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@devopslinks shared a link, 2 weeks, 2 days ago

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Chinese Vulnerability Database: CNVD vs CNNVD Analysis

Investigation profilesCNNVDandCNVDechoCVE. They reveal manual errors and poor machine-readability. China’s July 2021RMSVmandates 48-hour reporting and bans pre-patch disclosure. Mapping gaps exist. The databases published about1.4kentries ahead ofCVE, with lead times measured in months... read more

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@devopslinks shared a link, 2 weeks, 2 days ago

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Building a Least-Privilege AI Agent Gateway for Infrastructure Automation with MCP, OPA, and Ephemeral Runners

Introduces anAI Agent Gateway. It mediates agent requests, validates intent, enforcespolicy-as-code, and isolates execution inephemeral runners. Agents discover tools viaMCP. They submitJSON-RPCcalls and receiveOPAdecisions. Jobs queue and run in short-lived namespaces. Each run carries plan hashes,.. read more

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@devopslinks shared a link, 2 weeks, 2 days ago

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Please stop externalizing your costs directly into my face

SourceHut spent20–100%of weekly time mitigating hyper‑aggressive LLM crawlers. That work caused dozens of short outages and delayed core projects. The crawlers ignorerobots.txt. They hit costly endpoints likegit blame. They scan full git logs and commits. They rotate randomUser‑Agentsand thousands o.. read more

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@devopslinks shared a link, 2 weeks, 2 days ago

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The hunt for truly zero-CVE container images

Chainguard's Factory 2.0 andDriftlessAFrebuild images from source on upstream changes. They produce 2,000+ minimalzero‑CVEimages. Each image includes anSBOMand a cryptographicsignature. Docker'sDHIbuilds onDebianandAlpine. It mirrors Debian'sno‑DSAtriage intoVEX. It also suppresses real CVEs until D.. read more

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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.