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@viktoriiagolovtseva shared a post, 2 weeks, 6 days ago

Data Center Migration to Cloud: Step-by-Step Guide

Teams are migrating away fromJira Data Centerdue to its impending end-of-life, and staying put increases risks over time.Atlassian recently announced the end of life for Data Centerand is focusing its investments onJira Cloud, where new features, automation, and improvements to roadmaps and dashboar..

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@laura_garcia shared a post, 2 weeks, 6 days ago

Software Developer, RELIANOID

🚨 𝗡𝗜𝗦𝟮 𝗶𝘀 𝗰𝗵𝗮𝗻𝗴𝗶𝗻𝗴 𝘁𝗵𝗲 𝗰𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗴𝗮𝗺𝗲 𝗶𝗻 𝗘𝘂𝗿𝗼𝗽𝗲

It’s no longer just about protection — it’s about 𝗮𝗰𝗰𝗼𝘂𝗻𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆, 𝗰𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲, 𝗮𝗻𝗱 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗿𝗲𝘀𝗶𝗹𝗶𝗲𝗻𝗰𝗲. ⚠️ Fines up to €10M 🔍 Supplier & partner scrutiny 🛡️ Mandatory risk management The question is: 𝗮𝗿𝗲 𝘆𝗼𝘂 𝗿𝗲𝗮𝗱𝘆? 📖 Read our latest blog to understand the impact and how to prepare: NIS2 Directive and..

Link Xygeni Team

@mashka shared a link, 2 weeks, 6 days ago

Paid Acquisition and Growth Marketing, xygeni

You don’t have a vulnerability problem. You have a prioritization problem.

Most teams today don’t struggle to find vulnerabilities; they struggle to decide what to fix first. With SAST, SCA, secrets, and CI/CD checks all generating signals, the real challenge is prioritization: what’s actually exploitable, what’s reachable, and what can be fixed without breaking things. Instead of relying only on severity, modern teams are shifting toward risk-based remediation, combining exploitability, context, and stability, while reducing noise across tools and automating safe fixes through PRs. If you’re dealing with alert fatigue or slow remediation cycles, this checklist is a practical starting point → https://go.xygeni.io/ai-driven-remediation-risk-prioritization-checklist

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@mikeschinkel started using tool SQLite , 3 weeks ago.

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@mikeschinkel started using tool PostgreSQL , 3 weeks ago.

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@mikeschinkel started using tool MySQL , 3 weeks ago.

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@mikeschinkel started using tool Kubernetes , 3 weeks ago.

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@mikeschinkel started using tool Go , 3 weeks ago.

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@mikeschinkel started using tool GNU/Linux , 3 weeks ago.

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@mikeschinkel started using tool Docker , 3 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.