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

Strengthen Your MFA with Google Authenticator and RELIANOID

🔐 Strengthen Your MFA with Google Authenticator and RELIANOID At RELIANOID, we take authentication seriously. We've just published a new technical guide on how to integrate Google Authenticator into the RELIANOID MFA Portal, using Active Directory or LDAP to manage user secrets. ✅ Understand TOTP vs..

2FA with AD_LDAP and Google Authenticator
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@roock started using tool Terraform , 2 weeks, 5 days ago.
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@roock started using tool Python , 2 weeks, 5 days ago.
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@roock started using tool Puppet , 2 weeks, 5 days ago.
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@habiledata shared a post, 2 weeks, 6 days ago
HabileData

5 Product Data Quality Issues in Multi-Channel Retail and How to Address Them

Weaknesses in product data expose themselves quickly in a multi-channel retail environment. Define a master schema, maintain control of your inventory and pricing via rules, continuously monitor for compliance, and connect performance metrics to the precise changes made for each SKU.

fixing-product-data-at-scale-5-issues-that-hurt-retail-listings
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@laura_garcia shared a post, 2 weeks, 6 days ago
Software Developer, RELIANOID

RELIANOID NIS360 Alignment & Compliance

🔐 RELIANOID NIS360 Alignment & Compliance At RELIANOID, we align our security strategy with the ENISA NIS360 Cyber Risk framework—helping organizations in critical sectors strengthen resilience and improve cybersecurity maturity. From governance and risk management to incident readiness and supply..

enisa nis360 relianoid
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@hitechdigital shared a post, 3 weeks ago
Business Consulting, HitechDigital Solutions

How SolidWorks Sheet Metal CAD Drafting Delivers Shop-Ready Drawings

Fabricating sheet metal requires documentation that describes the designer’s intent of how to manufacture the part. By linking parametric 3D models directly to manufacturing documentation viasheet metal CAD draftingin SolidWorks, each dimension, bend note, and flat pattern is the same as what has be..

How SolidWorks Sheet Metal CAD Drafting Delivers Shop-Ready Drawings
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@shurup shared a post, 3 weeks ago
@palark

Kubernetes 1.36 new alpha features

Kubernetes

Kubernetes v1.36 will be released in 2 weeks. What will change? Here are prominent newly introduced alpha features in the v1.36 release: - Workload-aware preemption. Groups of related Pods are now treated as a single entity. - Topology-aware workload scheduling, allowing you to place a group of Pods..

kubernetes-v1.36-release
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@laura_garcia shared a post, 3 weeks ago
Software Developer, RELIANOID

𝗡𝗲𝘁𝘄𝗼𝗿𝗸 𝗔𝘁𝘁𝗮𝗰𝗸𝘀 𝟭𝟬𝟭: 𝗪𝗵𝘆 𝗕𝗼𝘁𝗻𝗲𝘁𝘀 𝗔𝗿𝗲 𝗮 𝗠𝗮𝗷𝗼𝗿 𝗧𝗵𝗿𝗲𝗮𝘁

🔐 𝗡𝗲𝘁𝘄𝗼𝗿𝗸 𝗔𝘁𝘁𝗮𝗰𝗸𝘀 𝟭𝟬𝟭: 𝗪𝗵𝘆 𝗕𝗼𝘁𝗻𝗲𝘁𝘀 𝗔𝗿𝗲 𝗮 𝗠𝗮𝗷𝗼𝗿 𝗧𝗵𝗿𝗲𝗮𝘁 Cyberattacks are evolving fast. Among the most common: MITM DDoS IP & DNS Spoofing Rootkits Botnets ⚠️ 𝗕𝗼𝘁𝗻𝗲𝘁𝘀 𝘀𝘁𝗮𝗻𝗱 𝗼𝘂𝘁—networks of infected devices used for DDoS, data theft, and large-scale attacks. 🛡️ 𝗛𝗼𝘄 𝗥𝗘𝗟𝗜𝗔𝗡𝗢𝗜𝗗 𝗣𝗿𝗼𝘁𝗲𝗰𝘁𝘀 𝗬𝗼𝘂 Traffic filter..

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@vaibhavgupta shared a post, 3 weeks, 1 day ago

Awesome Shadcn Tooltip Components

Next.js React tailwindcss TypeScript

The blog introduces 7 reusable tooltip components built with shadcn/ui for React apps - focused on accessibility, customization, and real-world UI use cases.

Shadcn Tooltip Components
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.