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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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NGINX Basics

NGINXisn't just a web server; it's the lean, mean, speed machine you've always wanted. But, frankly, it's best understood by diving in and getting your hands dirty. Break stuff. Fix stuff. Repeat. That's how you hit pro status... read more  

NGINX Basics
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Build the highest resilience apps with multi-Region strong consistency in Amazon DynamoDB global tables

Amazon DynamoDBjust rolled out a nifty trick: multi-Region strong consistency. It's tailor-made for zero RPO junkies. Even during those pesky Region meltdowns, your data stays fresh as a daisy. Take your pick—go grand with three full replicas or skimp on cash with two replicas and a witness... read more  

Build the highest resilience apps with multi-Region strong consistency in Amazon DynamoDB global tables
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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Technical debt from outdated software slows down businesses, costingover $2.4 trillion annually in the U.S. Using AI in SaaS can smartly reduce debt, but beware AI-induced debt by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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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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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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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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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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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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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  

GPT-5.4 is OpenAI’s latest frontier AI model designed to perform complex professional and technical work more reliably. It combines advances in reasoning, coding, tool use, and long-context understanding into a single system capable of handling multi-step workflows across software environments. The model builds on earlier GPT-5 releases while integrating the strong coding capabilities previously introduced with GPT-5.3-Codex.

One of the defining features of GPT-5.4 is its ability to operate as part of agent-style workflows. The model can interact with tools, APIs, and external systems to complete tasks that extend beyond simple text generation. It also introduces native computer-use capabilities, allowing AI agents to operate applications using keyboard and mouse commands, screenshots, and browser automation frameworks such as Playwright.

GPT-5.4 supports context windows of up to one million tokens, enabling it to process and reason over very large documents, long conversations, or complex project contexts. This makes it suitable for tasks such as analyzing codebases, generating technical documentation, working with large spreadsheets, or coordinating long-running workflows. The model also introduces a feature called tool search, which allows it to dynamically retrieve tool definitions only when needed. This reduces token usage and makes it more efficient to work with large ecosystems of tools, including environments with dozens of APIs or MCP servers.

In addition to improved reasoning and automation capabilities, GPT-5.4 focuses on real-world productivity tasks. It performs better at generating and editing spreadsheets, presentations, and documents, and it is designed to maintain stronger context across longer reasoning processes. The model also improves factual accuracy and reduces hallucinations compared with previous versions.

GPT-5.4 is available across OpenAI’s ecosystem, including ChatGPT, the OpenAI API, and Codex. A higher-performance variant, GPT-5.4 Pro, is also available for users and developers who require maximum performance for complex tasks such as advanced research, large-scale automation, and demanding engineering workflows. Together, these capabilities position GPT-5.4 as a model aimed not just at conversation, but at executing real work across software systems.