DevOps & Cloud (AWS, AZURE, GCP) Tech Free Learning

🚨 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

🖥 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

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

😀😀 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!!!

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

🚨 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

🚨 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

🖥 https://cloud.prodevopsguy.xyz/advanced-guide-to-aws-codepipeline-aws-codedeploy-and-aws-codecommit 📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

🖥 https://blog.prodevopsguy.xyz/comprehensive-guide-to-securing-cicd-pipelines-with-azure-devops 📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

🥘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

In real-world projects, Jenkins pipelines play a crucial role in automating software delivery. Here are the two main types of Jenkins pipelines: 🔢. Scripted Pipeline: Description: Scripted pipelines are more traditional and allow developers to have fine-grained control over the build process. They are coded as Jenkinsfiles using Groovy, which requires some programming knowledge. ➡️Syntax Example:

node {
    stage('Build') {
        // Perform build steps
    }
    stage('Test') {
        // Execute tests
    }
    stage('Deploy') {
        // Deploy artifacts
    }
}

➡️Pros: - Greater flexibility for custom logic. - Full control over each stage. - Ideal for complex workflows. ➡️Cons: - Requires Groovy programming skills. - Less declarative. 🔢. Declarative Pipeline: Description: Declarative pipelines use a YAML-based syntax to define the build process. They are easier to work with and do not require knowledge of Groovy code. Jenkins can automatically validate the syntax of a declarative pipeline. ➡️Syntax Example:

pipeline {
    agent any
    stages {
        stage('Build') {
            steps {
                // Build steps
            }
        }
        stage('Test') {
            steps {
                // Testing tasks
            }
        }
        stage('Deploy') {
            steps {
                // Deployment actions
            }
        }
    }
}

➡️Pros: - Simpler syntax. - Automatic syntax validation. - Ideal for straightforward workflows. ➡️Cons: - Less flexible than scripted pipelines. Choose the pipeline type that best suits your project's needs. Whether you prefer fine-grained control or a more declarative approach, Jenkins pipelines empower you to automate your software delivery process! 🚀🔧 ➡️References: 1. Jenkins Pipeline: Examples, Usage, and Best Practices [1] 2. Jenkins Freestyle vs Pipeline: Which One Should You Use? [2] ➡️Reference links: [1] [2] [3] [4] 📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

☁️ AWS Beginner Guide Series 🌐 https://cloud.prodevopsguy.xyz/aws-iam-a-beginners-guide 📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

🌐 https://cloud.prodevopsguy.xyz/aws-ec2-instances-a-beginners-guide 📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

As a DevOps engineer working with Terraform, you'll find the following essential commands helpful for managing your infrastructure as code (IaC): 1. Initialization: Use terraform init to set up your working directory. This command downloads necessary providers and modules, preparing your environment for further Terraform operations[1][2]. 2. Formatting Code: Ensure your Terraform code follows the HashiCorp Configuration Language (HCL) standards. Run terraform fmt to format your configuration files consistently. You can also use flags like --recursive, --diff, and --check for additional functionality[1]. 3. Validation: Validate your Terraform configuration using terraform validate. This command checks whether your code adheres to the expected syntax and structure[1]. 4. Planning: Generate an execution plan with terraform plan. It shows the changes Terraform will apply to reach the desired state based on your configuration. Review this plan before making any changes[1][2]. 5. Applying Changes: Deploy your infrastructure using terraform apply. This command creates or updates resources based on your configuration. It's crucial for implementing changes[1][2]. 6. Destroying Resources: When you want to tear down resources, use terraform destroy. It removes all the Terraform-managed infrastructure based on your configuration[1][2]. 7. Workspace Management: List your workspaces: terraform workspace list Select a specific workspace: terraform workspace select <workspace_name> Create a new workspace: terraform workspace new <workspace_name> Delete a workspace: terraform workspace delete <workspace_name>[2]

Remember to incorporate these commands into your Terraform workflow to efficiently manage your infrastructure! 🚀⚙️

➡️ Reference links: [1] [2] [3] [4] [5] 📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

📣 New to DevOps? 📣 Here are the most widely used tools in the industry along with their official documentation: ➡️ Source Code Management: 1. Git: https://git-scm.com/docs 2. GitHub: https://docs.github.com/en 3. Bitbucket: https://lnkd.in/dA2PcM_w ➡️ Ticketing Tools: 1. Service Now: https://lnkd.in/d69yubJF 2. Jira: https://lnkd.in/dD_WcXFQ 3. Trello: https://trello.com/guide ➡️ Public Clouds: 1. AWS: https://lnkd.in/dMa9XpMa 2. Azure: https://lnkd.in/dBsJtZHy 3. GCP: https://lnkd.in/d3hmN-Jr ➡️ Containerization and Orchestration Tools: 1. Docker: https://docs.docker.com/ 2. Kubernetes: https://lnkd.in/dZXfQEqW 3. Mesos: https://lnkd.in/dqzvzJhY ➡️ Deployment Tools: 1. Terraform: https://lnkd.in/dM46h2_D 2. Octopus: https://octopus.com/docs 3. Heroku: https://lnkd.in/dCDuwvcj ➡️ Testing Tools: 1. Selenium: https://lnkd.in/dTnFN8bT 2. Cucumber: https://lnkd.in/dpmD4A9C 3. Postman: https://lnkd.in/d3xERi6c ➡️ Build Tools: 1. Maven: https://lnkd.in/dfgBnrZj 2. Gradle: https://lnkd.in/dv6rQczZ 3. Ant: https://lnkd.in/dQgMsgef ➡️ Pipeline Tools: 1. Jenkins: https://lnkd.in/dPmA6-ff 2. TravisCI: https://lnkd.in/dxxFaK_X 3. Argo CD: https://lnkd.in/dK5eXbYi ➡️ Monitoring Tools: 1. Grafana: https://lnkd.in/dX5anVq9 2. Prometheus: https://lnkd.in/ddxjc9bV 🚀 Follow for more DevOps content, tips and tricks, and Hands-On Project Implementation. 🔵 Follow for more: @prodevopsguy

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

⚙️ Terraform with Azure DevOps CI/CD Pipelines 👾 In this article, we will look at how to run Terraform in an Azure DevOps pipeline, step-by-step. We will go from the start of the process showing how to create an Azure DevOps instance and project, how to setup Terraform in Azure DevOps, and how to create Terraform configuration files for the infrastructure and pipelines using YAML, sharing some examples and best practices along the way. 𝑓𝑜𝑟 𝑚𝑜𝑟𝑒 𝑖𝑛𝑓𝑜, 𝑦𝑜𝑢 𝑐𝑎𝑛 𝑐ℎ𝑒𝑐𝑘 𝑡ℎ𝑖𝑠 𝑙𝑖𝑛𝑘: 🖥 https://prodevopsguy.site/terraform-with-azure-devops-ci-cd-pipelines ✈️ 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

➡️🐧 Linux Free Videos 🟩 : ✅Link: https://drive.usercontent.google.com/download?id=1MSo7Iwv0Xwe5bjg5fTcmjnxatULfhfLA&export=download&authuser=0 ❤️ Follow for more: @prodevopsguy // Follow for DevOps DOCs: @devopsdocs