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@sancharini shared a post, 1ย month ago

Black Box vs White Box Testing in Unit, Integration & E2E Testing: Where Each Belongs

Understand where black box and white box testing belong across unit, integration, and E2E testing. Learn the right technique for every layer of your test suite.

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@laura_garcia shared a post, 1ย month ago
Software Developer, RELIANOID

Deploy RELIANOID Load Balancer Community Edition v7 on AWS in minutes with Terraform.

โšก Deploy RELIANOID Load Balancer Community Edition v7 on AWS in minutes with Terraform. From zero to a fully functional load balancer โ€” automated, reproducible, and ready to go. ๐Ÿ‘‰ Follow the step-by-step guide and get started fast. #Terraform#AWS#InfrastructureAsCode#DevOps#RELIANOID#Automation http..

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@vlebo added a new tool ctx_ , 1ย month ago.
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@laura_garcia shared a post, 1ย month ago
Software Developer, RELIANOID

๐—จ๐—ž ๐—ฃ๐—ฆ๐—ง๐—œ ๐—”๐—ฐ๐˜: ๐—” ๐—ก๐—ฒ๐˜„ ๐—˜๐—ฟ๐—ฎ ๐—ณ๐—ผ๐—ฟ ๐—–๐—ผ๐—ป๐—ป๐—ฒ๐—ฐ๐˜๐—ฒ๐—ฑ ๐——๐—ฒ๐˜ƒ๐—ถ๐—ฐ๐—ฒ ๐—ฆ๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐˜๐˜†

๐Ÿ” ๐—จ๐—ป๐—ฑ๐—ฒ๐—ฟ๐˜€๐˜๐—ฎ๐—ป๐—ฑ๐—ถ๐—ป๐—ด ๐˜๐—ต๐—ฒ ๐—จ๐—ž ๐—ฃ๐—ฆ๐—ง๐—œ ๐—”๐—ฐ๐˜: ๐—” ๐—ก๐—ฒ๐˜„ ๐—˜๐—ฟ๐—ฎ ๐—ณ๐—ผ๐—ฟ ๐—–๐—ผ๐—ป๐—ป๐—ฒ๐—ฐ๐˜๐—ฒ๐—ฑ ๐——๐—ฒ๐˜ƒ๐—ถ๐—ฐ๐—ฒ ๐—ฆ๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐˜๐˜† The UK is raising the bar on cybersecurity with the Product Security and Telecommunications Infrastructure (PSTI) Act, now in force since April 2024. As cyber threats continue to grow, this regulation introduces a baseline for ..

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@omarabid added a new tool Code Input , 1ย month, 1ย week ago.
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@hitechdigital created an organization HitechDigital Solutions , 1ย month, 1ย week ago.
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@varbear shared a link, 1ย month, 1ย week ago
FAUN.dev()

What if I stored data in my mouse

The author experimented with storing data in a Logitech mouse's flash memory. Logitech mice communicate through HID++, a protocol that maps device features using stable IDs. Despite efforts to write data to certain registers, only the DPI register could retain data across power cycles... read more ย 

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@varbear shared a link, 1ย month, 1ย week ago
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How Microsoft Vaporized a Trillion Dollars

A former Azure Core engineer recounts arriving on his first day to find a 122-person org seriously planning to port Windows-based VM management agents - 173 of them, which nobody could fully explain - onto a tiny, low-power ARM chip running Linux. The stack was already failing to scale on server-gra.. read more ย 

How Microsoft Vaporized a Trillion Dollars
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@varbear shared a link, 1ย month, 1ย week ago
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Bad Analogies:ย Not Every Money-Burning Company is Amazon

The essay discusses the misconceptions around companies that burn a lot of money, drawing comparisons to Amazon's successful strategy. It delves into examples like Uber and WeWork to highlight the importance of understanding the long-term implications of cash burn. The focus is on the strategies and.. read more ย 

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@varbear shared a link, 1ย month, 1ย week ago
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The Beginning of Programming as Weโ€™ll Know It

In the wake of AI coding assistants like Claude and Codex, many wonder if the human role of "computer programmer" is ending. Although AI shows promise, human developers are valuable in the current transitional period. Real programmers are uniquely positioned to harness AI's power while augmenting it.. read more ย 

The Beginning of Programming as Weโ€™ll Know It
vLLM is an advanced open-source framework for serving and running large language models efficiently at scale. Developed by researchers and engineers from UC Berkeley and adopted widely across the AI industry, vLLM focuses on optimizing inference performance through its innovative PagedAttention mechanism โ€” a memory management system that enables near-zero waste in GPU memory utilization. It supports model parallelism, continuous batching, tensor parallelism, and dynamic batching across GPUs, making it ideal for real-world deployment of foundation models. vLLM integrates seamlessly with Hugging Face Transformers, OpenAI-compatible APIs, and popular orchestration tools like Ray Serve and Kubernetes. Its design allows developers and enterprises to host LLMs with reduced latency, lower hardware costs, and increased throughput, powering everything from chatbots to enterprise-scale AI services.