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The story of how we almost got hacked

Team Invictus caught a BEC attempt using WeTransfer to slip in a fake Microsoft 365 login page powered byEvilProxy. Classic Adversary-in-the-Middle move, but dressed up with a slick delivery package. Digging deeper, the team mapped the attacker’s setup and found something bigger: a credential grab c.. read more  

The story of how we almost got hacked
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Failure is inevitable: Learning from a large outage, and building for reliability in depth at

Datadog ditched its “never fail” mindset after a March 2023 meltdown knocked out half its Kubernetes nodes and took major user features down with them. The fix? A full-stack rethink built aroundgraceful degradation. The team addeddisk-based persistence at intake,live-data prioritization,QoS-aware re.. read more  

Failure is inevitable: Learning from a large outage, and building for reliability in depth at
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Declarative Action Architecture

The Declarative Action Architecture (DAA) is a scalable E2E testing pattern that separates concerns across three distinct layers. TheTest Layeris 100% declarative, statingwhatis being tested without any procedural logic, making tests read like documentation. The coreAction Layerimplements the execut.. read more  

Declarative Action Architecture
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Comparing AWS Lambda Arm64 vs x86_64 Performance Across Multiple Runtimes in Late 2025

A new open-source benchmark looked at 183,000 AWS Lambda invocations, andarm64 beats x86_64across the board in both cost and speed. Rust on arm64 with SHA-256 tuned in assembly? It clocks in 4–5× faster than x86 in CPU-heavy tasks. Cold starts are snappy too—5–8× quicker than Node.js and Python... read more  

Comparing AWS Lambda Arm64 vs x86_64 Performance Across Multiple Runtimes in Late 2025
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@kaptain shared an update, 1 month, 2 weeks ago
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Agent Sandbox Brings Kernel-Level Guardrails to AI Agents on Kubernetes

gVisor Kata Containers Google Kubernetes Engine (GKE) Kubernetes

Agent Sandbox, a new Kubernetes primitive, was introduced at KubeCon NA 2025 to enhance AI agent management on Kubernetes and Google Kubernetes Engine.

Agent Sandbox Brings Kernel-Level Guardrails to AI Agents on Kubernetes
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AWS Unveils Graviton5: A 192-Core Leap in Cloud Performance and Efficiency

Amazon Web Services Amazon EC2

AWS introduces Graviton5-based EC2 M9g instances, boosting performance by 25% and enhancing scalability while reducing costs.

AWS Unveils Graviton5: A 192-Core Leap in Cloud Performance and Efficiency
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@varbear shared an update, 1 month, 2 weeks ago
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Tor Goes Rust: Introducing Arti, a New Foundation for the Future of Tor

Arti Rust Tor

The development of "Arti," a Rust-based Tor implementation funded by Zcash, aims to enhance security and efficiency by addressing the limitations of the current C-based Tor.

Tor Goes Rust: Introducing Arti, a New Foundation for the Future of Tor
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@varbear added a new tool Arti , 1 month, 2 weeks ago.
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@kala shared an update, 1 month, 2 weeks ago
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Gemini Deep Research Is Now Programmable Through a New API

Gemini 3 Vertex AI

The enhanced Gemini Deep Research agent is now available via API, enabling developers to integrate advanced research capabilities into applications, with the open-sourcing of DeepSearchQA for evaluating complex tasks.

Gemini Deep Research Is Now Programmable Through a New API
GPT (Generative Pre-trained Transformer) is a deep learning model developed by OpenAI that has been pre-trained on massive amounts of text data using unsupervised learning techniques. GPT is designed to generate human-like text in response to prompts, and it is capable of performing a variety of natural language processing tasks, including language translation, summarization, and question-answering. The model is based on the transformer architecture, which allows it to handle long-range dependencies and generate coherent, fluent text. GPT has been used in a wide range of applications, including chatbots, language translation, and content generation.

GPT is a family of language models that have been trained on large amounts of text data using a technique called unsupervised learning. The model is pre-trained on a diverse range of text sources, including books, articles, and web pages, which allows it to capture a broad range of language patterns and styles. Once trained, GPT can be fine-tuned on specific tasks, such as language translation or question-answering, by providing it with task-specific data.

One of the key features of GPT is its ability to generate coherent and fluent text that is indistinguishable from human-generated text. This is achieved by training the model to predict the next word in a sentence given the previous words. GPT also uses a technique called attention, which allows it to focus on relevant parts of the input text when generating a response.

GPT has become increasingly popular in recent years, particularly in the field of natural language processing. The model has been used in a wide range of applications, including chatbots, content generation, and language translation. GPT has also been used to create AI-generated stories, poetry, and even music.