Damien Metzler

Remember back in 2012, when PostgreSQL introduced JSON support ? https://lnkd.in/e_Qb8rpc Now in PostgreSQL 17 we have JSON_TABLE and new JSON functions !

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👀 Looking for an instructor-led and in-person Kubernetes #training in Europe 🇪🇺? Then don’t miss this opportunity: Kubernetes is the leading technology for hosting containerized workloads. Along with other Cloud Native projects, it enables you to deliver applications to your customers securely and reliably - at an extremely fast pace and low cost! That is, of course, with the assumption that your engineering team has the necessary knowledge and skills to use these tools according to best practices. However, learning Kubernetes and other Cloud Native tools on your own and along the way, while designing and implementing production-grade application solutions, may be a challenging and stressful experience. To make the learning process efficient, effective and enjoyable, we at Elastisys, offer Kubernetes training and certification packages, suitable for application developers, Cloud Native solution architects, as well as DevOps and Cloud Security experts. As the Linux Foundation Authorized Instructor, I am teaching all of the official Kubernetes courses: ➡️ LFS458: Kubernetes Administration ➡️ LFD459: Kubernetes for App Developers ➡️ LFS460: Kubernetes Security Fundamentals If you are looking for training in Kubernetes or other Cloud Native technologies: 🔝 𝗘𝗡𝗥𝗢𝗟 today in the course that best suits your needs (link on the top of my profile) ___ My name is Jakub Krzywda, PhD. I post about: #kubernetes, #cloudnative technologies and #devops practices. #K8sWithK5a 𝗖𝗟𝗜𝗖𝗞 my name + 𝗙𝗢𝗟𝗟𝗢𝗪 + 🔔 so you don’t miss my next posts! 𝗟𝗜𝗞𝗘 👍 to support | 𝗖𝗢𝗠𝗠𝗘𝗡𝗧 💬 to add your perspective | 𝗥𝗘𝗣𝗢𝗦𝗧 ♻️ to share with your network

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To all the AWS Admins in my network. Read the article below regarding the Python Package Index (PyPI) named “fabrice,” which has been stealthily exfiltrating developers’ Amazon Web Services (AWS) credentials for over three years. This package is a typosquat of the popular “fabric” library, designed to execute shell commands remotely over SSH. The malicious “fabrice” package has been downloaded over 37,100 times since its release in March 2021. It exploits the trust associated with “fabric” by incorporating payloads that steal credentials, create backdoors, and execute platform-specific scripts. Cybersecurity researchers have identified a malicious Linux systems download that executes shell scripts from an external server, while on Windows, it runs a Visual Basic Script and a Python script to execute further commands and download malicious executables. The primary goal of “fabrice” is to steal AWS access and secret keys using the Boto3 AWS SDK for Python, exfiltrating this sensitive information back to the attacker’s server. This sophisticated typosquatting attack highlights the importance of vigilance when downloading and using software packages. #cybersecurity #usda #AWS #python #dynamotechnologies #alphaomega #cvp #vknowit

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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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👋 Hey ! Have you ever wondered whether you should use Docker images or Zip files for your AWS Lambda function? Hope this last article will help you 😉

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💲𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐅𝐢𝐧𝐎𝐩𝐬: 𝐀 𝐆𝐮𝐢𝐝𝐞 𝐟𝐨𝐫 𝟐𝟎𝟐𝟒 ✦✦ ▓▓▓▓▓▓▓▓▓▓▓ https://lnkd.in/gR6fFaHw ▓▓▓▓▓▓▓▓▓▓▓▓▓▓ Explore how Kubernetes and FinOps come together to optimize costs in a cloud-native environment in 2024. This guide helps you maximize the efficiency of your Kubernetes infrastructure while proactively managing cloud expenses. Whether you're a DevOps engineer or an IT finance leader, learn the tools and best practices for optimized resource management and cost reduction with Kubernetes FinOps.

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🚀 Mastering Terraform: How to Use the for Expression to Filter and Group Instances In my latest article, I walk through some practical examples of how to use the for expression to: 1️⃣ Filter Instances Based on OS Type Easily separate Linux and Windows instances from a map of objects. 2️⃣ Group Instances by Instance Type Dynamically group EC2 instances by type (e.g., t3.micro, m5.large), making it easier to manage large-scale environments. 🔍 Whether you're new to Terraform or an experienced DevOps engineer, these tips will help you get more out of Terraform's declarative approach to infrastructure management. Check out the full post here and learn how to apply the for expression in your Terraform scripts to create cleaner, more organized configurations. 💻👇 https://lnkd.in/dJErgMRZ #Terraform #DevOps #InfrastructureAsCode #IaC #Automation #aws

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𝟏𝟐 𝐄𝐬𝐬𝐞𝐧𝐭𝐢𝐚𝐥 𝐌𝐢𝐜𝐫𝐨𝐬𝐞𝐫𝐯𝐢𝐜𝐞𝐬 𝐁𝐞𝐬𝐭 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞𝐬 𝐟𝐨𝐫 𝐒𝐜𝐚𝐥𝐚𝐛𝐥𝐞 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞𝐬 ✦ ✧✦ ✧✦ ✧✦ ✧✦ ✧✦ ✧✦ ✧✦ ✧✦ ✧✦ ✧✦ ✧✦ ✧✦ ✧✦ ✧ 🚀 Elevate your microservices approach with these foundational strategies: 1️⃣ 𝐃𝐨𝐜𝐤𝐞𝐫 Orchestrate containers seamlessly with Docker Daemon and a registry for storing images, simplifying deployment. 2️⃣ 𝐂𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫 𝐎𝐫𝐜𝐡𝐞𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧 Deploy and manage applications with orchestration tools like Kubernetes, allowing for robust multi-node management. 3️⃣ 𝐂𝐚𝐜𝐡𝐢𝐧𝐠 Boost performance with distributed caching, reducing load on your databases by storing frequently accessed data. 4️⃣ 𝐒𝐢𝐧𝐠𝐥𝐞 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 Centralized DB access keeps data consistent but may introduce bottlenecks if not managed effectively. 5️⃣ 𝐃𝐢𝐬𝐭𝐫𝐢𝐛𝐮𝐭𝐞𝐝 𝐓𝐫𝐚𝐜𝐢𝐧𝐠 Track requests across services, helping with troubleshooting and monitoring in a microservices landscape. 6️⃣ 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 & 𝐓𝐫𝐚𝐜𝐢𝐧𝐠 Achieve full visibility across your tech stack, ensuring effective performance monitoring and early issue detection. 7️⃣ 𝐂𝐞𝐧𝐭𝐫𝐚𝐥𝐢𝐳𝐞𝐝 𝐋𝐨𝐠𝐠𝐢𝐧𝐠 Gather logs from all microservices in one place to streamline troubleshooting and analysis. 8️⃣ 𝐄𝐯𝐞𝐧𝐭 𝐁𝐮𝐬 Facilitate asynchronous, event-driven communication between services, enhancing decoupling and responsiveness. 9️⃣ 𝐒𝐞𝐫𝐯𝐢𝐜𝐞 𝐃𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲 Automate inter-service connections with a service registry and load balancer, ensuring smooth service interaction. 🔟 𝐋𝐨𝐚𝐝 𝐁𝐚𝐥𝐚𝐧𝐜𝐢𝐧𝐠 Distribute incoming requests evenly, optimizing scalability and resilience. 1️⃣1️⃣ 𝐀𝐏𝐈 𝐆𝐚𝐭𝐞𝐰𝐚𝐲 Simplify client access with a unified entry point that handles routing, authentication, and rate limiting. 1️⃣2️⃣ 𝐂𝐥𝐨𝐮𝐝 𝐏𝐫𝐨𝐯𝐢𝐝𝐞𝐫 Leverage cloud-hosted infrastructure for on-demand scalability and flexibility. ✦ ✧✦ ✧✦ ✧✦ ✧✦ ✧✦ ✧✦ ✧✦ ✧✦ ✧✦ ✧✦ ✧✦ ✧✦ ✧✦ ✧ #Microservices #BestPractices #Docker #Kubernetes #Caching #ContainerOrchestration #DistributedTracing #Monitoring #Logging #EventDrivenArchitecture #ServiceDiscovery #LoadBalancing #APIGateway #CloudComputing #DevOps

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This is for REALLY advanced Airflow users The presentation is impressive👇 My friend Philippe Gagnon did a talk about the Airflow Scheduler. This kind of insight is impossible to find anywhere else. Here are the key takeaways 🔑: ➡️ The main scheduler loop is where everything happens (initialization of loop timers, which are intervals of time performing maintenance operations on the objects the scheduler works with - task instances, datasets, etc / executor and task instances heartbeats). ➡️ max_tis_per_query has a large impact on scheduler performance (default 16). Large values will cause each iteration of the scheduling loop to take longer (slowing the queuing process) but they will perform more work. ➡️ Task instances are selected among running DAG runs and ordered by priority weight, which is a global value that spans all currently running DAG runs. ➡️ Task scheduling priority is decoupled from DAG run scheduling priority (because of priority weight). Priority weight is calculated according to a weight rule. ➡️ Default weight rule is "downstream." The task's effective weight is the aggregate sum of all downstream descendants. Therefore, the structure of a DAG impacts task scheduling priority. For example, DAG A is a very deep DAG (one after the other) that coexists with DAG B (only three tasks in parallel at the top), which is a very shallow DAG. If DAG A is scheduled very aggressively, it's possible that task instances in DAG B will never be scheduled depending on max_tis_per_query. That can make you think DAG B is starved whereas it's not. and more! If you're interested in understanding the intrinsic details of the Airflow scheduler, go to the official Apache Airflow YouTube channel. Enjoy ❤️ #airflow #apacheairflow #dataengineering #dataengineer

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⚡ Another great announcement: 𝐃𝐞𝐟𝐞𝐧𝐝𝐞𝐫 𝐟𝐨𝐫 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞𝐬 (in 𝐃𝐞𝐟𝐞𝐧𝐝𝐞𝐫 𝐟𝐨𝐫 𝐂𝐥𝐨𝐮𝐝) now also protects the following open source relational databases running in 𝐀𝐖𝐒: 𝐀𝐮𝐫𝐨𝐫𝐚 𝐏𝐨𝐬𝐭𝐠𝐫𝐞𝐒𝐐𝐋, 𝐀𝐮𝐫𝐨𝐫𝐚 𝐌𝐲𝐒𝐐𝐋, 𝐏𝐨𝐬𝐭𝐠𝐫𝐞𝐒𝐐𝐋, 𝐌𝐲𝐒𝐐𝐋 and 𝐌𝐚𝐫𝐢𝐚𝐃𝐁. This is now in public preview 𝘢𝘵 𝘯𝘰 𝘤𝘰𝘴𝘵! What you get: ▶ 𝑨𝒏𝒐𝒎𝒂𝒍𝒐𝒖𝒔 𝒅𝒂𝒕𝒂𝒃𝒂𝒔𝒆 𝒂𝒄𝒄𝒆𝒔𝒔 𝒂𝒏𝒅 𝒒𝒖𝒆𝒓𝒚 𝒑𝒂𝒕𝒕𝒆𝒓𝒏𝒔 - For example, a logon from a suspicious location or from a domain not seen in the past 60 days. ▶ 𝑺𝒖𝒔𝒑𝒊𝒄𝒊𝒐𝒖𝒔 𝒅𝒂𝒕𝒂𝒃𝒂𝒔𝒆 𝒂𝒄𝒕𝒊𝒗𝒊𝒕𝒊𝒆𝒔 - For example, a user accessing a database service from a breached computer which communicated with a crypto-mining C&C server. ▶ 𝑩𝒓𝒖𝒕𝒆-𝒇𝒐𝒓𝒄𝒆 𝒂𝒕𝒕𝒂𝒄𝒌𝒔, with the ability to separate simple brute force attempt from a successful brute force. ▶ 𝑺𝒆𝒏𝒔𝒊𝒕𝒊𝒗𝒆 𝒅𝒂𝒕𝒂 𝒅𝒊𝒔𝒄𝒐𝒗𝒆𝒓𝒚 within your open source relational DBs in AWS RDS. Try it now! #DefenderForDatabases #MicrosoftDefenderForCloud #AWS #AuroraPostgreSQL #AuroraMySQL #PostgreSQL #MySQL #MariaDB

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Performance-wise, the new protocol has reduced dataplane latency by 11% on average, and by 17.4% at the P90 mark. In addition to making SQS itself more performant, this change benefits services that build on SQS as well. For example, messages sent through Amazon Simple Notification Service (Amazon SNS) now spend 10% less time “inside” before being delivered. Finally, due to the protocol change, the existing fleet of SQS hosts (a mix of X86 and Graviton-powered instances) can now handle 17.8% more requests than before. #AWS #AmazonWebServices #AWSBlogs #Cloud #CloudComputing #Serverless #SQS

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📢 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐞𝐝 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐀𝐝𝐦𝐢𝐧𝐢𝐬𝐭𝐫𝐚𝐭𝐨𝐫 (𝐂𝐊𝐀) 𝐄𝐱𝐚𝐦 𝐔𝐩𝐝𝐚𝐭𝐞𝐬 𝐂𝐨𝐦𝐢𝐧𝐠 𝐒𝐨𝐨𝐧!🚀 ✦✦✦✦✦✦✦✦✦✦✦✦ https://lnkd.in/dkWBqV3D ✪✪ For more details, check out the official update here: https://lnkd.in/duKd69ai ✦✦✦✦✦✦ The CKA exam will be refreshed in the coming months to keep up with the latest industry standards and skills. These updates will ensure that certified professionals continue to meet the demands of the evolving Kubernetes landscape. 🗓 Important: The changes won’t take effect before November 25, 2024, so there's still time to prepare under the current format. Stay tuned for more details and keep sharpening those Kubernetes skills! 🔥 ✦✦✦✦✦✦✦✦✦✦✦✦✦ #Kubernetes #CKA #CertifiedKubernetesAdministrator #DevOps #CloudComputing #TechUpdates #ExamPrep #Certification #K8s

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How to Manage 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐰𝐢𝐭𝐡 𝐀𝐧𝐬𝐢𝐛𝐥𝐞[Tutorial] ☰☰☰☰☰☰☰☰☰☰☰☰☰☰ https://lnkd.in/d4X8q4-Z ☰☰☰☰ #Kubernetes #Management #DevOps #Containerization #CloudNative #ContainerOrchestration #InfrastructureAsCode #Automation #Scalability

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⚜ 𝐄𝐱𝐩𝐥𝐨𝐫𝐞 𝐭𝐡𝐞 𝐩𝐨𝐰𝐞𝐫 𝐨𝐟 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐰𝐢𝐭𝐡 𝐆𝐢𝐭𝐎𝐩𝐬! ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● "GitOps Cookbook - Kubernetes Automation in Practice" is the ultimate guide for implementing #GitOps workflows effectively. This practical book provides step-by-step examples and real-world scenarios to help you master #Kubernetes #automation, streamline #CI / #CD pipelines, and simplify #cluster #management. A must-read for #DevOps enthusiasts and #Kubernetes professionals looking to take #automation to the next level. 🔥 Start automating smarter, faster, and more efficiently with GitOps! ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● #GitOps #Kubernetes #DevOps #Automation #CloudNative #InfrastructureAsCode #CI_CD #TechBooks #K8s #KubernetesAutomation #DevOpsPractices #CloudComputing #TechLearning #ITProfessionals #ContinuousDeployment

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