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@laura_garcia shared a post, 2 weeks, 5 days ago
Software Developer, RELIANOID

🔐🌱 Cybersecurity and industrial sustainability: a moment to reflect as the year comes to an end

We shared this article a few months ago, but year-end is the perfect time to revisit it and reflect on where the industry is heading in the year ahead. Cybersecurity and sustainability can no longer be treated as separate disciplines. They share a common goal: ensuring ethical, resilient, and respon..

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@eon01 shared a post, 3 weeks, 1 day ago
Founder, FAUN.dev

Enshittification is not a bug

Docker Helm Kubernetes

Bitnami charts are still high quality, but their public image distribution is going away. Instead of rewriting everything, many teams can keep the charts and switch the underlying images (for example, to Docker Hardened Images) to minimize disruption and maintain security.

Bitnami vs Docker Hardened Images
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@laura_garcia shared a post, 3 weeks, 4 days ago
Software Developer, RELIANOID

🚀 Deploy RELIANOID CE v7 on AWS with Terraform

Quickly deploy RELIANOID Community Edition v7 on AWS using the official Terraform module. ✔️ VPC, Subnet & Security Group ✔️ EC2 with RELIANOID AMI ✔️ SSH & Web GUI ready ✔️ Easy cleanup with terraform destroy ⚠️ AMI is region-specific (default: us-east-1) 🔐 Always secure your SSH private key #Terra..

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@viktoriiagolovtseva shared a post, 3 weeks, 4 days ago

How To Create a Jira Test Case Template To Boost Efficiency

Many agile teams prefer Jira for managing test cases. Even though it’s not a dedicated tool, it provides a straightforward way to organize the testing process, track progress, and share results with stakeholders. Additionally, it enhances collaboration between QA and development teams.

Using test case templates in Jira allows you to manage this process even more efficiently. These templates save time, promote standardization, and provide a structured foundation for test execution. In this short tutorial, I will show you how to create a Jira test case template and use it with automation to simplify your testing process.

Zrzut ekranu 2025-12-23 155342
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INTELLECT-3 is a frontier-class 100B+ Mixture-of-Experts language model developed by Prime Intellect and trained end-to-end using their large-scale asynchronous RL framework, PRIME-RL. Built on the GLM-4.5-Air base model, INTELLECT-3 combines supervised fine-tuning with long-horizon reinforcement learning across hundreds of verifier-backed environments spanning math, code, science, logic, and agentic tasks.

The model was trained on a high-performance cluster of 512 NVIDIA H200 GPUs across 64 nodes, supported by Prime Intellect’s Sandboxes execution engine, deterministic compute orchestration, and Lustre-backed distributed storage. The result is a model that surpasses many larger systems in reasoning benchmarks while remaining fully open-source.

Prime Intellect released not only the model weights but also the full training recipe: PRIME-RL, Verifiers, the Environments Hub, datasets, and evaluation suites. INTELLECT-3 is positioned as a foundation for organizations seeking to post-train or customize their own frontier-grade models without relying on proprietary AI labs.