Kaviraj K.

📈 We released DuckDB 1.4.0 today. This is our first LTS release that comes with one year of community support. 👉 The new release packs many new features for security, data lake support and productivity: swipe below for a quick summary. ⏱️ For a more complete list of performance optimizations, distribution improvements and new integrations, see the announcement blog post – link in the comments.

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Kafka isn’t just another buzzword; it’s the backbone of real-time data streaming and the silent force behind countless applications. • Need real-time insights? Kafka delivers. • Want scalable data processing? Kafka scales effortlessly. • Dream of future-proof architecture? Kafka makes it happen. → Top 6 Kafka Use Cases 1️⃣Change Data Capture (CDC): Sync databases instantly and seamlessly, eliminating polling delays. 2️⃣ Monitoring & Alerting: Detect anomalies instantly by ingesting logs and metrics—proactive problem-solving to prevent downtime. 3️⃣ Message Queuing: Handle massive volumes faster and more reliably than traditional queues. 4️⃣ Data Streaming: Power real-time dashboards, dynamic recommendations, and instant fraud detection with low-latency event streams. 5️⃣ Data Replication: Safeguard business continuity by replicating data across multiple locations. 6️⃣ Log Aggregation: Centralize scattered logs for faster troubleshooting and quicker resolutions. credit:-Sandeep Bonagiri follow:-Tech In Nutshell

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The latest CNCF end-user survey shows how widely Argo CD is being used for GitOps: ✅ 97% of respondents run it in production (up from 93% in 2023) ✅ 60% have used it for more than 2 years ✅ 42% manage over 500 apps per instance ✅ 25% connect to more than 20 clusters Interesting to see how much adoption and scale Argo CD has reached. 👉

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Big news for the Apache Kafka community! 🎉 Kafka 4.1 is out. This release includes 18 KIPs from the broader community. Kafka 4.1 hardens the 4.0 foundation and introduces new features for OAuth, operations, Streams, Connect, Queues, KIP-848, and more. Explore what’s new in the blog ➡️ https://cnfl.io/461BTbe

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Eric Thomas took an excellent lakehouse tutorial built with Airflow and rebuilt it with Dagster. The stack is the same: MinIO, Trino, Iceberg, and dbt. The orchestrator is different. The results were striking: → Event-driven sensors replaced time-based scheduling. Pipelines run when data arrives, not on a clock. → Smart partitioning enabled backfills and selective reruns. No more all-or-nothing processing. → Asset checks created multi-layered quality validation. Data quality became programmatic, not just hoped for. → Pure SQL patterns eliminated Python bottlenecks. Trino handles the heavy lifting. The Lakehouse provides the foundation, but the orchestration layer determines how effectively teams can actually use it. The original tutorial teaches lakehouse fundamentals beautifully. This comparison shows how much orchestration choice matters for production readiness. Check out the full blog today! Link in the comments

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🧠 “I don’t want to store memories in a text file. I want them in a proper memory system — searchable, contextual, and shared across projects.” In this livestream, Rowan Trollope (CEO of Redis) and Guy Gur-Ari (Co-founder of Augment Code): 1⃣ Replace flat file memory with a Redis-powered vector store 2⃣ Teach agents how to store, recall, and reason with real context 3⃣ Debug live failures (and fix them using the agent itself) 4⃣ Explore how memory could scale across projects and teams If you’ve ever hit the ceiling of what AI agents can “remember,” this is your blueprint for pushing past it. 🎥 Watch it now → https://lnkd.in/g8Muq9qE

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ShareChat runs hundreds of Go services across thousands of cores. At #P99CONF, Paweł Obrępalski will break down two core components of Go’s runtime: the scheduler and garbage collector. You'll learn how they influence latency, throughput, and resource usage during this highly technical session. https://lnkd.in/ebDnC332 #ScyllaDB

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When someone who has trained thousands of #DevOps engineers speaks, you listen. 🎤 In this conversation with Nana Janashia she called out the pattern: Early teams ship fast… until they start patching nodes, fixing ingress, chasing security, and scaling infra by hand. Manual Kubernetes can burn time, headcount, and best practices: • No ingress or load balancer setup • Security you don’t notice until it’s too late • Upgrades, Patching taking up whole development time • DevOps engineers tied up managing clusters instead of building product Automation isn’t enterprise-only anymore. Amazon EKS Auto Mode is built for that shift — automate infra, scale on demand, secure by default, and stay focused on building. ➡️ https://go.aws/47jn45F #Automation #EKSAutoMode #PlatformEngineering

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How much does a Kubernetes engineer earn in Q3 2025? Is Platform Engineering really eating DevOps' lunch? We analyzed 509 Kubernetes job descriptions and discovered: 💰 North American salaries average $177,983 (€92,113 in Europe) 🚀 Platform Engineer roles jumped to 9% of positions (vs 4-7% last year) 👨‍💻 43% of jobs are for Software Engineers, but DevOps roles offer the best remote flexibility (56%) 🏠 Remote work paradox: 67% allow remote, but only 0.29% are truly location-independent Dive into the complete State of Kubernetes Job Market Q3 2025 report: https://lnkd.in/gfmuQWhe ⭐️ This report is brought to you by LearnKube — get started on your Kubernetes journey through comprehensive online, in-person, or remote training. https://lnkd.in/ge4aYVZq

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Kube Resource Orchestrator (KRO) is a Kubernetes-native tool that simplifies the creation and management of complex custom resources by allowing developers to define reusable components, group resources, and manage dependencies effectively. More: https://ku.bz/2y0L9vDf9

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☁️ "A good BYOC solution will support zero-access from the vendor accessing their raw data in their cloud under any circumstances." - Tom Wilkie, CTO of Grafana Labs It's essential to understand precisely what a company's BYOC offering entails and how it's implemented. Here's what you should know regarding sovereignty and privacy issues: https://lnkd.in/get-VCfY From Richard Speed at The Register.

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☁️ Kubernetes will solve YAML headaches with KYAML. The new KYAML subset just for K8s relieves the need to count white spaces and solves the age-old "Norway" issue. Get the details: https://hubs.la/Q03Dr0Kr0 #YAML #Kubernetes #CloudNative

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A GUI is nice—but real agility comes from code. That’s why we built Graphiant SDKs in Python and Go, plus Terraform and Ansible playbooks. Now, developers can programmatically spin up cloud gateways and integrate Graphiant into their CI/CD pipelines. Consistent. Repeatable. Scalable. Multi-cloud networking should be as flexible as your application stack. With Graphiant, it finally is. 👉 Read the full blog here: https://hubs.ly/Q03DTYH20

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Zadara was built from the ground up as a multi-tenant cloud, aligning natively with NVIDIA’s recommendations. Here’s how Zadara meets and exceeds the reference design expectations: -Native Multi-Tenancy -Full-Stack Workload Support -Per-Tenant Kubernetes Environments -Elastic Resource Allocation -Global Edge Presence Read more: https://lnkd.in/eTCu6rTF

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