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@laura_garcia shared a post, 2 months, 1 week ago

Software Developer, RELIANOID

🚀 FinovateEurope 2026

📍 London, UK | 🗓️ 10–11 February 2026 Market-ready innovations. Executive-level networking. Inspiring insights. FinovateEurope brings together banking leaders, fintech innovators, investors, and technology providers to shape the future of financial services at a critical moment for the global fint..

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@jordanunix posted an event DevOpsDayLA at SCALE23x The Southern California Linux and Open Source Expo by DevOpsDayLA , 2 months, 1 week ago.

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@kala shared an update, 2 months, 1 week ago

FAUN.dev()

This Is the First AI That Helped Build Itself - Meet GPT-5.3-Codex

#cyberse... #GPT-5.3... #coding ... #SWE-Ben... #Termina...

GPT-5.3-Codex, an advanced model, enhances coding performance and reasoning, operating 25% faster than its predecessor. It excels in industry benchmarks, supports the software lifecycle, and can autonomously build complex applications. The model is available on multiple platforms with plans for API access.

This Is the First AI That Helped Build Itself - Meet GPT-5.3-Codex

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@kala added a new tool GPT-5.3-Codex , 2 months, 1 week ago.

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

Software Developer, RELIANOID

🔐 CISO Sydney 2026

📍 Sydney, Australia | 🗓 10–11 February 2026 CISO Sydney returns for its 5th edition, bringing together New South Wales’ most senior Information Security leaders to explore how cybersecurity can truly enable business growth. From AI-driven threats and shared risk responsibility to culture-first secur..

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@nelly96 added a new tool GPTHuman , 2 months, 2 weeks ago.

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

Software Developer, RELIANOID

Want to deploy RELIANOID Load Balancer Enterprise Edition v8 on AWS using Terraform in a clean, automated way?

We’ve got you covered. In this step-by-step guide, you’ll learn how to: Use the official Terraform module from the Terraform Registry Automatically provision VPC, subnet, security groups, and EC2 Deploy the RELIANOID Enterprise Edition AMI Access the VM via SSH and Web GUI Easily destroy all resourc..

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@sancharini shared a post, 2 months, 2 weeks ago

Interpreting Software Testing Metrics Beyond Dashboards

Learn how to interpret software testing metrics beyond dashboards, turning raw data into actionable insights that improve release decisions and reduce risk.

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@idjuric660 shared a post, 2 months, 2 weeks ago

Technical Content Writer, Mailtrap

5 Best Email API for Python Developers Tested & Compared

The best email APIs for Python developers are Mailtrap, Mailgun, SendGrid, Amazon SES, and Postmark. SDK quality & framework compatibility All five providers offerPythonSDKs and they’re compatible with popular frameworks. I tested each withDjango,Flask, and FastAPI to assess real-world integration. ..

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@jordanunix created an organization DevOpsDayLA , 2 months, 2 weeks ago.

AIStor is an enterprise-grade, high-performance object storage platform built for modern data workloads such as AI, machine learning, analytics, and large-scale data lakes. It is designed to handle massive datasets with predictable performance, operational simplicity, and hyperscale efficiency, while remaining fully compatible with the Amazon S3 API. AIStor is offered under a commercial license as a subscription-based product.

At its core, AIStor is a software-defined, distributed object store that runs on commodity hardware or in containerized environments like Kubernetes. Rather than being limited to traditional file or block interfaces, it exposes object storage semantics that scale from petabytes to exabytes within a single namespace, enabling consistent, flat addressing of vast datasets. It is engineered to sustain very high throughput and concurrency, with examples of multi-TiB/s read performance on optimized clusters.

AIStor is optimized specifically for AI and data-intensive workloads, where throughput, low latency, and horizontal scalability are critical. It integrates broadly with modern AI and analytics tools, including frameworks such as TensorFlow, PyTorch, Spark, and Iceberg-style table engines, making it suitable as the foundational storage layer for pipelines that demand both performance and consistency.

Security and enterprise readiness are central to AIStor’s design. It includes capabilities like encryption, replication, erasure coding, identity and access controls, immutability, lifecycle management, and operational observability, which are important for mission-critical deployments that must meet compliance and data protection requirements.

AIStor is positioned as a platform that unifies diverse data workloads — from unstructured storage for application data to structured table storage for analytics, as well as AI training and inference datasets — within a consistent object-native architecture. It supports multi-tenant environments and can be deployed across on-premises, cloud, and hybrid infrastructure.