Updates and recent posts about AIStor..

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@devopslinks shared a link, 2 months, 1 week ago

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The story of how we almost got hacked

Team Invictus caught a BEC attempt using WeTransfer to slip in a fake Microsoft 365 login page powered byEvilProxy. Classic Adversary-in-the-Middle move, but dressed up with a slick delivery package. Digging deeper, the team mapped the attacker’s setup and found something bigger: a credential grab c.. read more

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

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Agent Sandbox Brings Kernel-Level Guardrails to AI Agents on Kubernetes

#Agent S... #gVisor #AI agen... #GKE #kuberne...

Agent Sandbox, a new Kubernetes primitive, was introduced at KubeCon NA 2025 to enhance AI agent management on Kubernetes and Google Kubernetes Engine.

Agent Sandbox Brings Kernel-Level Guardrails to AI Agents on Kubernetes

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

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AWS Unveils Graviton5: A 192-Core Leap in Cloud Performance and Efficiency

#M9g ins... #Nitro S... #EC2 #aws #Gravito...

AWS introduces Graviton5-based EC2 M9g instances, boosting performance by 25% and enhancing scalability while reducing costs.

AWS Unveils Graviton5: A 192-Core Leap in Cloud Performance and Efficiency

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

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Tor Goes Rust: Introducing Arti, a New Foundation for the Future of Tor

#Rust #Securit... #Tor #Arti #cryptog...

The development of "Arti," a Rust-based Tor implementation funded by Zcash, aims to enhance security and efficiency by addressing the limitations of the current C-based Tor.

Tor Goes Rust: Introducing Arti, a New Foundation for the Future of Tor

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@varbear added a new tool Arti , 2 months, 1 week ago.

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@varbear added a new tool Tor , 2 months, 1 week ago.

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

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Gemini Deep Research Is Now Programmable Through a New API

#Gemini ... #Interac... #DeepSea... #financi... #automat...

The enhanced Gemini Deep Research agent is now available via API, enabling developers to integrate advanced research capabilities into applications, with the open-sourcing of DeepSearchQA for evaluating complex tasks.

Gemini Deep Research Is Now Programmable Through a New API

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@kala added a new tool Vertex AI , 2 months, 1 week ago.

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@kala added a new tool Gemini 3 , 2 months, 1 week ago.

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

FAUN.dev()

GitHub Copilot Adds GPT-5.2 With Long-Context and UI Generation

#GPT-5.2 #Copilot #GitHub ... #github #OpenAI

OpenAI unveils GPT-5.2 for GitHub Copilot, enhancing software engineering with improved long-context reasoning and UI generation, integrated with Microsoft Azure and NVIDIA.

GitHub Copilot Adds GPT-5.2 With Long-Context and UI Generation

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.