Hanane CHRIF-EL-ASRI

https://caxus.net/ 🚀Terraform and GitLab CI Pipelines: The Ultimate Solution for Infrastructure Management 🚀 1. Total Automation 🤖: With Terraform, you can define your infrastructure as code. This means you can create and manage all your cloud resources automatically and repeatably. 2. Seamless Integration ➡️: Thanks to GitLab CI/CD, every change you make in your code can be automatically reflected in your infrastructure. No more manual deployments prone to errors. 3. Security and Transparency 🔒: All changes in your infrastructure are recorded in your Git repository. This allows for total control and a transparent history of all modifications. 4. Continuous Development 🔄: With GitLab CI Pipelines, you can create pipelines that automatically validate, test, and deploy your Terraform configurations. It has never been easier to ensure that everything works as it should! 5. Guaranteed Scalability 📈: By using these tools, you can quickly scale your infrastructure to deal with traffic spikes or new features. 6. Cost Reduction 💸: By automating infrastructure management, you reduce human errors and optimize resource usage, resulting in lower operating costs. 7. Team Efficiency 🛠️: These tools allow your development and operations teams to work together efficiently, minimizing wait times and improving collaboration. 8. Flexibility and Adaptability 🧩: Adjust and evolve your infrastructure according to business needs without complications, all while using market best practices. 9. Recommended Tools 🛠️: Some tools that can help improve productivity are: VSCode for code editing, Terraform Cloud for remote state management, and Slack for quick and effective communication. At Caxus, we are experts in adopting AWS cloud solutions 🌩️. If you want to optimize your infrastructure using Terraform and GitLab CI Pipelines, contact us and let's take your business to the next level. Contact us by Whatsapp: https://buff.ly/4aSbAWy Contact us today for more information! [email protected] We’d love to discuss how we can save you proyect in the cloud. [email protected] #devops #GitLabCI #aws #automation #terraform #gitlabci #pipelines #caxus #gitlab #DominaTuIndustria #Collaboration #Efficiency #CloudAdoption #Seguridad #Optimizacion #LinkedIn #HerramientasDigitales #AprendizajeContinuo #work #growing #teamwork #creatividad #DevSecOps #machinelearning #security #devsecops #cloud #infrastructure #DataAnalytics #AgileInfrastructure #CloudAdoption #Caxus

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New Post: How to Validate a Docker Compose YAML File

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𝗦𝘁𝗿𝗲𝗮𝗺𝗹𝗶𝗻𝗲 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝘄𝗶𝘁𝗵 𝗧𝗲𝗿𝗿𝗮𝗳𝗼𝗿𝗺 𝗗𝘆𝗻𝗮𝗺𝗶𝗰 𝗠𝗼𝗱𝘂𝗹𝗲𝘀! Picture a world where building infrastructure doesn’t feel like starting from scratch every time. That’s the power of Terraform dynamic modules—a game changer for managing scalable and efficient setups in modern DevOps environments. 🔑 𝗪𝗵𝘆 𝗗𝘆𝗻𝗮𝗺𝗶𝗰 𝗠𝗼𝗱𝘂𝗹𝗲𝘀? Dynamic modules allow you to write reusable, turning repetitive tasks into modular, scalable, and error-free workflows. Whether you’re managing multiple VPCs, security groups, or application stacks, dynamic modules empower teams to: - Save Time: No need to rewrite code for every environment (Dev, Staging, - Prod). - Reduce Errors: Standardize infrastructure to eliminate inconsistencies. - Encourages dry coding: Focus on innovation, not duplication. - Increase Collaboration: Share modules across teams for consistency and efficiency. 💡 𝗥𝗲𝗮𝗹-𝗪𝗼𝗿𝗹𝗱 𝗘𝘅𝗮𝗺𝗽𝗹𝗲: Say you're deploying an Application Load Balancer (ALB). Instead of hardcoding the configuration for every project, a dynamic module can accept inputs like VPC IDs, subnet lists, and security groups—letting you deploy an ALB anywhere with just a few lines of code. Need a change? Update the module, and every instance benefits. In professional environments, where teams manage complex multi-cloud infrastructures, dynamic modules unlock scalability and agility. They’re not just for Terraform enthusiasts, they’re a necessity for modern DevOps workflows. Drop your experiences, lessons, or questions below—I’d love to hear how you’re scaling your infrastructure. 📢 Let’s build smarter, not harder! #Terraform #InfrastructureAsCode #DevOps #CloudEngineering #PlatformEngineering #AWS #Azure #GCP #IAC #CloudComputing #Automation #EngineeringExcellence #TechLeadership

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If you would like to secure your java apps using the Microsoft Identity Platform, check the below samples and tutorials!

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6 𝐘𝐞𝐚𝐫𝐬 𝐢𝐧 𝐃𝐞𝐯𝐎𝐩𝐬: 𝐖𝐡𝐚𝐭 𝐈𝐭 𝐑𝐞𝐚𝐥𝐥𝐲 𝐓𝐚𝐤𝐞𝐬 🤞 If you think it’s all smooth sailing with Kubernetes and Docker, think again…. it’s been a wild ride! Here’s a little insight into what actually happens behind the scenes: 🔻 𝐆𝐞𝐭 𝐂𝐨𝐦𝐟𝐨𝐫𝐭𝐚𝐛𝐥𝐞 𝐰𝐢𝐭𝐡 𝐂𝐡𝐚𝐨𝐬 🤯 Remember when things just worked? Yeah, me neither. The moment you think your CI/CD pipeline is flawless, it breaks somewhere. The secret? 𝘚𝘮𝘪𝘭𝘦 𝘵𝘩𝘳𝘰𝘶𝘨𝘩 𝘵𝘩𝘦 𝘤𝘳𝘢𝘴𝘩𝘦𝘴 🔻 𝐌𝐚𝐬𝐭𝐞𝐫 𝐭𝐡𝐞 𝐀𝐫𝐭 𝐨𝐟 𝐆𝐨𝐨𝐠𝐥𝐞 𝐒𝐞𝐚𝐫𝐜𝐡 🕵️‍♂️ Honestly, half of the job is Googling error messages and hopping Stack Overflow had the answer (Now ChatGpt obvio) 🔻 𝐒𝐩𝐞𝐚𝐤 𝐓𝐰𝐨 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞𝐬 🗣 One for Dev: “𝘐𝘵 𝘸𝘰𝘳𝘬𝘴 𝘰𝘯 𝘮𝘺 𝘮𝘢𝘤𝘩𝘪𝘯𝘦!” And one for Ops: “𝘞𝘩𝘺 𝘪𝘴 𝘵𝘩𝘪𝘴 𝘣𝘳𝘰𝘬𝘦𝘯 𝘢𝘨𝘢𝘪𝘯?” Your job? Translate both and figure out what’s really going on 🔻 𝐄𝐦𝐛𝐫𝐚𝐜𝐞 𝐭𝐡𝐞 𝐈𝐧𝐟𝐢𝐧𝐢𝐭𝐞 𝐓𝐨-𝐃𝐨 𝐋𝐢𝐬𝐭 📋 The backlog? It’s never-ending. And just when you think you're catching up, surprise! New cloud feature, new tool, new something to learn 🔻 𝐉𝐞𝐧𝐤𝐢𝐧𝐬 = 𝐋𝐨𝐯𝐞/𝐇𝐚𝐭𝐞 𝐑𝐞𝐥𝐚𝐭𝐢𝐨𝐧𝐬𝐡𝐢𝐩 🤝 You’ll know Jenkins better than your best friend. You’ll love it, hate it, and occasionally want to throw your laptop out the window because of it. But in the end, it gets the job done… most of the time So yeah, DevOps is fun, challenging, and definitely keeps you on your toes. If you’re up for the ride, buckle up—it’s worth it! 😄 What’s the favorite part of working in your field? Or is it all chaos? #DevOpsLife

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Implementing Azure IaC DevOps for Terraform Project: CI/CD with Azure DevOps 😎 blog by Antoine Fongang on medium As a DevOps Engineer at StipeSoft Company, our goal was to improve the efficiency and reliability of our infrastructure management. Our existing process involved manual configurations and deployments, leading to inconsistencies and delays. To solve these issues, we implemented Infrastructure as Code (IaC) with Terraform and automated our workflows using Azure DevOps. This project streamlined our deployment process, making it faster and more reliable. Project Overview: Objective: The primary objective was to automate the entire lifecycle of our infrastructure deployment, from code validation to resource provisioning, using Azure DevOps and Terraform. This included setting up Continuous Integration (CI) and Continuous Delivery (CD) pipelines, ensuring secure code management, and achieving consistent and repeatable deployments across multiple environments. Azure IaC DevOps with Terraform Key Components: CI/CD Pipelines: Build Pipelines (Continuous Integration): Configured Azure Build Pipelines to automatically trigger on every commit to our GitHub repository. Integrated Terraform validations and automated testing within the build pipeline to ensure that only valid and error-free configurations proceed to the next stage. Release Pipelines (Continuous Delivery): Designed Azure Release Pipelines to deploy validated Terraform configurations to our development, staging, and production environments. Implemented approval gates and notifications to maintain control and visibility over the deployment process. 2. Terraform Configuration Management: Organized Terraform configuration files into a structured directory layout, promoting reusability and maintainability. Managed state files securely using Azure Storage, ensuring accurate tracking of infrastructure changes and preventing conflicts. 3. Azure DevOps Organization Setup: Established an Azure DevOps organization to centralize our project management and collaboration efforts. Utilized Azure Repos for version control, ensuring secure and efficient code collaboration among team members. 4. Infrastructure Deployment Automation: Leveraged Terraform to define and automate the provisioning of Azure resources, enabling quick and consistent environment setups. Adopted Terraform modules and workspaces to handle different environments and resource configurations systematically. 5. GitHub SSH Connection: Set up a secure SSH connection between Azure DevOps and our GitHub repository, ensuring encrypted and authenticated access to our codebase. Challenges and Solutions: Challenge: Ensuring consistency across multiple environments. checkout the blog ---> https://lnkd.in/gVP_WkC6

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New Post: How to Validate a Docker Compose YAML File

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We're thrilled to release Kubernetes Explorer as part of our observability platform. It has powerful new features that enable teams to 𝘂𝗻𝗰𝗼𝘃𝗲𝗿 𝗿𝗼𝗼𝘁 𝗰𝗮𝘂𝘀𝗲𝘀 𝗮𝗻𝗱 𝘀𝗼𝗹𝘃𝗲 𝘁𝗵𝗲𝗺 𝗳𝗮𝘀𝘁𝗲𝗿 𝘁𝗵𝗮𝗻 𝗲𝘃𝗲𝗿 𝗯𝗲𝗳𝗼𝗿𝗲: 👀 Kubernetes Hindsight: Gain historical visibility so teams can conduct retrospective analyses and performance optimizations in ephemeral container environments. 🗺️ Cluster Optimization: View a map of workload distribution across the Kubernetes cluster, enabling rapid identification of underutilized capacity and optimization of resources. 🔁 Resource Descriptors: Achieve comprehensive visibility into full YAML configurations of Kubernetes resources, maintaining deployment descriptor history for easy version comparison. Learn more in our NEW blog post: https://lnkd.in/gw3jnivi #KubernetesExplorer #AI #Kubernetes #observability

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SlimFaas is one of the tools with the strongest Green impact that I know of! Are you using Kubernetes? It can be tested in 5 minutes and will likely reduce your CPU and RAM consumption by five or six times. A small gesture for the planet. #SlimFaas https://lnkd.in/etDaUV4m

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#StarWind_how_to Embark on a journey through #Git submodules in #Azure #DevOps pipelines with our insightful article by Didier Van Hoye for #StarWind. Delve into the challenges faced, solutions discovered, and the path to seamless integration in private repositories. Read more here: https://starwind.com/s/1V

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💡 TipOPS of the day 👨‍💻 👩‍💻 A team created a GKE cluster with 3 nodes (for high availability) to test their applications, if all tests are ok, they can deploy to production cluster with the same GKE configuration. How can we improve this architecture ? 👉 We can create a GKE cluster with only one node with autoscale and use spot VM because it's not a critical environment (this practice will reduce GKE invoice). To optimise cost and resources, a scheduler can be created to shutdow the pods every night (outside office hours) and during the weekend. For production, autoscale is a recommanded practice and choose the most optimised compute engine. If you have another tips about this subject, share it 😄 #cloud #gke #GoogleCloud #kubernetes #architect #devops

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Implementing Azure IaC DevOps for Terraform Project: CI/CD with Azure DevOps 😎 blog by Antoine Fongang on medium As a DevOps Engineer at StipeSoft Company, our goal was to improve the efficiency and reliability of our infrastructure management. Our existing process involved manual configurations and deployments, leading to inconsistencies and delays. To solve these issues, we implemented Infrastructure as Code (IaC) with Terraform and automated our workflows using Azure DevOps. This project streamlined our deployment process, making it faster and more reliable. Project Overview: Objective: The primary objective was to automate the entire lifecycle of our infrastructure deployment, from code validation to resource provisioning, using Azure DevOps and Terraform. This included setting up Continuous Integration (CI) and Continuous Delivery (CD) pipelines, ensuring secure code management, and achieving consistent and repeatable deployments across multiple environments. Azure IaC DevOps with Terraform Key Components: CI/CD Pipelines: Build Pipelines (Continuous Integration): Configured Azure Build Pipelines to automatically trigger on every commit to our GitHub repository. Integrated Terraform validations and automated testing within the build pipeline to ensure that only valid and error-free configurations proceed to the next stage. Release Pipelines (Continuous Delivery): Designed Azure Release Pipelines to deploy validated Terraform configurations to our development, staging, and production environments. Implemented approval gates and notifications to maintain control and visibility over the deployment process. 2. Terraform Configuration Management: Organized Terraform configuration files into a structured directory layout, promoting reusability and maintainability. Managed state files securely using Azure Storage, ensuring accurate tracking of infrastructure changes and preventing conflicts. 3. Azure DevOps Organization Setup: Established an Azure DevOps organization to centralize our project management and collaboration efforts. Utilized Azure Repos for version control, ensuring secure and efficient code collaboration among team members. 4. Infrastructure Deployment Automation: Leveraged Terraform to define and automate the provisioning of Azure resources, enabling quick and consistent environment setups. Adopted Terraform modules and workspaces to handle different environments and resource configurations systematically. 5. GitHub SSH Connection: Set up a secure SSH connection between Azure DevOps and our GitHub repository, ensuring encrypted and authenticated access to our codebase. Challenges and Solutions: Challenge: Ensuring consistency across multiple environments. checkout the blog ---> https://lnkd.in/gVP_WkC6

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#Terraform for managing #MultiEnvironment infrastructure while keeping your code #DRY and organized. Scenario: You’re tasked with deploying infrastructure for three environments: dev, test, and prod. The resources (e.g., EC2 instances, S3 buckets , RDS ) are the same, but configuration values like instance type, AMI, or bucket names differ by environment. Challenge: How can you efficiently reuse the same Terraform configuration across multiple environments (dev, test, prod) without duplicating code? Solution: A solution is to use Terraform modules combined with environment-specific variable files to maintain DRY and modular infrastructure-as-code. Here’s how: Define Terraform Modules: The module will contain the core resource definitions (e.g., EC2 instances, S3 buckets and RDS) and use variables for configurable values. Create Environment-Specific .tfvars Files: Each environment (dev, test, prod) has its own .tfvars file to specify unique values, such as instance type, number of instances, etc. Call the Module in the Root Configuration: The root configuration references the module and passes in variables from the .tfvars files. Apply Configuration: Run the following to specify the environment file: bash terraform apply -var-file="dev.tfvars" This approach allows you to reuse the module for all environments while keeping configurations separate and clean. Example Script: Here’s a quick example: 1. Module Definition (modules/ec2/main.tf) variable "instance_type" {} variable "ami" {} resource "aws_instance" "example" { ami = var.ami instance_type = var.instance_type } 2. Root Configuration (main.tf) module "ec2" { source = "./modules/ec2" instance_type = var.instance_type ami = var.ami } 3. Environment-Specific Variables (e.g., dev.tfvars) instance_type = "t2.micro" ami = "ami-123456" Run terraform apply -var-file="dev.tfvars" to apply the configuration for the dev environment. #DevCommunity #InfraManagement #IAC #SysAdmin #devops #hiring

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We always have recommendations about not to use `:latest` docker tags in our deployments either from teammates during daily work or while navigating documentations, Github issues or forums. But why this matters ? The below blog post will illustrate the importance of avoid using the docker `:latest` tag in our deployments & what alternatives we should adopt. https://lnkd.in/eKm_BKni #devops #docker #containers

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💻 𝐃𝐞𝐯𝐎𝐩𝐬 𝐢𝐬𝐧’𝐭 𝐭𝐡𝐞 𝐟𝐢𝐧𝐢𝐬𝐡 𝐥𝐢𝐧𝐞... 𝐢𝐭 𝐢𝐬 𝐣𝐮𝐬𝐭 𝐭𝐡𝐞 𝐛𝐞𝐠𝐢𝐧𝐧𝐢𝐧𝐠‼️ One of the best things about being a DevOps engineer is that it puts you at the heart of so many crucial aspects of tech: - 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 - 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 - 𝐂𝐈/𝐂𝐃 - 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 DevOps is a 𝐟𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧! If you’re passionate about security, why not dive into 𝐃𝐞𝐯𝐒𝐞𝐜𝐎𝐩𝐬? Evolving threats demand a focus on integrating security seamlessly into the development lifecycle. As a DevOps engineer, you’re already halfway there! Interested in machine learning? The rise of 𝐌𝐋𝐎𝐩𝐬 has shown just how critical it is to operationalise machine learning workflows. Again... As a DevOps engineer you are halfway there! By blending your DevOps expertise with an understanding of ML models and pipelines, you can help bridge the gap between data science and production systems. The point is: DevOps is an amazing 𝐜𝐞𝐧𝐭𝐫𝐚𝐥𝐢𝐬𝐞𝐝 place to start, but your development shouldn’t stop there. The tech landscape is constantly changing. Whether it’s 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬, 𝐬𝐞𝐫𝐯𝐞𝐫𝐥𝐞𝐬𝐬 𝐜𝐨𝐦𝐩𝐮𝐭𝐢𝐧𝐠, or AI-driven monitoring tools, there’s always something new to learn. By evolving your skills, you can carve out a niche that not only excites you but also keeps you in demand. 🚀 So, 𝐝𝐨𝐧’𝐭 𝐬𝐞𝐭𝐭𝐥𝐞.... 𝐄𝐯𝐨𝐥𝐯𝐞. Whether you’re exploring 𝐃𝐞𝐯𝐒𝐞𝐜𝐎𝐩𝐬, 𝐌𝐋𝐎𝐩𝐬, or any other specialisation, remember that the key to long-term success in tech is consistent learning. Being a great DevOps engineer is a huge 𝐦𝐢𝐥𝐞𝐬𝐭𝐨𝐧𝐞! But it’s not the whole journey. What specialisation are you considering? 𝐋𝐞𝐭’𝐬 𝐝𝐢𝐬𝐜𝐮𝐬𝐬 𝐢𝐧 𝐭𝐡𝐞 𝐜𝐨𝐦𝐦𝐞𝐧𝐭𝐬!

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I’m happy to share my first GCP guide on building a Microservices Application on Google Cloud using Terraform and a CI/CD Pipeline! I cover setting up a microservices application on Google Cloud Platform using Terraform for infrastructure and Google Cloud Build & Skaffold for automated deployments. 🛠️ I’d love to hear your feedback! Feel free to share it with anyone who might find it helpful. #GoogleCloud #Terraform #Microservices #CloudArchitecture #DevOps #CICD #GKE #CloudBuild

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