Rudy Krol

🚨 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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Myth: Adding more monitoring tools to #Kubernetes results in better insights. 🚫 Truth: Over-tooling can lead to complexity and noise. Effective observability is about choosing the right tools that integrate seamlessly and provide meaningful data. Understanding relationships between existing telemetry is often a bigger win than adding another source. Try Metoro and simplify the #k8s observability 👇

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Cloud-native, #Kubernetes-oriented, microservices based architectures are driving the need for over-the-network storage solutions like MinIO. Unlike legacy systems, MinIO supports modern disaggregated architectures, delivering cost savings, scalability, and superior performance, as demonstrated by one of our financial customers that achieved over 60% cost-to-performance improvements with MinIO over #HDFS. AJ takes you through how to bring the benefits of #objectstorage to Hadoop—by changing the storage protocol, data migration and performance tuning. https://hubs.li/Q02QPdSS0

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Cloud-native, #Kubernetes-oriented, microservices based architectures are driving the need for over-the-network storage solutions like MinIO. Unlike legacy systems, MinIO supports modern disaggregated architectures, delivering cost savings, scalability, and superior performance, as demonstrated by one of our financial customers that achieved over 60% cost-to-performance improvements with MinIO over #HDFS. AJ takes you through how to bring the benefits of #objectstorage to Hadoop—by changing the storage protocol, data migration and performance tuning. https://hubs.li/Q02QP9fD0

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𝐇𝐨𝐰 𝐭𝐨 𝐆𝐢𝐭𝐎𝐩𝐬 𝐟𝐨𝐫 𝐊𝐚𝐟𝐤𝐚 𝐚𝐭 𝐬𝐜𝐚𝐥𝐞? Managing complex infrastructures like Kafka requires a scalable and automated approach. As deployments grow in size and complexity, keeping track of configurations, updates, and dependencies becomes a daunting task for platform teams. At the same time, identifying ownership, discovering existing resources, and cross-team data sharing are challenges for development teams. 👉 GitOps and Infrastructure as Code (IaC) are foundational practices in the DevOps and cloud-native spaces. These practices can be leveraged on Kafka to bring consistency, standardization, and business agility. In the context of Kafka, GitOps relates to: - Deployment automation - Kafka resource configuration - Access provisioning - Kafka client configurations Learn how to GitOps for Kafka at scale ➡️ https://lnkd.in/gy2naCKp

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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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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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Want Kubernetes but not the complexity? Join our Dec 10 webinar to explore #k0s — a simpler, flexible solution with minimal dependencies and super easy setup. And learn how #k0smotron enables Kubernetes-as-a-Service. https://bit.ly/498IG48

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OpenShift and Kubernetes are today's most widely used container orchestration software options. How do they compare? Watch this video for an in-depth look at their similarities, differences and which is right for your projects. Red Hat

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Tired of manually scaling your cloud applications to meet fluctuating demand? 😯 Kubernetes Autoscaling has you covered! This powerful feature automatically adjusts the number of running application pods based on real-time needs. Here's the magic: 🔔 Dynamic Scaling: Kubernetes scales your applications up or down as workloads change, ensuring optimal performance without ever needing manual intervention. 🔔 Spike Protection: Sudden traffic surges? No problem. Autoscaling seamlessly handles them, preventing application downtime and performance dips. 🔔 Resource Optimization: Stop wasting resources on underutilized applications. Autoscaling ensures efficient resource allocation, saving you money on cloud infrastructure. The result? Highly scalable and cost-effective cloud applications that run smoothly, even during peak loads. Ready to learn more? Check out this insightful article for a deep dive into Kubernetes Autoscaling and its benefits for your business: https://lnkd.in/g7SisHNz #Kubernetes #CloudComputing #DevOps #Autoscaling

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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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Facing data delays at the edge? Discover how to solve latency and inefficiency issues in industries like manufacturing and telecom. Watch our on-demand webinar to learn how Mirantis Container Runtime brings data processing closer to the edge, reduces latency, and boosts real-time performance with #Kubernetes, #Swarm, or standalone #MCR. Watch now! https://bit.ly/40uj4fI

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Want to get the most out of Flink on Kubernetes? We've got you covered! In this on-demand recording, our own Lior Friedler shares how to: 👉 Tailor Flink to Kubernetes for optimal performance. 👉 Allocate and manage resources like a pro. 👉 Overcome common Flink on Kubernetes challenges. 👉 Leverage Kubernetes for effortless Flink rollouts. Watch the recording now! ➡️ https://ow.ly/WVX450RqaIp #Flink #Kubernetes #K8s #DataEngineering

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Kafka Operators for Kubernetes Curious about simplifying your Kafka deployments on Kubernetes? Our blog breaks it all down: ✅ What is a Kafka Operator? Understand how it works within Kubernetes. ✅ Streamlining Deployments: Learn how it automates complex tasks for you. ✅ Reliable Cluster Management: Discover why operators are crucial for maintaining stability and scaling with ease. If you're working in a cloud-native environment or leveraging microservices, Kafka Operators are a game-changer. 👉 Dive into the full blog here: https://lnkd.in/eggr7Abu #Kafka #Kubernetes #CloudNative #DevOps #Microservices

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🚀 Streamline Your Kubernetes Deployments with Labels & Service Discovery 🚀 When scaling complex applications in Kubernetes, effective Labeling and Service Discovery are your power tools. But how can you harness these capabilities to manage cloud native applications more efficiently? 🔑 Key Concepts: Labels & Annotations: Use labels to group and organize Kubernetes objects like Pods. For example, applying labels such as app=frontend, env=prod makes filtering, scaling, and monitoring your clusters a breeze. Labels → Organized Clusters Annotations → Metadata for Enhanced Functionality Service Discovery: Kubernetes' dynamic environment makes traditional service discovery methods obsolete. The Service Object automatically discovers and connects services to your Pods, using DNS for name resolution and balancing traffic across Pods. Service Object → Automatically Routing Traffic DNS-Based Discovery → Resilient and Dynamic 💡 Real-Time Applications: E-commerce Scaling: Apply labels to manage different environments (e.g., prod, staging) for microservices, streamlining testing and updates. Service Resilience: Automatically discover failing Pods with DNS-based service discovery, ensuring smooth traffic routing and improved uptime. Labels & Annotations → Organized Pods (app=frontend, env=prod) ↓ Service Discovery → Traffic Routing & Load Balancing ↓ Application Stability → High Resilience, Scalability, and Automated Failover 🌟 Ready to take your Kubernetes deployments to the next level? 🌟 At #Nodesol, we specialize in Laravel, SaaS development, and Kubernetes orchestration. Our team of experts can help you streamline your cloud-native applications using best-in-class Kubernetes solutions. Whether it’s setting up resilient microservices or optimizing your clusters for efficiency and performance, we’ve got you covered. ✨ Let Nodesol help you deploy with confidence, scale seamlessly, and build resilient, cloud-native applications that stand out in today's competitive landscape. Contact us today to get started! #Kubernetes #Nodesol #ServiceDiscovery #DevOps #CloudNative #Automation #Microservices #SaaS

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As a cloud-native platform engineer, what is the biggest challenge you're currently facing? Feel free to elaborate on your specific challenge in the comments. Thank you for your participation! 🙏 1️⃣ WebAssembly integration 2️⃣ GitOps integration 3️⃣ Service mesh complexity 4️⃣ CI/CD pipelines

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🔐 Welcome to today’s Cloud Safari episode! 🌥️ Dive deep into AWS Secrets Manager and learn how to securely manage your API keys, passwords, and sensitive data. Discover the core functionalities, benefits, and step-by-step integration with RDS and EC2 instances. 🚀 Enhance your security posture with automatic secrets rotation, multi-region support, and seamless integration with various AWS services. Don’t miss out on this essential guide to simplifying and securing your cloud infrastructure! https://lnkd.in/gz_tRbkX  #adexltd #youtubevideos #awstutorial #aws #amazonwebservices #awssecretmanager

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