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Driving Content Delivery Efficiency Through Classifying Cache Misses

Netflix’sOpen Connectprogram rewires the streaming game. EnterOpen Connect Appliances (OCAs): these local units demolish latency, curbcache misses, and pump up streaming power. How? By magnetizing servers withnetwork proximitywizardry. Meanwhile,Kafkarolls up its sleeves, juggling low-latency logs l.. read more  

Driving Content Delivery Efficiency Through Classifying Cache Misses
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New Amazon EC2 P6e-GB200 UltraServers accelerated by NVIDIA Grace Blackwell GPUs for the highest AI performance

Amazon EC2 P6e-GB200 UltraServersroar to life withNVIDIA Grace Blackwell. Imagine a beast with360 petaflopsof FP8 compute and13.4 TBof high-bandwidth memory. Hungry for speed? They deliver, with28.8 TbpsEFAv4 networking, ensuring lightning-fast data flow. And the GPUs chat like old friends, thanks t.. read more  

New Amazon EC2 P6e-GB200 UltraServers accelerated by NVIDIA Grace Blackwell GPUs for the highest AI performance
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Local Chatbot RAG with FreeBSD Knowledge

Deepseek-r1crushes it for FreeBSD chatbots running locally on hefty GPUs. It dishes out adjustable precision, but don’t expect rubber-stamped approval... read more  

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Hidden Complexities of Distributed SQL

Distributed SQL engines shine when it comes to wrangling scattered data. Their secret weapons?Push-down filtersandTopNtricks that slash data transfer and shrink processing time. They deftly juggle complex queries from multiple sources, without the whole data mess piling up. Even the humdinger of ope.. read more  

Hidden Complexities of Distributed SQL
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Why Policy as Code is a Game Changer for Platform Engineers

Policy as Code (PaC) isn't just another tech trend. It’s shaking up platform engineering. Get instant feedback, dodge production disasters, and automate compliance. It’s like a security blanket for self-service platforms. Enforcing those"golden paths"might actually keep things safe while innovation .. read more  

Why Policy as Code is a Game Changer for Platform Engineers
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Netflix Tudum Architecture: from CQRS with Kafka to CQRS with RAW Hollow

RAW Hollow, Netflix's brainy in-memory database, torches Tudum's update lag by jamming full datasets right into app memory. This move guaranteesO(1)access time and rock-solidread-after-writeconsistency while flexing to juggle a whopping100 millionrecords... read more  

Netflix Tudum Architecture: from CQRS with Kafka to CQRS with RAW Hollow
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How to Reduce Technical Debt With Artificial Intelligence (AI)

Technical debt from outdated software slows down businesses, costingover $2.4 trillion annually in the U.S. Using AI in SaaS can smartly reduce debt, but beware AI-induced debt by implementing rigorous oversight and governance principles likeT.R.U.S.T. Responsible AI integration enhances SaaS scalab.. read more  

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Understanding Time Series Databases

Time series databasesoptimize storage, retrieval, and analysis of time-stamped data, offering high-speed ingestion and specialized analytics. TSDBs are designed for efficiency and scalability, outperforming traditional databases in time-centric applications... read more  

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Backup for GKE supports cross-project backup and restore

Backup for GKEjust got a power-up. Now, you can zip data from one Google Cloud project and unpack it in another. This shake-up makes disaster recovery smoother, teamwork easier, and security tighter by keeping backups out of the wrong hands. All the control, none of the headache. No scripts needed... read more  

Backup for GKE supports cross-project backup and restore
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Docker Desktop 4.43: Expanded Model Runner, Reimagined MCP Catalog, MCP Server Submissions, and Smarter Gordon

Docker Desktop 4.43 cranks up AI integration with theModel Runner. OpenAI APIs? Now they're putty in your hands. Fine-tune model runtime with ease. EnterDocker’s Gordon—the multitasker extraordinaire who juggles threads like a caffeinated circus performer. Enjoy speeds and accuracy that make old ver.. read more  

Docker Desktop 4.43: Expanded Model Runner, Reimagined MCP Catalog, MCP Server Submissions, and Smarter Gordon
Vertex AI is Google Cloud’s end-to-end machine learning and generative AI platform, designed to help teams build, deploy, and operate AI systems reliably at scale. It unifies data preparation, model training, evaluation, deployment, and monitoring into a single managed environment, reducing operational complexity while supporting advanced AI workloads.

Vertex AI supports both custom models and foundation models, including Google’s Gemini model family. It enables organizations to fine-tune models, run large-scale inference, orchestrate agentic workflows, and integrate AI into production systems with strong security, governance, and observability controls.

The platform includes tools for AutoML, custom training with TensorFlow and PyTorch, managed pipelines, feature stores, vector search, and online and batch prediction. For generative AI use cases, Vertex AI provides APIs for text, image, code, multimodal generation, embeddings, and agent-based systems, including support for Model Context Protocol (MCP) integrations.

Built for enterprise environments, Vertex AI integrates deeply with Google Cloud services such as BigQuery, Cloud Storage, IAM, and VPC, enabling secure data access and compliance. It is widely used across industries like finance, healthcare, retail, and science for applications ranging from recommendation systems and forecasting to autonomous research agents and AI-powered products.