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@laura_garcia shared a post, 2ย days, 11ย hours ago
Software Developer, RELIANOID

๐—ฅ๐—˜๐—Ÿ๐—œ๐—”๐—ก๐—ข๐—œ๐—— ๐—ฎ๐—น๐—ถ๐—ด๐—ป๐˜€ ๐˜„๐—ถ๐˜๐—ต ๐˜๐—ต๐—ฒ ๐—ฝ๐—ฟ๐—ถ๐—ป๐—ฐ๐—ถ๐—ฝ๐—น๐—ฒ๐˜€ ๐—ผ๐—ณ ๐—œ๐—ฆ๐—ข/๐—œ๐—˜๐—– ๐Ÿฒ๐Ÿฎ๐Ÿฐ๐Ÿฐ๐Ÿฏ

๐Ÿšจ ๐—œ๐—ป๐—ฑ๐˜‚๐˜€๐˜๐—ฟ๐—ถ๐—ฎ๐—น ๐—ฐ๐˜†๐—ฏ๐—ฒ๐—ฟ๐˜€๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐˜๐˜† ๐—ถ๐˜€ ๐—ป๐—ผ ๐—น๐—ผ๐—ป๐—ด๐—ฒ๐—ฟ ๐—ผ๐—ฝ๐˜๐—ถ๐—ผ๐—ป๐—ฎ๐—น โ€” ๐—ถ๐˜'๐˜€ ๐—ณ๐—ผ๐˜‚๐—ป๐—ฑ๐—ฎ๐˜๐—ถ๐—ผ๐—ป๐—ฎ๐—น. We're proud to share that ๐—ฅ๐—˜๐—Ÿ๐—œ๐—”๐—ก๐—ข๐—œ๐—— ๐—ฎ๐—น๐—ถ๐—ด๐—ป๐˜€ ๐˜„๐—ถ๐˜๐—ต ๐˜๐—ต๐—ฒ ๐—ฝ๐—ฟ๐—ถ๐—ป๐—ฐ๐—ถ๐—ฝ๐—น๐—ฒ๐˜€ ๐—ผ๐—ณ ๐—œ๐—ฆ๐—ข/๐—œ๐—˜๐—– ๐Ÿฒ๐Ÿฎ๐Ÿฐ๐Ÿฐ๐Ÿฏ, the ๐˜ช๐˜ฏ๐˜ต๐˜ฆ๐˜ณ๐˜ฏ๐˜ข๐˜ต๐˜ช๐˜ฐ๐˜ฏ๐˜ข๐˜ญ๐˜ญ๐˜บ ๐˜ณ๐˜ฆ๐˜ค๐˜ฐ๐˜จ๐˜ฏ๐˜ช๐˜ป๐˜ฆ๐˜ฅ ๐˜ด๐˜ต๐˜ข๐˜ฏ๐˜ฅ๐˜ข๐˜ณ๐˜ฅ ๐˜ง๐˜ฐ๐˜ณ ๐˜ด๐˜ฆ๐˜ค๐˜ถ๐˜ณ๐˜ช๐˜ฏ๐˜จ ๐˜๐˜ฏ๐˜ฅ๐˜ถ๐˜ด๐˜ต๐˜ณ๐˜ช๐˜ข๐˜ญ ๐˜ˆ๐˜ถ๐˜ต๐˜ฐ๐˜ฎ๐˜ข๐˜ต๐˜ช๐˜ฐ๐˜ฏ ๐˜ข๐˜ฏ๐˜ฅ ๐˜Š๐˜ฐ๐˜ฏ๐˜ต๐˜ณ๐˜ฐ๐˜ญ ๐˜š๐˜บ๐˜ด๐˜ต๐˜ฆ๐˜ฎ๐˜ด (๐˜๐˜ˆ๐˜Š๐˜š). From manufacturing and energy to utilities, go..

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@david6983 started using tool Kubernetes , 3ย days, 9ย hours ago.
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@david6983 started using tool Helm , 3ย days, 9ย hours ago.
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@david6983 started using tool Google Kubernetes Engine (GKE) , 3ย days, 9ย hours ago.
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@david6983 started using tool Flux , 3ย days, 9ย hours ago.
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@laura_garcia shared a post, 3ย days, 11ย hours ago
Software Developer, RELIANOID

๐—ผ๐—ฝ๐—ฒ๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป๐—ฎ๐—น ๐—ฟ๐—ฒ๐˜€๐—ถ๐—น๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐—ฎ๐—ป๐—ฑ ๐˜๐—ต๐—ฒ ๐˜๐—ฟ๐˜‚๐—ฒ ๐—ฐ๐—ผ๐˜€๐˜ ๐—ผ๐—ณ ๐—ฑ๐—ผ๐˜„๐—ป๐˜๐—ถ๐—บ๐—ฒ

๐ŸŽ‰ We're honored to be featured in this excellent article on one of today's most important topics: ๐—ผ๐—ฝ๐—ฒ๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป๐—ฎ๐—น ๐—ฟ๐—ฒ๐˜€๐—ถ๐—น๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐—ฎ๐—ป๐—ฑ ๐˜๐—ต๐—ฒ ๐˜๐—ฟ๐˜‚๐—ฒ ๐—ฐ๐—ผ๐˜€๐˜ ๐—ผ๐—ณ ๐—ฑ๐—ผ๐˜„๐—ป๐˜๐—ถ๐—บ๐—ฒ. It's always rewarding to see industry experts recognize the critical role that intelligent application delivery, high availability, and resilient tr..

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@sancharini shared a post, 4ย days, 4ย hours ago

Building Production-Ready Pipelines with Open Source Automation Tools: Real Patterns That Work

Learn the patterns that separate production-ready pipelines from those that fail. How experienced teams use open source automation tools effectively.

Open Source Automation Tools Modern Engineering Teams Are Building Pipelines Around
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@laura_garcia shared a post, 6ย days, 15ย hours ago
Software Developer, RELIANOID

Network Load Balancer

๐ŸŒ ๐˜Ž๐˜ณ๐˜ฆ๐˜ข๐˜ต ๐˜ฑ๐˜ฆ๐˜ณ๐˜ง๐˜ฐ๐˜ณ๐˜ฎ๐˜ข๐˜ฏ๐˜ค๐˜ฆ ๐˜ด๐˜ต๐˜ข๐˜ณ๐˜ต๐˜ด ๐˜ธ๐˜ช๐˜ต๐˜ฉ ๐˜ช๐˜ฏ๐˜ต๐˜ฆ๐˜ญ๐˜ญ๐˜ช๐˜จ๐˜ฆ๐˜ฏ๐˜ต ๐˜ต๐˜ณ๐˜ข๐˜ง๐˜ง๐˜ช๐˜ค ๐˜ฅ๐˜ช๐˜ด๐˜ต๐˜ณ๐˜ช๐˜ฃ๐˜ถ๐˜ต๐˜ช๐˜ฐ๐˜ฏ. A ๐—ก๐—ฒ๐˜๐˜„๐—ผ๐—ฟ๐—ธ ๐—Ÿ๐—ผ๐—ฎ๐—ฑ ๐—•๐—ฎ๐—น๐—ฎ๐—ป๐—ฐ๐—ฒ๐—ฟ helps organizations maximize availability, eliminate bottlenecks, and keep critical applications running smoothlyโ€”even under heavy traffic or unexpected failures. In our latest article, we explain how Layer 4 l..

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

SOC2 compliance

๐Ÿ” ๐—ฆ๐—ข๐—– ๐Ÿฎ alignment is about trust, resilience, and doing security right by design. At ๐—ฅ๐—˜๐—Ÿ๐—œ๐—”๐—ก๐—ข๐—œ๐——, our load balancing and application delivery platform is aligned with the ๐—ฆ๐—ข๐—– ๐Ÿฎ ๐—ง๐—ฟ๐˜‚๐˜€๐˜ ๐—ฆ๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฐ๐—ฒ๐˜€ ๐—–๐—ฟ๐—ถ๐˜๐—ฒ๐—ฟ๐—ถ๐—ฎโ€”๐—ฐ๐—ผ๐˜ƒ๐—ฒ๐—ฟ๐—ถ๐—ป๐—ด ๐—ฆ๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐˜๐˜†, ๐—”๐˜ƒ๐—ฎ๐—ถ๐—น๐—ฎ๐—ฏ๐—ถ๐—น๐—ถ๐˜๐˜†, ๐—–๐—ผ๐—ป๐—ณ๐—ถ๐—ฑ๐—ฒ๐—ป๐˜๐—ถ๐—ฎ๐—น๐—ถ๐˜๐˜†, ๐—ฃ๐—ฟ๐—ผ๐—ฐ๐—ฒ๐˜€๐˜€๐—ถ๐—ป๐—ด ๐—œ๐—ป๐˜๐—ฒ๐—ด๐—ฟ๐—ถ๐˜๐˜†, ๐—ฎ๐—ป๐—ฑ ๐—ฃ๐—ฟ๐—ถ๐˜ƒ๐—ฎ๐—ฐ๐˜†. From encryption ..

Unsloth is an open-source toolkit for training and fine-tuning large language models faster and with less memory than a standard Hugging Face stack. Its core library replaces PyTorch's default autograd with custom backpropagation kernels written in OpenAI's Triton language, which is where most of its speed and memory savings come from. It supports LoRA, QLoRA, full fine-tuning, reinforcement learning, pretraining, and 4-bit, 16-bit, and FP8 training, across more than 500 text, vision, audio, and embedding models.

The practical draw is hardware reach. QLoRA workflows in Unsloth let you fine-tune an 8B model on a single 12 GB consumer GPU, and the project headlines roughly 2x faster training with about 70 percent less VRAM versus baseline implementations, though the exact figures vary by model, GPU, and config. A 2026 update added faster mixture-of-experts training, with models like Qwen3-30B-A3B fine-tunable on about 17.5 GB of VRAM. It runs on NVIDIA (including Blackwell and DGX Spark), AMD, and Intel GPUs, with free Colab and Kaggle notebooks for trying it without local hardware.

It fits cleanly into the local-AI workflow. Unsloth integrates with Hugging Face transformers and TRL, and uses llama.cpp to save and run models, exporting to GGUF for Ollama or LM Studio as well as safetensors. As of 2026 it also ships Unsloth Studio, a local no-code GUI that covers the full lifecycle from dataset creation to training to running and comparing GGUF and safetensors models, with tool-calling, web search, and an OpenAI-compatible API, all running offline on Mac and Windows, with the core library under the Apache 2.0 license.