Laurent Vallar

Pulumi ESC's biggest launch yet: Introducing three game-changing features to manage your secrets and configurations: - 𝗩𝗲𝗿𝘀𝗶𝗼𝗻𝗶𝗻𝗴: Track changes, compare versions side by side, roll back to any previous state, tag versions for easy reference, and use tagged versions for controlled rollouts to your environments - 𝗖𝗹𝗶𝗲𝗻𝘁 𝗦𝗗𝗞: Automate your application secrets and configuration management with the new Pulumi ESC SDK for Typescript, Go, and #Python. Seamlessly integrate secrets and configuration into your apps at runtime. - 𝗘𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁𝘀 𝗮𝘀 𝗖𝗼𝗱𝗲 𝘄𝗶𝘁𝗵 𝗜𝗮𝗖: The Pulumi Service Provider and Automation API gives you complete control to manage ESC environments using familiar Infrastructure as Code (IaC) practices—perform CRUD operations, manage access, and add version tags with ease. Explore how these features can elevate secure practices and your development workflows a https://lnkd.in/gJ9k7wQW #DevSecOps #DevOps #SoftwareEngineering

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Deploy a Kafka 3 nodes Cluster in few minutes on OVHcloud multi-regions #multicloud #hybridCloud In this example, we'll deploy the Kafka in cluster Mode (KRaft - Apache Kafka Without ZooKeeper). Here we'll look at how to deploy 4 services with a single YAML file: - 3 controllers and brokers - 1 kafka-ui (web interface)

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Join us on July 23 at 4 pm CEST for our next webinar with kreuzwerker, Automate & Save: Kubernetes Cost Reduction Techniques. We’ll do a live demo and share best practices for optimizing Kubernetes clusters and cutting costs. 💰 You'll learn how to: 💡Automatically optimize Kubernetes clusters and cloud costs  💡Increase CPU and memory usage  💡Monitor resource usage precisely 👉 RVSP today at this link: https://lnkd.in/eBUUUMDf And stay until the end of the webinar when we’ll give away a prize!

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Platform Engineering is hard, because it requires product mentality & business value orientation of Sysadmins & DevOps engineers - very technical roles. Want a proof? Ask any DevOps / Network / Sysadmin Engineer what they do in their work. I guess majority of the answers will be: - "I administer Kubernetes Clusters", - "I create CI/CD pipelines", - "I open network connections". Or even more technical, like "I use terraform to...". Solution-oriented answer, and correct ones - because before Platforms, we didn't expected those people to think differently. Before Platforms - it was enough. What changed is that Platform Engineer first thought and quick answer should be: "I unblock developers by..." / "I improve developers experience". And you won't learn it by "configuring namespaces", because it's not a technical skill. It's a mentality shift. What I worry (and what probably will kill PE as a concept) is that we are going to repeat the failure of SOA. A nice concept around service-orientation across company (one unit serving other unit) we, engineers, killed with large ESB deployments & big products specialisation (webmethods, OSB, Tibco etc) - instead of working on the mentality. Platform Engineering is hard, because it's an IT topic, which cannot be covered by a single tool deployment.

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7 commentaires

Elevate your Kubernetes testing with Playwright and Testkube! 🎭🚀 Learn to run Playwright tests in K8s, visualize results, and streamline your CI/CD pipeline. Perfect for cloud-native e2e testing. Explore now: https://bit.ly/4e75Dq8 #Kubernetes #Playwright #CloudNative #QA

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Are your Application Teams waiting on 𝗬𝗢𝗨 to provision their subscriptions and on-prem connectivity? Why not enable them to manage it themselves? It's time for a change! With #meshStack, your Application Teams can take control of their workflows autonomously, easing the burden on your Platform Team. Empower your teams with an intuitive front end for your #GitOps pipelines, eliminating manual approvals and resource-intensive support. ✨͟ ͟K͟e͟y͟ ͟B͟e͟n͟e͟f͟i͟t͟s͟:͟ 𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝘆: Application teams can deploy services and manage infrastructure effortlessly. 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆: Reduce the workload of the platform team, speeding up operations and lowering costs. 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻: Shift focus from maintenance to building new solutions. Ready to transform your workflow? Connect with us to learn more and see meshStack in action! 👇 https://lnkd.in/eGFCUarV

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Todays #Tip is on #Terraform #DRY #MultiEnvironment #InfraManagement #IAC #Scenario: As a #DevOps engineer, you are tasked with deploying infrastructure for three environments: dev, test and prod. The resources to be created (like EC2 instances, S3 buckets, etc.) are the same for each environment, but the configuration values, such as instance type,ami, or bucket names, differ. #Challenge: How can you efficiently reuse the same Terraform configuration for multiple environments (dev, test, prod) while ensuring that the configuration values (e.g., instance type,ami , bucket names) can be customized for each environment without duplicating code? #Solution One of the solution that will address this challenge is by following the below steps. Here's how it works: 1. Define #TerraformModules: The module will contain resource definitions, such as EC2 instances or S3 buckets. It will be parameterized with variables to handle configurable values (e.g., instance type, bucket name etc). 2. Create Environment-specific #tfvars files: Each environment (dev, test, prod) will have its own `.tfvars` file that defines the environment-specific values (e.g., instance type, number of instances). 3. Call the module in the #root configuration: The root configuration will have the modules with their inputs as variable. 4. When running `terraform apply`, you can specify the appropriate environment configuration file like this: terraform apply -var-file="dev.tfvars" This way, you reuse the same module across multiple environments, while passing environment-specific configurations through variables. It keeps the code DRY and ensures clean, maintainable infrastructure code for all environments.

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🚨 Looking for a powerful alternative to Kafka? ApachePulsar's unique architecture sets it apart in building event-driven applications. Watch Julien Jakubowski 🥑's #OSACon 2023 session and learn about its scalable processing power, exceptional message durability, and comprehensive use case coverage, rivaling #RabbitMQ and #Kafka with a single broker. #opensource https://lnkd.in/gMt72TUr

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By integrating StreamX with #AEM and enabling the Server-Side Includes (SSI) module in #ApacheDispatcher, you get a component that will display content that changes in real time - without ever needing to clear the cache or republish anything. Go to our latest tutorial in the StreamX documentation to learn how to do just that: https://lnkd.in/d-nv-7-h

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The #ApachePaimon PMC officially announces the release of Apache Paimon 0.9.0. This version was developed over the course of four months, with the participation of 80 contributors, resulting in more than 600 commits. Thank you to all contributors for your support! The community has decided that the next version will be 1.0, marking that most functionalities of Apache Paimon have become relatively mature and stable. Version Overview Paimon's long-term plan is to become a unified lake storage format that meets the main requirements for minute level #bigdata: offline batch computing, real-time stream computing, and OLAP computing. Notable changes in this version include: ✔Paimon Branch: The branch functionality is now officially production-ready, and the introduction of the ‘scan.fallback-branch’ feature helps to better unify stream and batch storage for businesses. ✔Universal Format: This version introduces native Iceberg compatibility. You can enable Iceberg compatibility mode, and Paimon will generate Iceberg-compatible snapshots in real-time, allowing you to use the Iceberg ecosystem to read this Paimon table. ✔Caching Catalog: This version introduces the implementation of Caching Catalog by default. Table metadata and manifest files will be cached in the catalog, which can accelerate OLAP query performance. ✔Improvements in Bucketed Append Table Availability: The small file issue has been significantly alleviated, and it can be applied to bucketed joins in Spark, reducing shuffles during joins. ✔Support for DELETE & UPDATE & MERGEINTO in Append Tables: This version introduces support for DELETE, UPDATE, and MERGE INTO in append tables. You can modify and delete records in append tables using Spark SQL, and it also supports Deletion Vectors mode. Read the full release announcement to learn more: https://lnkd.in/gaqrqwfh About Apache Paimon: A lake format that enables building a real-time lakehouse architecture with Flink and Spark for both streaming and batch operations. Innovatively combines lake format and LSM structure, bringing realtime streaming updates into the lake architecture. #BigData #OpenSource #DataEngineering #Streaming

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🚨 As we continue to refine our integration of Ory Corp with NestJS, our latest blog post by Edouard Maleix, focuses on one crucial aspect: configuring external services to make our setup as straightforward and adaptable as possible across all environments— be it self-hosted or cloud-based. 🗃 Reusable Configuration Files: We've introduced a method to create separate template configuration files for Ory Kratos and Ory Keto, which can be easily extended with environment-specific values. 💼 Organized and Accessible: By storing these configurations in an 'infra' directory and using a consistent naming convention for environment variables, we ensure that our setup remains organized and easily manageable. 💡 Flexibility and Efficiency: This approach not only simplifies the initial configuration process but also enhances the flexibility to adjust settings as per the deployment environment, ensuring efficient management across the board. This part of our blog provides practical insights into simplifying complex configurations, helping developers streamline their setup without compromising functionality or security. 🔗 Explore the detailed guide to configuring external services here: https://lnkd.in/dXsvXGqS #NestJS #Ory #CloudComputing #WebDevelopment #DevOps

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I'm definitely not the target audience for #Clio, but I have to say it is surprisingly useful for even a non engineer. Yesterday I had clio deploy #Kubernetes (k3d) on my Mac in Docker. Which basically means I was running a kubernetes distro, in a container, running on a vm on a mac. Not surprisingly Clio handled it really well, it's basically just deploying a container. Then I had it launch a Minecraft VM on my kubernetes cluster. Again, as expected no problem. Clio told me it was up, and even gave me the IP address I needed to access it. This is where things got interesting, I tried connecting to the Minecraft server and the Minecraft client couldn't find it. So I went back to Clio and asked her to help me figure out why it wasn't working. At first she thought it was just a port forwarding issue, but when I explained that I was running it on k3d locally, she realized that it wasn't set up correctly and figured out she needed to update the k3d cluster configuration to map the service port to a port on my host machine. Unfortunately, she then said the only way to update #k3d with the correct port mappings was to delete and recreate the entire cluster. Luckily, I was explaining this to Darren Shepherd and he said that wasn't true, the latest versions of k3d allowed you to modify the cluster without recreating. He suggested I push back on Clio and ask if she could just modify the cluster without restarting it. So I asked, and she remained steadfast and said nope, you need to restart it. Then Darren told me to just ask her "are you sure, google it," and sure enough, Clio went out to the internet, realized k3d had been updated since she was trained on it and, you can modify port mappings of an existing k3d cluster using the `k3d cluster edit` command. And that was it, she asked if she should make the change, I approved it and I was able to get to my Minecraft server. It was genuinely really exciting to see how powerful Clio was, but also how it could help me troubleshoot a relatively complex issue. AI assistants are absolutely no threat to the jobs of $sysadmins, but as a tool, they are amazing.  #ai #devops You can try clio here: https://lnkd.in/ghG-NzVx

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In this episode, we talk with Marvin Beckers from Kubermatic about KCP - a CNCF Sandbox project that provides a horizontally scalable control plane for Kubernetes-like APIs. https://lnkd.in/gez2JWgF

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[BLOG POST SERIES ON CI/CD PIPELINE SECURITY] Third Step: Securing Your Continuous Deployment Pipelines 🛡️🔒 In our latest blog post written in collaboration with Alexandre Couedelo, discover strategies to enhance the security of your delivery pipelines: ✅ The importance of compliance and auditing. ✅ Isolation and restriction of access to target environments. ✅ Digital signatures for artifact deposits. ✅ Imperative vs. declarative deployments: exploring the specific advantages of each. Learn how these practices can improve the security and reliability of your software deliveries. Happy reading. ⬇ #devsecops #security #pipelineascode #continuousdeployment

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🔒 The Lowdown on Locked Namespaces 🔒 ControlPlane’s Senior Consultant Marco De Benedictis gave a talk at KubeCon EU 2024, where he discussed how namespaces have grown from an optional feature to the cornerstone for several Kubernetes security controls and why you should consider them as a security boundary in your cluster 🔗 To read more about this, click the link below to read Marco’s blog piece 👇

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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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Constantly seeking ways to optimize your applications for better performance and stability? 🤔 In his latest blog post, Maciej Korolik explores how implementing a custom retry mechanism can address challenges with app crushes and loading issues, and improve your app's reliability (up to 92% reduction in app crashes!) 💪 🚀 Here's what you'll find inside: 👉 An overview of React.lazy() and its performance benefits 👉Common pitfalls with dynamically loaded modules 👉A detailed guide to creating and using a custom retry mechanism 👉Real-world results and how this fix can enhance your user experience Read the full article now! #ReactJS #WebDevelopment #TechTips #PerformanceOptimization #Coding #SoftwareDevelopment #TechBlog

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