾𝘂𝗲𝘀𝘁𝘀 𝗼𝗻 𝘁𝗵𝗶𝘀 𝗽𝗼𝗿𝘁 for the service to work.

💢 Services 💢
☑️ Load Balancing
☑️ Service Discovery
☑️ Expose to external world --> Outside K8's cluster

💢 Service types 💢
☑️ Cluster IP - Only accessible from within the cluster
☑️ Node port - Static port on each node’s IP
☑️ Load balancer - Cloud provider’s load balancer


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🔥 AZURE DEVOPS NOTES 2023


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📢 AWS Projects

📎 Link : https://drive.google.com/drive/folders/1XE1IPS2N0ValL8sImojb8VuWscymclzD?usp=drive_link


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☑️ Free Resources
☑️ eBook: Azure DevOps Security Checklist


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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

➡️ 𝗚𝗶𝘁, a fundamental tool that is indispensable for managing the complexities of modern codebases.
As a distributed version control system, Git offers unparalleled flexibility, robustness, and efficiency in handling code revisions, branches, and merges, making it the de facto standard for both open-source contributors and enterprise developers.

➡️ 𝗧𝗵𝗲 𝗽𝗼𝘄𝗲𝗿 𝗼𝗳 𝗚𝗶𝘁 lies not only in its capability to track changes and coordinate work among multiple contributors but also in its ability to facilitate a non-linear development process.
It enables developers to branch out, experiment, collaborate, and converge, thereby fostering innovation and speed in software development.

👉 This extensive list includes the most useful operations one can perform with Git, from basic setup and file handling to advanced repository management and automation.

While there are many more Git commands and options available, these operations form the core toolkit that most users will require for efficient version control with Git.


©: @prodevopsguy

🔥 SITE TO LEARN DEVOPS:

➡️ https://kodekloud.com/
➡️ https://lnkd.in/dVeX_UVV
➡️ https://lnkd.in/ddVE2r-3
➡️ https://www.edureka.co/
➡️ https://theitern.com/
➡️ https://intellipaat.com/
➡️ https://lnkd.in/dKZHTEce
➡️ https://www.udacity.com/
➡️ https://cloudacademy.com/

NOTE : WHEN YOU COPY TO PASTE ON YOUR PAGE, GIVE CREDIT


©: @prodevopsguy

🔥 Do you know what the day to day activities of DevOps Engineers are:


📌 Day to Day activities for DevOps Engineer

➡️1. Make sure that the pipeline is running smoothly - This is one of the most important tasks of a DevOps engineer to make sure that the CI/CD pipeline is intact and fixing any issue or failure with it is the #1 priority for the day. They often need to spend time on troubleshooting, analysing and providing fixes to issues.

➡️2. Interaction with other teams – Co-ordination and collaboration is the key for DevOps to be successful and hence daily integration with Dev and QA team, Program management, IT is always required.

➡️3. Work on Automation Backlog – Automation is soul of DevOps so DevOps engineering need to plan it out and I can see DevOps engineer spending lots of time behind the keyboard working on Automating stuff on daily basis.

➡️4. Infrastructure Management – DevOps engineer are also responsible for maintaining and managing the infrastructure required for CI/CD pipeline and making sure that its up #devops and running and being used optimally is also part of their daily schedule. Working on Backup, High Availability, New Platform setup etc.

➡️5. Dealing with Legacy stuff – Not everyone is lucky to work on latest and newest things and DevOps engineers are no exception hence they also need to spend time on legacy i.e. in terms of supporting it or migrating to the latest.

➡️6. Exploration – DevOps leverage a lot from the various tools which are available, there are many options as open source so teams need to regularly check on this to make sure the adoptions as required, this is something which also requires some effort not on a daily but regular basis. What are open source options available to keep the cost at minimum?

➡️7. Removing bottleneck – DevOps primary purpose is identify the bottlenecks / Manual handshakes and work with everyone involved (Dev / QA and all other stakeholder) to remove them so team spend good amount of time in finding such things and build the Automation Backlog using this.

➡️8. Documentation – Though Agile / DevOps stresses less on the documentation, it is still the important one which DevOps engineer does on daily basis, Be it Server Information, Daily Week charted, Scrum / Kanban board or Simple steps to configure / backup or modify the infrastructure, you need to spent good amount of time in coming up these artifacts.

➡️9. Training and Self Development – Self leaning and Training is very useful in getting better understanding and many organisations encourage their employee to take the time out and do some of these and same holds true for DevOps folks as well, So learn something new everyday.

➡️ 10. Continuous Improvement as Practice – Last but not least, It’s up to the DevOps folks to build awareness on the potential of CI/CD and DevOps practices and building a culture of leveraging it for doing things better, reducing re-work, increasing the productivity and optimising the use of existing resources.



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🔥 𝗖𝗜/𝗖𝗗: 𝗧𝗵𝗲 𝗦𝗲𝗰𝗿𝗲𝘁 𝘁𝗼 𝗙𝗮𝘀𝘁 𝗮𝗻𝗱 𝗥𝗲𝗹𝗶𝗮𝗯𝗹𝗲 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝘆 🚀

The software development life cycle (SDLC) can be a long and tedious process. But what if there was a way to automate it and make it faster, more reliable, and less error-prone?

That's where CI/CD comes in. CI/CD stands for continuous integration and continuous delivery (or continuous deployment). It's a set of practices that automate the SDLC, from development to testing to deployment.

➡️ Here's how it works:

1️⃣. Developers commit code changes to a version control system (like GitHub or GitLab).
2️⃣. A CI server automatically detects the changes and triggers a build.
3️⃣. The code is compiled and tested (unit tests, integration tests, and sometimes even end-to-end tests).
4️⃣. The test results are reported back to the developers.
5️⃣. If the tests pass, the code is deployed to a staging environment.
6️⃣. More testing can be done in staging before the code is released to production.
7️⃣. A CD server automatically deploys the approved changes to production.
CI/CD can help you:

✔️ 𝗥𝗲𝗹𝗲𝗮𝘀𝗲 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗳𝗮𝘀𝘁𝗲𝗿: CI/CD automates the build and deployment process, so you can release new features and bug fixes more quickly.
✔️ 𝐈𝐦𝐩𝐫𝐨𝐯𝐞 𝐪𝐮𝐚𝐥𝐢𝐭𝐲: CI/CD helps you find and fix bugs early, before they make it to production.
✔️ 𝐑𝐞𝐝𝐮𝐜𝐞 𝐑𝐢𝐬𝐤𝐬: CI/CD makes it easier to roll back changes if something goes wrong.
✔️ 𝐒𝐚𝐯𝐞 𝐭𝐢𝐦𝐞 𝐚𝐧𝐝 𝐦𝐨𝐧𝐞𝐲: CI/CD can save you time and money by automating manual tasks.

𝗜𝗳 𝘆𝗼𝘂'𝗿𝗲 𝗹𝗼𝗼𝗸𝗶𝗻𝗴 𝘁𝗼 𝗶𝗺𝗽𝗿𝗼𝘃𝗲 𝘁𝗵𝗲 𝘀𝗽𝗲𝗲𝗱, 𝗾𝘂𝗮𝗹𝗶𝘁𝘆, 𝗮𝗻𝗱 𝗿𝗲𝗹𝗶𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗼𝗳 𝘆𝗼𝘂𝗿 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘆, 𝗖𝗜/𝗖𝗗 𝗶𝘀 𝗮 𝗴𝗿𝗲𝗮𝘁 𝗽𝗹𝗮𝗰𝗲 𝘁𝗼 𝘀𝘁𝗮𝗿𝘁. 🏎


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🐳 𝐀 𝐪𝐮𝐢𝐜𝐤 𝐃𝐨𝐜𝐤𝐞𝐫 𝐦𝐚𝐠𝐢𝐜 𝐭𝐢𝐩! 🚀

Ever struggled with deploying multi-container applications? Enter 𝗱𝗼𝗰𝗸𝗲𝗿-𝗰𝗼𝗺𝗽𝗼𝘀𝗲 𝘂𝗽! ⬆️

One command to rule them all - orchestrating your containers seamlessly. ♾

Spin up your dev environment with ease, define services, and voila! But wait, there's more - when it's time to call it a day, simply do a graceful exit with 𝗱𝗼𝗰𝗸𝗲𝗿-𝗰𝗼𝗺𝗽𝗼𝘀𝗲 𝗱𝗼𝘄𝗻. ⬇️

Clean, efficient, and a game-changer for simplifying your development workflow.🚀


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🛠 Implementation of the Entire Advanced CI/CD Pipeline with Major DevOps Tools 🛠

➡️ Project Link : HERE

💥 Included Step by Step procedure
💥 Easy Understanding guide
💥 Used DevOps advanced Tools
💥 Each & Every Commands used in project are Included
💥 Tools used in Project :
✅ Jenkins
✅ Docker
✅ Kubernetes
✅ Ansible
✅ Terraform
✅ Prometeous
✅ Maven
✅ AWS
✅ SonarQube
✅ SonarCloud
✅ JFrog

Hit the Star! 🌟 & Follow me on GitHub for more like this

If you are planning to use this repo for learning, please hit the star.


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💥 Happy Diwali to you and your family! 🪔

This Diwali, I hope new opportunities come your way. Savour the celebrations to the fullest! 💥

🔥Enjoy a happy and safe Diwali!


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🔥 AWS & DevOps Free Videos :–


➡️ Part -1 : https://drive.google.com/drive/folders/1P2MORPWWUDk6MBzLktlahDRHJgh9YNta?usp=sharing

➡️ Part -2: https://drive.google.com/drive/folders/1-9pCWtNrSwWW3Bgd0BjqfH_x0sfJcXvE?usp=sharing

➡️ Part -3 : https://drive.google.com/drive/folders/1OD3B97MfmlQbnBVB_PMbt5bb5mtjyQk9?usp=sharing


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𝐓𝐨𝐩 𝟓 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐏𝐚𝐭𝐭𝐞𝐫𝐧𝐬 𝐲𝐨𝐮 𝐧𝐞𝐞𝐝 𝐭𝐨 𝐤𝐧𝐨𝐰 𝐢𝐧 𝟐𝟎𝟐𝟑 !!


🔴𝗖𝗮𝗻𝗮𝗿𝘆 𝗥𝗲𝗹𝗲𝗮𝘀𝗲𝘀 🦜 Introduce new features to a small group of users first 😀 to test their performance and identify any issues ⚠️ before rolling them out to everyone. This is like dipping your toe in the water before diving in headfirst 👣.

🔴𝗕𝗹𝘂𝗲/𝗚𝗿𝗲𝗲𝗻 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁: Create two identical production environments, one for live traffic 🚦 and one for testing 🧪. When you're ready to release a new feature, simply switch traffic from the blue environment to the green environment 🔄. This ensures a seamless transition with minimal downtime 🕐.

🔴𝗙𝗲𝗮𝘁𝘂𝗿𝗲 𝗧𝗼𝗴𝗴𝗹𝗲𝘀: Enable or disable features on demand 📈, giving you flexibility in how and when you release new features. This is like having a superpower to control what your users see and experience 🧙👀.

🔴𝗔/𝗕 𝗧𝗲𝘀𝘁𝗶𝗻𝗴: Compare two versions of a feature to see which one performs better ⚖️. This is like running a poll to gauge your users' preferences 📊.

🔴𝗗𝗮𝗿𝗸 𝗟𝗮𝘂𝗻𝗰𝗵𝗲𝘀: Release new features to a select group of users without any fanfare 🤫. This is like testing out a new outfit before you wear it in public.


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🔥 Netflix Backend Architecture 🔥


Netflix Backend architecture involves various components and considerations to ensure scalability, reliability, and performance.

Below is a high-level overview of the system architecture:

➡️ Client: The client could be a web browser, a mobile app, a smart TV, or any other device capable of streaming content. Clients communicate with the backend through APIs.

➡️ AWS Elastic Load Balancer (ELB): ELB helps distribute incoming traffic across multiple instances of microservices to ensure load balancing, fault tolerance, and high availability. It can be set up to handle both internal and external traffic.

➡️ API Gateway: An API Gateway acts as a single entry point for clients to interact with various microservices. It can handle tasks such as authentication, authorization, request/response transformations, and more. AWS provides the Amazon API Gateway service for this purpose.

➡️ Microservices Architecture: Netflix relies heavily on microservices to break down its application into small, loosely coupled services that can be developed, deployed, and scaled independently. Examples of microservices in Netflix include user management, content recommendation, billing, and streaming.

➡️ Cache: Caching is essential for improving performance and reducing latency. Services like AWS ElastiCache (for in-memory caching) or Amazon DynamoDB Accelerator (DAX) can be used to cache frequently accessed data.

➡️ Stream Processing Pipelines: Netflix uses stream processing for real-time data analytics and processing. Apache Kafka and Apache Flink are examples of technologies that can be employed to build stream processing pipelines. These pipelines can process events in real-time, such as user interactions and content consumption, to make timely decisions and updates.

➡️ Notification System: A notification system can be implemented to inform users about new content, recommendations, or updates.

➡️ Elasticsearch: Elasticsearch can be employed for efficient and fast search capabilities within the content catalog. It enables users to search for specific titles, genres, or other metadata.

➡️ Spark for Data Processing: Apache Spark can be used for batch processing and large-scale data analytics. It can handle tasks like data cleansing, transformation, and analysis to derive meaningful insights.

➡️ Storage: Netflix likely uses distributed storage systems like Amazon S3 for storing and retrieving large volumes of data, including video content, user profiles, and other assets.

Remember that the specific technologies and services used can vary, and the above components are just a general guideline based on the typical requirements of a large-scale streaming service like Netflix.


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