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@basit001 created an organization Levelop.dev , 1 week, 6 days ago.

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@laura_garcia shared a post, 2 weeks ago

Software Developer, RELIANOID

𝟭𝟴𝟰 𝗺𝗶𝗹𝗹𝗶𝗼𝗻 𝗰𝗿𝗲𝗱𝗲𝗻𝘁𝗶𝗮𝗹 𝗿𝗲𝗰𝗼𝗿𝗱𝘀 exposure

A 𝗽𝘂𝗯𝗹𝗶𝗰𝗹𝘆 𝗲𝘅𝗽𝗼𝘀𝗲𝗱 𝗱𝗮𝘁𝗮𝗯𝗮𝘀𝗲 containing 𝟭𝟴𝟰 𝗺𝗶𝗹𝗹𝗶𝗼𝗻 𝗰𝗿𝗲𝗱𝗲𝗻𝘁𝗶𝗮𝗹 𝗿𝗲𝗰𝗼𝗿𝗱𝘀 has highlighted once again 𝙝𝙤𝙬 𝙛𝙧𝙖𝙜𝙞𝙡𝙚 𝙙𝙖𝙩𝙖 𝙥𝙧𝙤𝙩𝙚𝙘𝙩𝙞𝙤𝙣 𝙘𝙖𝙣 𝙗𝙚 𝙬𝙞𝙩𝙝𝙤𝙪𝙩 𝙥𝙧𝙤𝙥𝙚𝙧 𝙨𝙚𝙘𝙪𝙧𝙞𝙩𝙮 𝙘𝙤𝙣𝙩𝙧𝙤𝙡𝙨. From social media and financial services to healthcare and government accounts, the scale of this exposure demonstrates why 𝗽𝗿𝗼𝗮𝗰𝘁𝗶𝘃𝗲 ..

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@hitechanalytics started using tool DataTables , 2 weeks ago.

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@laura_garcia shared a post, 2 weeks ago

Software Developer, RELIANOID

𝗗𝘂𝗯𝗹𝗶𝗻 𝗧𝗲𝗰𝗵 𝗦𝘂𝗺𝗺𝗶𝘁 𝟮𝟬𝟮𝟲

Excited to announce that 𝗥𝗘𝗟𝗜𝗔𝗡𝗢𝗜𝗗 will be attending the 𝗗𝘂𝗯𝗹𝗶𝗻 𝗧𝗲𝗰𝗵 𝗦𝘂𝗺𝗺𝗶𝘁 𝟮𝟬𝟮𝟲 on May 27–28 in Dublin! Celebrating its 10th anniversary, this global tech event brings together innovators, startups, investors, and industry leaders from over 70 countries to 𝘦𝘹𝘱𝘭𝘰𝘳𝘦 𝘵𝘩𝘦 𝘧𝘶𝘵𝘶𝘳𝘦 𝘰𝘧 𝘵𝘦𝘤𝘩𝘯𝘰𝘭𝘰𝘨𝘺. 🚀 From A..

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@laura_garcia shared a post, 2 weeks, 2 days ago

Software Developer, RELIANOID

New Linux kernel vulnerability disclosed: CVE-2026-46300 “Fragnesia”

🔐 New Linux kernel vulnerability disclosed: CVE-2026-46300 “Fragnesia” A new local privilege escalation flaw affecting Linux XFRM/IPsec components has been identified, related to the same vulnerability class as Dirty Frag and Copy Fail. We’ve published a brief impact assessment and mitigation guidan..

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@laura_garcia shared a post, 2 weeks, 2 days ago

Software Developer, RELIANOID

𝗔𝗶𝗿𝗽𝗼𝗿𝘁 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀

✈️ 𝗔𝗶𝗿𝗽𝗼𝗿𝘁 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀 depend on 𝗵𝗶𝗴𝗵𝗹𝘆 𝗮𝘃𝗮𝗶𝗹𝗮𝗯𝗹𝗲, 𝘀𝗲𝗰𝘂𝗿𝗲, 𝗮𝗻𝗱 𝘀𝗰𝗮𝗹𝗮𝗯𝗹𝗲 𝗜𝗧 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝘀. From AODB platforms and baggage handling to ATC systems and passenger services, every critical airport application requires uninterrupted performance. In our latest article, we explore how 𝗥𝗘𝗟𝗜𝗔𝗡𝗢𝗜𝗗 helps ensu..

high_availiability_relianoid_solutions_airports

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@varbear shared a link, 2 weeks, 3 days ago

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Formatting an entire 25 million line codebase overnight: the rubyfmt story

Stripe's Developer Productivity team rolled out rubyfmt, a Rust-based zero-config Ruby autoformatter, across 25 million lines of Ruby in one Saturday morning in 2024, after the project had been in flight since 2018 as Fable Tales's personal OSS work. The hard parts were Ruby itself (no Ruby parser e.. read more

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@varbear shared a link, 2 weeks, 3 days ago

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Why I'm leaving GitHub for Forgejo

The Dutch Ministry of the Interior launched code.overheid.nl, a self-hosted Forgejo instance for government source code. This move was driven by the need to own and control the platform where code is published. Forgejo was chosen over GitLab for its open-source nature and alignment with the ministry.. read more

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@varbear shared a link, 2 weeks, 3 days ago

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Making your own programming language is easier than you think (but also harder)

A game developer explains how he built a low-level modding language, including sandbox constraints, an AArch64 JIT, and a small C++ compiler... read more

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@varbear shared a link, 2 weeks, 3 days ago

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Replacing a 3 GB SQLite database with a 10 MB FST (finite state transducer) binary

Andrew Quinn shipped Taskusanakirja (tsk), a Finnish-English pocket dictionary with search-as-you-type, originally backed by a trie for ~400k base words plus a 3 GB SQLite FTS database to cover the 40-60M inflected forms that Finnish's agglutinative morphology demands. Reaching for BurntSushi'sIndex.. read more

Vertex AI is Google Cloud’s end-to-end machine learning and generative AI platform, designed to help teams build, deploy, and operate AI systems reliably at scale. It unifies data preparation, model training, evaluation, deployment, and monitoring into a single managed environment, reducing operational complexity while supporting advanced AI workloads.

Vertex AI supports both custom models and foundation models, including Google’s Gemini model family. It enables organizations to fine-tune models, run large-scale inference, orchestrate agentic workflows, and integrate AI into production systems with strong security, governance, and observability controls.

The platform includes tools for AutoML, custom training with TensorFlow and PyTorch, managed pipelines, feature stores, vector search, and online and batch prediction. For generative AI use cases, Vertex AI provides APIs for text, image, code, multimodal generation, embeddings, and agent-based systems, including support for Model Context Protocol (MCP) integrations.

Built for enterprise environments, Vertex AI integrates deeply with Google Cloud services such as BigQuery, Cloud Storage, IAM, and VPC, enabling secure data access and compliance. It is widely used across industries like finance, healthcare, retail, and science for applications ranging from recommendation systems and forecasting to autonomous research agents and AI-powered products.