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Open Source Observability Stack Essentials
I’m excited to share that my newest course is now live on Coursera: Open Source Observability Stack Essentials. This course is built for software engineers, SREs, and platform engineers who want a practical, hands-on way to learn the foundations of modern observability using the open-source tools that matter most: Prometheus, Grafana, and OpenTelemetry. In just a few hours, you’ll go from concepts to practice: - understanding metrics, logs, and traces - deploying a minimal local observability stack - instrumenting an app with OpenTelemetry - building a Grafana dashboard for requests, errors, and latency - creating alerts that are actually useful in real environments I designed this course to be practical, not theoretical. By the end, learners will have working configs, starter queries, and a clearer path toward production-ready observability, including topics like SLOs, burn rate alerts, retention, and exporter strategy. Observability is no longer optional in cloud-native systems. Modern applications rarely fail loudly — they fail through latency, partial degradation, and noisy dependencies. My goal with this course is to help learners build the skills to detect, understand, and troubleshoot those issues with confidence. Thanks to everyone who has supported my learning journey so far through books, courses, and the open-source community. I’m proud to keep contributing content that helps engineers build stronger systems. https://www.coursera.org/learn/open-source-observability-stack-essentials/ #Observability #OpenTelemetry #Prometheus #Grafana #SRE #DevOps #CloudNative #Monitoring #Engineering #Kubernetes #OpenSource #Coursera
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Open Source Observability Stack Essentials
Kyverno GRADUATED vote by CNCF
Huge moment for @Kyverno The CNCF TOC has opened the graduation vote. If you support #Kyverno and policy as code, add your to the issue and help back this milestone for the community. https://github.com/cncf/toc/issues/1967#issuecomment-4067997727
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A self hosted virtual browser that runs in docker and uses WebRTC
Welcome to Neko, a self-hosted virtual browser that runs in Docker and uses WebRTC technology. Neko is a powerful tool that allows you to run a fully-functional browser in a virtual environment, giving you the ability to access the internet securely and privately from anywhere. With Neko, you can browse the web, run applications, and perform other tasks just as you would on a regular browser, all within a secure and isolated environment. Whether you are a developer looking to test web applications, a privacy-conscious user seeking a secure browsing experience, or simply someone who wants to take advantage of the convenience and flexibility of a virtual browser, Neko is the perfect solution. In addition to its security and privacy features, Neko offers the ability for multiple users to access it simultaneously. This makes it an ideal solution for teams or organizations that need to share access to a browser, as well as for individuals who want to use multiple devices to access the same virtual environment. With Neko, you can easily and securely share access to a browser with others, without having to worry about maintaining separate configurations or settings. Whether you need to collaborate on a project, access shared resources, or simply want to share access to a browser with friends or family, Neko makes it easy to do so. Neko is also a great tool for hosting watch parties and interactive presentations. With its virtual browser capabilities, Neko allows you to host watch parties and presentations that are accessible from anywhere, without the need for in-person gatherings. This makes it easy to stay connected with friends and colleagues, even when you are unable to meet in person. With Neko, you can easily host a watch party or give an interactive presentation, whether it's for leisure or work. Simply invite your guests to join the virtual environment, and you can share the screen and interact with them in real-time. https://neko.m1k1o.net/
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War at the Speed of Software: Is AI Taking Over the Kill Chain?
While most of us are using AI to draft emails, the military is using it to “accelerate the kill chain”. I’ve spent 18 years advising organizations on responsible technology, but the shift we are seeing in modern warfare is unprecedented. We are moving from human-led analysis toward computer-driven triage, where AI platforms fuse satellite imagery and drone footage to propose targets at a tempo humans can barely process. The real danger isn't a "Terminator" scenario—it’s decision compression. When a machine generates a recommendation in seconds, the human "in the loop" often becomes a mere approver reacting to a queue rather than a commander making a deliberative judgment. In my latest video, I dive into: The quest for "Decision Dominance". The tension between military speed and corporate safety boundaries. Why we need explainability, auditability, and accountability to avoid "moral crumple zones". Is "human control" becoming a mere formality in the age of AI? Watch the full breakdown here: https://lucaberton.com/blog/ai-warfare-speed-of-software-kill-chain/ #AI #DefenseTech #MilitaryAI #EthicalAI #NationalSecurity #TechLeadership #Innovation
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War at the Speed of Software: Is AI Taking Over the Kill Chain?
Fully automatic censorship removal for language models
Heretic is a tool that removes censorship (aka "safety alignment") from transformer-based language models without expensive post-training. It combines an advanced implementation of directional ablation, also known as "abliteration" (Arditi et al. 2024, Lai 2025 (1, 2)), with a TPE-based parameter optimizer powered by Optuna. This approach enables Heretic to work completely automatically. Heretic finds high-quality abliteration parameters by co-minimizing the number of refusals and the KL divergence from the original model. This results in a decensored model that retains as much of the original model's intelligence as possible. Using Heretic does not require an understanding of transformer internals. In fact, anyone who knows how to run a command-line program can use Heretic to decensor language models. https://github.com/p-e-w/heretic
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Fully automatic censorship removal for language models
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