Emeric Tabakhoff

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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🔧 Fantastic session on Kubectl plugins by Aurélie Vache (OVHcloud) & 👩‍💻 Gaëlle Acas (Doctolib) at #KubeCon! Want to supercharge your kubectl experience? Here's how to create & share custom plugins in minutes: 🎯 Key Takeaways: • Create plugins in Bash or Go to simplify complex kubectl commands • Use Krew as your plugin package manager • Share plugins globally or within your organization • Implement help messages for better user experience • Leverage private indices for team-specific plugins 💡 Pro Tips: • Go is recommended for production plugins (easy binary generation & CI/CD) • Focus on solving real productivity pain points • Use meaningful naming conventions • Include clear documentation • Test across multiple platforms 🛠️ Tools Highlighted: • Krew - The kubectl plugin manager • Example plugins: view-secret, each • Private plugin indices for enterprise use Ready to build your first kubectl plugin? Watch the full demo: https://lnkd.in/gJrE7SRy #Kubernetes #DevOps #CloudNative #CNCF #K8s #CloudComputing

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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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https://caxus.net/ Discover the Advantages of Using Terraform in your Organization 🌟 Do you want to improve the way you manage your infrastructure? Terraform is the perfect tool for you. Here's why: 1. Infrastructure as Code ✍️: Define all your infrastructure in a codified way. This allows you to easily reproduce and version your configurations. 2. Assured Consistency 🔄: By having your configurations in code, you ensure that each change is consistent and tested before being applied in production. 3. Rapid Deployment 🚀: Implement resources in minutes. Goodbye to long and manual processes. 4. Improved Collaboration 🤝: Your entire team can work on the same configuration and see changes in real time, improving coordination and reducing errors. 5. Automatic Scalability 📈: With Terraform, you can adjust your infrastructure as your needs grow, without complications. 6. Multi-Cloud Support ☁️☁️: Manage resources across multiple cloud providers from one place. AWS, Azure, Google Cloud? No problem! 7. Audit and Control 🔍: All changes are logged, making auditing easier and improving the security of your infrastructure. 8. Cost Reduction 💰: Optimize your resource usage by automating creation and management, reducing waste and costs. 9. Simulation and Testing 🧪: With Terraform, you can anticipate how changes will affect before applying them, avoiding unpleasant surprises. 10. Efficiency and Productivity 🛠️: Tools like Terraform Cloud for centralized management, VSCode for coding, and DataDog for monitoring can significantly increase your team's productivity. At Caxus, we specialize in helping you adopt AWS cloud solutions in the most effective way possible. Don't hesitate to contact us to make your transition to Terraform a total success. 🌐✨ 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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🚨 A recently discovered malicious package, "fabrice," exploited the trust in the popular "fabric" SSH library on PyPI, designed to steal AWS credentials from developers. With over 37,000 downloads since 2021, fabrice mimics the trusted "fabric" library, used by millions, to exfiltrate sensitive credentials and create backdoors using platform-specific payloads for Linux and Windows systems. On Linux, fabrice employs the linuxThread() function, which downloads, decodes and executes scripts stored in hidden directories. It begins by creating a concealed folder, ~/.local/bin/vscode, where the malicious scripts are saved. The server URL it contacts is obfuscated and points to a VPN endpoint at "89.44.9.227," masking its activity. The function’s malicious process involves: - Creating hidden directories to host downloaded scripts, making detection difficult. - Downloading malicious code, parsing it into multiple parts and storing each as a separate shell script. - Executing these scripts with elevated permissions, establishing a foothold on the compromised system and enabling further attacks. On Windows, fabrice uses winThread() with two encoded payloads, vv and zz, to establish persistence and remote command execution: - The vv variable decodes into a VBScript (p.vbs) that initiates a hidden Python script (d.py) in the Downloads folder. This VBScript enables d.py to run discreetly, launching further payloads as needed. - The zz variable decodes into a Python script that downloads an additional executable file (chrome.exe) from the attacker's server and saves it in the Downloads folder. It sets up a scheduled task to execute every 15 minutes, ensuring ongoing control. Finally, zz removes the initial d.py, concealing evidence of its actions. The main objective of fabrice is to steal AWS credentials using the boto3 library, which it uses to gather and exfiltrate AWS access and secret keys to the attacker's server: - The malware initiates a boto3 session to gather AWS credentials stored in the environment. - These credentials are then sent to the attacker’s server, which, by using a VPN endpoint, masks the location of the attackers while giving them access to sensitive cloud resources. - The test() function in fabrice adapts to the operating system, launching either the Linux or Windows thread based on the detected platform. This cross-platform approach broadens fabrice’s reach, impacting both Linux and Windows users. To guard against such threats: - Update and thoroughly audit dependencies, focus on high-risk typosquatted names. - Utilize security tools to monitor repositories for potentially harmful dependencies. - Apply strict credential management and access controls, safeguard sensitive information like AWS keys. - Enable Multi-Factor Authentication (MFA). The fabrice package has since been removed from PyPI. Stay vigilant! Source: https://lnkd.in/daCRfszx

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📡 Open Collaboration: OpenProject + GitLab Integrate A new article on the OpenProject #GitLab integration has been published on OpenSource.net, supported by the Open Source Initiative (OSI). The article tells the open source success story of how Community contributor Benjamin Tey created a GitLab plugin for OpenProject out of his own need. And how – due to immense demand – this plugin was recently integrated into the OpenProject core. We are very happy and proud of our amazing open source Community. Only together we can achieve great things. 💙 https://lnkd.in/dyc28x8K

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New Post: How to Validate a Docker Compose YAML File

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Terraform 🌍 What It Is: Terraform is a tool for provisioning and managing cloud infrastructure using code. It allows you to define resources and infrastructure in a declarative manner. Key Features: Declarative Language 📝: Define the desired state of your infrastructure, and Terraform figures out the details. State Management 📊: Keeps track of your infrastructure’s state with a state file. Provider Support ☁️: Works with many cloud providers and services (AWS, Azure, GCP, etc.). Modularization 🧩: Create reusable modules to organize and share configurations. Use Cases: Provisioning cloud resources (e.g., VMs, networks, databases). Managing complex infrastructure setups. Ensuring consistency across multiple environments. Ansible ⚙️ What It Is: Ansible is an automation tool for configuration management and application deployment, using YAML for defining tasks. Key Features: Declarative Language 📝: Describe what you want to achieve, and Ansible does the work. Agentless 🚫: Uses SSH to communicate with target machines, no need for agents. Playbooks 📜: YAML files that describe the tasks and configurations. Extensibility 🔌: Supports a wide range of modules and plugins for different tasks. Use Cases: Configuring servers and applications (installing software, updating settings). Orchestrating multi-step workflows and deployments. Managing system state and enforcing compliance. Integrating Terraform and Ansible 🤝 Terraform 🌍 handles provisioning infrastructure (e.g., creating VMs, networks). Ansible ⚙️ configures the provisioned infrastructure (e.g., installing software, setting up services). Workflow Example: Terraform 🌍: Define and provision the infrastructure. Ansible ⚙️: Configure and deploy applications on the provisioned infrastructure. By using Terraform and Ansible together, you get the best of both worlds: efficient infrastructure provisioning and detailed configuration management.

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Your contribution for the evening 🌟: Griptape👇 Co-founded by Kyle Roche and Vasily Vasinov, Griptape is a modular open source framework that allows developers to build and deploy LLM-based agents, pipelines, and workflows. Here’s why you should contribute to this repo: 1️⃣ With over 1,500 stars, contributing to Griptape means you can gain exposure and hands-on experience with LLMs and modular framework design, enhancing your skills in highly sought-after areas. You will also join the Griptape community, which allows you to connect with like-minded developers and experts in the field, expanding your professional network and potentially opening doors to new opportunities and collaborations! 💪 2️⃣ The repo is more accessible. At Quira, we rank Developers by their DevRank (more on this here: https://lnkd.in/eNtrs97F). We found that the median developer working on the repo belongs to the 90th percentile of GitHub developers. For reference, many of the open source companies we reported on have had a median contributor level of ~95th percentile. This means that you have a real opportunity to make an impact. ⚡️ 3️⃣ Returning contributors are a good proxy for the health of a repo and your chances to make a meaningful impact. Impressively, close to 60% of contributors merge a second pull request. This means that if you enjoyed contributing the first time, chances are you'll come back for more. 😉 You can check more of their open-source stats on Quira (https://lnkd.in/eguqtcWD) or access the GitHub page: https://lnkd.in/gPRRfAi2 📖

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If you are stuck using a Kafka client based on a non-recent version of Apache Kafka, there are many reasons why you should consider upgrading, including: ➤ Greater compatibility and support ➤ Critical bug fixes and security patches ➤ Improved performance ➤ Exciting new features ➤ Reliable long-term maintenance In his new Medium post, Gilles Philippart shows you exactly what you're missing—version by version! Read it here ➡️ https://cnfl.io/3M2YZVi

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True #Multicloud isn't about using one or the other :p How to deploy in 2 minutes, a 3-node #MongoDB ReplicaSet in #multicloud / #hybridCloud with LayerOps on private server(Physical Server #LXD),  OVHcloud and #Azure. #Fair #DbaaS #DevOps #PlatformEngineering #layerops

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⏰Join us at 11am ET TOMORROW for the next YugabyteDB Community Open Hours.⏰ In this episode, Yugabyte experts Franck Pachot and Denis Magda will participate in the recently launched Postgres App Century Challenge by performing a live migration of several existing Postgres applications to YugabyteDB. 👀 You’ll learn migration tips and tricks, plus how to avoid pitfalls. Join us to see how many apps Franck and Denis can migrate in one hour!💡 Learn more about the challenge here: https://hubs.la/Q02M_Mn_0 Bring your questions to the chat and join the discussion.🚀 Register now!➡️https://hubs.la/Q02M_NMS0 Join the YugabyteDB community!➡️ https://hubs.la/Q02M_GVT0 #YugabyteDB #cloudnative #distributedsql #Postgresql #community #opensource #migration

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Taming the Technical Debt Monster: New Methods for DevOps DevOps, a popular approach for software development, emphasizes collaboration and continuous improvement. However, a new study by Jose BONET FAUSé, Pascal Le Masson, Ugo Pelissier, Nafissa Jibet, Antoine Bordas, and Sébastien Pajot from Mines de Paris and Ubisoft highlight a hidden challenge: Entangled Technical Debt (ETD). (ICED23 Proceedings) https://lnkd.in/gkw5E4SM Join the "Design is a Team Sport" movement at ICED25 Dallas. How can DevOps practices be adapted to minimize technical debt? What are the biggest challenges in managing technical debt in software development? Share your thoughts on the future of DevOps and its role in sustainable software engineering! Don't miss out!  · Register for ICED25 Dallas: iced.designsociety.org/ The University of Texas at Dallas, The Design Society #DevOps #TechnicalDebt #SoftwareDevelopment #SystemsEngineering #DesignThinking #SoftwareQuality

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The three pillars are dead, long live OpenTelemetry’s 𝐬𝐢𝐠𝐧𝐚𝐥𝐬! In the OpenTelemetry terminology, different types of telemetry are known as 𝐬𝐢𝐠𝐧𝐚𝐥𝐬. OpenTelemetry provides support for the “classic” signals, namely metrics, logs, and traces (sometimes still referred to as “three pillars”, although that idiom is a remnant of the past, as we will cover in an upcoming “Observability and its history” series), but work is underway on other signals: profiling, real user monitoring, and events. 𝐌𝐞𝐭𝐫𝐢𝐜𝐬 are data collected over time and represent a measurement of a resource, i.e., 𝐭𝐢𝐦𝐞 𝐬𝐞𝐫𝐢𝐞𝐬. For example, the CPU utilization of a host, the count of Pods in a Kubernetes cluster, or the request count of a service can all be considered metrics. 𝐋𝐨𝐠𝐬 provide information about something happening at one point in time in a component. Logs are annotated with their 𝐬𝐞𝐯𝐞𝐫𝐢𝐭𝐲 to denote the offer of valuable insights at different levels of importance. Developers commonly use logs in production environments for debugging purposes. 𝐓𝐫𝐚𝐜𝐞𝐬 (or 𝐝𝐢𝐬𝐭𝐫𝐢𝐛𝐮𝐭𝐞𝐝 𝐭𝐫𝐚𝐜𝐢𝐧𝐠) involves capturing the path taken by a request within the various components of a (distributed) application, including timing information, errors encountered, and relevant attributes like HTTP status codes to analyze the performance and behavior of cloud-native applications. 𝐏𝐫𝐨𝐟𝐢𝐥𝐞𝐬, currently under early development in OpenTelemetry, measure the runtime behavior of an application by taking snapshots of the executed code at various points in time. This allows for identifying optimization opportunities in terms of CPU and memory consumption, as well as hot spots for execution time. #opentelemetry #opentelemetrynative

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🚨Join us LIVE in ONE HOUR for the next YugabyteDB Community Open Hours.🚨 In this episode, Yugabyte experts Franck Pachot and Denis Magda will discuss and demonstrate their five top PostgreSQL extensions for application developers. Bring your questions to the chat and join the discussion.🚀 Register now!➡️https://hubs.la/Q02w7mph0 Join the YugabyteDB community!➡️ https://hubs.la/Q02w7p8f0 #YugabyteDB #cloudnative #distributedsql #Postgresql #community #opensource

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