Angular vs React: Which Framework Is Better for Web Development?
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Updates and recent posts about AIStor..ย Activity
@smh started using tool Kubernetes , 1ย week, 4ย days ago.
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@smh started using tool Amazon Web Services , 1ย week, 4ย days ago.
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@viktoriiagolovtseva shared a post, 1ย week, 5ย days ago
How to Make Your Jira Sprint Planning Really Agile
You know the drill:build a product roadmap in Jira, create your product backlog, review it, update the user stories, come up with a sprint goal before the meeting, and finally, review every story to decide which ones need to be completed this sprint. Easier said than done, right? Well-planned sprint..
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@laura_garcia shared a post, 1ย week, 5ย days ago
Software Developer, RELIANOID
Not all ๐ฑ๐ถ๐ด๐ถ๐๐ฎ๐น ๐ฐ๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ฒ๐ are created equal
๐จ Not all ๐ฑ๐ถ๐ด๐ถ๐๐ฎ๐น ๐ฐ๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ฒ๐ are created equal. From ๐๐ฉ, ๐ข๐ฉ, ๐๐ฉ ๐๐ผ ๐บ๐ง๐๐ฆ ๐ฐ๐น๐ถ๐ฒ๐ป๐ ๐ฐ๐ฒ๐ฟ๐๐ and ๐ฐ๐ผ๐ฑ๐ฒ ๐๐ถ๐ด๐ป๐ถ๐ป๐ด, each plays a different role in your security posture. ๐ Encryption is just the beginning: โ Identity validation โ Trust chains (Root โ Intermediate โ Leaf) โ Secure software delivery โ Zero Trust..
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@sanjayjoshi shared a post, 1ย week, 5ย days ago
8+ Shadcn Combobox Components for React & Nextjs Projects
Shadcn combobox components are more than just UI elements theyโre productivity boosters. They simplify complex selections, enhance usability, and make your applications feel fast and modern.
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@rafidbottler created an organization WPWeb Infotech , 1ย week, 5ย days ago.
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 AIStorโs 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 โ from unstructured storage for application data to structured table storage for analytics, as well as AI training and inference datasets โ within a consistent object-native architecture. It supports multi-tenant environments and can be deployed across on-premises, cloud, and hybrid infrastructure.
