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ShadowBroker - comprehensive OSINT dashboard in real time
Shadowbroker is an open-source network monitoring tool for data collection and traffic analysis.
Netdata - a powerful tool for server monitoring
Netdata is a monitoring tool that provides real-time data about server performance.
Mocker - CLI compatible with Docker, running on macOS (Apple Containerization)
Mocker is a tool for generating mock data for applications, simplifying testing and prototyping.
Review of 15 Single-Board Computers (SBC) Tested in 2025
The article provides a detailed overview of single-board computers tested in 2025, focusing on their performance, features, and applications.
You make decisions too hastily - 6 thinking models that will change that
The article discusses the hidden math behind our daily decisions and why many people make poor choices. It highlights how instincts can mislead us and suggests that understanding cognitive biases can enhance decision-making skills.
How Apple Designed Laptops for Repairability?
The article discusses how Apple used to design its laptops with repairability in mind and how this has changed over time. These changes impact users and the environment.
Retro-podcast: a review of computer press from 20, 25, and 30 years ago
The first episode of the retro podcast 'Yet to Be Named' takes listeners through the world of computer games from the 80s and 90s, discussing their impact on today’s culture.
The title of the issue on GitHub led to the infection of 4,000 developers' machines
The article explores 'clinejection', a phenomenon where AI tools autonomously install additional software, raising concerns and a need for responsible management.
NMAP - Network Scanning and Vulnerability Detection [sponsored]
As DevOps workshops offer hands-on training in the latest DevOps technologies, catering to the needs of both beginners and experienced participants. It's a great chance to learn and build valuable connections.
LLM generates 'credible' code rather than 'correct' - a case analysis with the database
The article addresses the limitations of large language models in generating correct code. It emphasizes the need for programmers to verify the code generated by LLMs to avoid mistakes and incorrect solutions.
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