🔥 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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🔥 DevOps Interview Preparation Guide 2023

🔗 Link : https://github.com/NotHarshhaa/into-the-devops/blob/master/prepare_for_interview.md

➡️ How to prepare for DevOps/SRE/Production Engineer interviews?

Detailed Steps are included, Go read it out

🔍 All DevOps Content will be posted here, Fork the Repository


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🚀 𝗖𝗜𝗖𝗗 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝗶𝗻 𝗔𝘇𝘂𝗿𝗲 𝗗𝗲𝘃𝗢𝗽𝘀 🚀

Here we understand the flow of Azure DevOps CI/CD for deploying to Azure Kubernetes Service.

𝟭. 𝗣𝗥 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 (𝗣𝘂𝗹𝗹 𝗥𝗲𝗾𝘂𝗲𝘀𝘁)
🛠️ Fast quality checks: linting, building, and unit testing the code.
😀 Failed checks prevent PR merge.
✅ Successful run results in PR merge.

𝟮. 𝗖𝗜 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 (𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻)
🔄 Runs tasks from PR pipeline + integration tests.
🔒 Accesses secrets from Azure Key Vault.
📦 Creates & publishes container image in non-production Azure Container Repository.

𝟯. 𝗖𝗗 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗧𝗿𝗶𝗴𝗴𝗲𝗿𝗲𝗱
🚀 Completion of CI pipeline triggers CD pipeline.

𝟰. 𝗦𝘁𝗮𝗴𝗶𝗻𝗴 𝗘𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁
📝 Deploys YAML template to staging AKS environment.
✅ Performs acceptance tests on the staging environment.
⚙️ Manual validation task (optional).

𝟱. 𝗖𝗗 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 - 𝗠𝗮𝗻𝘂𝗮𝗹 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻
👤 Manual validation step to validate deployment.
🎙 Manual intervention resumes the pipeline.

𝟲. 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁
🚀 Promotes image to production Azure Container Registry.
🚢 Deploys YAML template to production AKS environment.

𝟳. 𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 & 𝗔𝘇𝘂𝗿𝗲 𝗠𝗼𝗻𝗶𝘁𝗼𝗿
📊 Container Insights forwards performance metrics to Azure Monitor.
📈 Azure Monitor collects observability data - logs, metrics, health, and performance.

𝟴. 𝗞𝗲𝘆 𝗖𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁𝘀
📦 Container Registry: Stores private container images.
🛠️ AKS: Managed Kubernetes service by Azure.
🔒 Azure Key Vault: Manages secrets for pipelines.
🔍 Defender for DevOps: Performs static analysis, enhances security visibility across AKS pipelines.

The workflow integrates various stages ensuring code quality, testing, and secure deployments across non-production and production environments in Azure DevOps. Container Insights, Azure Monitor, and Defender for DevOps enhance monitoring, observability, and security within the CI/CD pipeline.


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🔴 On Kubernetes platforms, traffic may come from an internal source (between workloads within the cluster), or an 𝗲𝘅𝘁𝗲𝗿𝗻𝗮𝗹 𝘀𝗼𝘂𝗿𝗰𝗲 (from an outside client to a workload in the cluster). List all objects 𝗶𝗻𝘃𝗼𝗹𝘃𝗲𝗱 𝗶𝗻 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝘁𝗿𝗮𝗳𝗳𝗶𝗰 𝗿𝗼𝘂𝘁𝗶𝗻𝗴:

✅ External Load Balancer - Distribute external traffic
✅ Ingress Controller - Responsible for implementing these rules
✅ Ingress - Incoming traffic to the pod
✅ Service - Exposing a network application
✅ Pod - Collection of one or more containers

🔴 HTTP is a protocol that enables data transmission via the world wide web, HTTPS is essentially a 𝗺𝗼𝗿𝗲 𝘀𝗲𝗰𝘂𝗿𝗲 𝘃𝗲𝗿𝘀𝗶𝗼𝗻.

🔴 SSL & TLS are the same. SSL is the old name. TLS is the 𝐮𝐩𝐝𝐚𝐭𝐞𝐝 𝐯𝐞𝐫𝐬𝐢𝐨𝐧 𝐨𝐟 𝐒𝐒𝐋.

🔴 The basic requirement for ingress TLS is a 𝗧𝗟𝗦/𝗦𝗦𝗟 𝗰𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗲. You can obtain these certificates in the following ways.

☑️ Self-Signed Certificates
☑️ Purchase an SSL Certificate
☑️ Use Letsencrpt Certificate - Non trusted certificate

𝗧𝘆𝗽𝗲𝘀 𝗼𝗳 𝗜𝗻𝗴𝗿𝗲𝘀𝘀
☑️ Single service Ingress ➡️ All traffic is routed to a single default backend.
☑️ Simple fanout Ingress ➡️ Sends traffic from a single IP address to multiple Services depending on the requested HTTP.
☑️ Name-based virtual hosting ➡️ Support steering HTTP traffic to various hostnames at a similar IP address.

🔴 A Kubernetes Secret is an object that contains a 𝘀𝗺𝗮𝗹𝗹 𝗮𝗺𝗼𝘂𝗻𝘁 𝗼𝗳 𝘀𝗲𝗻𝘀𝗶𝘁𝗶𝘃𝗲 𝗱𝗮𝘁𝗮 such as a password, a token, or a key.

Creating From Yaml File

𝗮𝗽𝗶𝗩𝗲𝗿𝘀𝗶𝗼𝗻: 𝘃𝟭
𝗸𝗶𝗻𝗱: 𝗦𝗲𝗰𝗿𝗲𝘁
𝗺𝗲𝘁𝗮𝗱𝗮𝘁𝗮:
𝗻𝗮𝗺𝗲: 𝘀𝗲𝗰𝗿𝗲𝘁-𝗱𝗼𝗰𝗸𝗲𝗿𝗰𝗳𝗴
𝘁𝘆𝗽𝗲: 𝗸𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀.𝗶𝗼/𝗱𝗼𝗰𝗸𝗲𝗿𝗰𝗳𝗴
𝗱𝗮𝘁𝗮:
𝗽𝗮𝘀𝘀𝘄𝗼𝗿𝗱: <𝗨𝘀𝗲𝗿 𝗣𝗮𝘀𝘀𝘄𝗼𝗿𝗱>
𝘂𝘀𝗲𝗿𝗻𝗮𝗺𝗲: <𝗨𝘀𝗲𝗿 𝗡𝗮𝗺𝗲>

Creating the Secret
𝗸𝘂𝗯𝗲𝗰𝘁𝗹 𝗰𝗿𝗲𝗮𝘁𝗲 –𝗳 𝗦𝗲𝗰𝗿𝗲𝘁.𝘆𝗮𝗺𝗹

🔴 When you create a secret, it needs to be referenced by the pod that will use it. To make a secret available for a pod.
✔️ Mount the secret as a file in a volume available to any number of containers in a pod.
✔️ Import the secret as an environment variable to a container.

𝗧𝘆𝗽𝗲𝘀 𝗼𝗳 𝗦𝗲𝗰𝗿𝗲𝘁

Opaque ➡️ arbitrary user-defined data
https://lnkd.in/gXcUF7cD ➡️ ServiceAccount token
kubernetes.io/dockercfg ➡️ serialized ~/.dockercfg file
https://lnkd.in/gmF_-H56 ➡️ serialized ~/.docker/config.json file
kubernetes.io/tls ➡️ data for a TLS client or server


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🚀 Jenkins, Maven, Gradle, and CI/CD Pipelines 🚀

Are you ready to elevate your development process to new heights? 🚀 Embrace the power of Jenkins, Maven, Gradle, and CI/CD pipelines for a seamless DevOps experience! 🛠️🌟

🛠 Jenkins: Your ultimate automation hub! Streamline your workflows, automate repetitive tasks, and enhance collaboration across your development teams. Jenkins is the heartbeat of DevOps, orchestrating the entire software delivery process. 🔄💼

📦 Maven and Gradle: The dynamic duo of build automation! 🚀 Maven simplifies project management and dependency resolution, while Gradle empowers you with a flexible, customizable build system. Whether you're a Maven enthusiast or a Gradle aficionado, these tools are your go-to for efficient project builds. 🏗️🔨

🔄 CI/CD Pipelines: Accelerate your delivery pipeline and achieve continuous integration and continuous deployment with CI/CD pipelines. 🚚💨 Enhance collaboration, reduce errors, and deliver high-quality software at the speed of DevOps. Your code goes from development to production seamlessly, ensuring a smooth and efficient release process. 🌐⚙️

🌟 DevOps Magic: Unleash the magic of DevOps to foster collaboration, automate processes, and deliver value to your users faster than ever! 🚀✨ Embrace a culture of continuous improvement and innovation. With Jenkins, Maven, Gradle, and CI/CD pipelines, your DevOps journey is set to reach new heights! 📈🚀

🛡 Tool Integration: Seamlessly integrate these powerful tools into your DevOps toolchain. Whether you're building Java applications, managing dependencies, or automating deployment, this arsenal of tools ensures a cohesive and efficient development process. 🔗🔄

🌐 Join the DevOps Revolution!: Elevate your development game with Jenkins, Maven, Gradle, and CI/CD pipelines. 🚀 Embrace efficiency, collaboration, and innovation. Your DevOps journey starts now! 💼🖥🚀


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🔥 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