Updates and recent posts about AIStor..

Posts
Description

Link

@faun shared a link, 1 year ago

FAUN.dev()

A Journey Through Kafkian SplitDNS in a Multitenant Kubernetes Offering

SCHIPfaced off with tenant demands for serverless Kafka. Their weapon of choice? A crafty DNS trick usingCoreDNSand a few clevernode-local DNSadjustments. They kept multitenancy alive and kicking without wearing out the ops team. Nice move... read more

Link

@faun shared a link, 1 year ago

FAUN.dev()

GitOps for Kubernetes With Nixidy and ArgoCD

Nixidyturns Kubernetes YAMLs into sleek, declarative Nix setups. It offers a robust, repeatable config flow—even for those complex Helm charts. Spice up your deployment by pairingArgoCDwith encrypted secrets viasops-secrets-operator. Now you can wrangle sensitive data in Git with style—and security... read more

Link

@faun shared a link, 1 year ago

FAUN.dev()

Kubernetes 1.33: Resizing Pods Without the Drama (Finally!)

Kubernetes 1.33brings in-place pod vertical scaling, allowing you to adjust CPU and memory without restarting pods, a game-changer for seamless resource management in production workloads. This feature simplifies vertical pod autoscaling especially for stateful workloads like databases... read more

Link

@faun shared a link, 1 year ago

FAUN.dev()

The Ultimate Guide to Running Kubernetes in a Home Lab

K3sandMicroK8sshine in makeshift home labs with minimal hardware. Throw inLonghornfor storage andVelerofor backup bliss. Now that's a recipe for tech nirvana... read more

Link

@faun shared a link, 1 year ago

FAUN.dev()

Amazon EKS Pod Identity streamlines cross account access

Amazon EKS Pod Identityjust got an upgrade. Now you can tap into cross-account access usingIAM role chaining. Forget intricate setups and tiresome code changes. Drop in source and target IAM roles, and let EKS juggle temp credentials at runtime. It's innovation doing a happy dance... read more

Link

@faun shared a link, 1 year ago

FAUN.dev()

NSEnter and Kubernetes

nsenteris your backstage pass to aKubernetesnode. It plays with Linux namespaces, crashing through isolation walls for a direct look inside. Summon it withPID1 and proper permissions, and you're deep in the node's core. No middleman required... read more

Link

@faun shared a link, 1 year ago

FAUN.dev()

Interesting Kubernetes application demos

Kubeappsis your backstage pass to deploying and controllingK8sapps with style. Dive into a treasure chest ofHelmcharts ready to roll. For those looking to jazz up a demo, unleashKubedoomorKubevaders. Obliteratepodsfor stress-testing, or just because you can. Craving some retro-futuristic fun? Check .. read more

Link

@faun shared a link, 1 year ago

FAUN.dev()

F5 Unleashes Innovation with Powerful New AI Capabilities on BIG-IP Next for Kubernetes on NVIDIA BlueField-3 DPUs

TheModel Context Protocol (MCP)just crashed the party, turning heads and flipping tables with its focus on tailor-made AI setups. EnterAI factoriesandNeoclouds—souped-up cloud havens crafted to power-hungry AI demands. Handle with care, because these bad boys redefine what's possible... read more

Link

@faun shared a link, 1 year ago

FAUN.dev()

How We Designed Model Runner and What’s Next

Docker's just unleashed a new gadget with Desktop4.40. Meet theModel Runner, your ticket to running AI models on your local machine. Imagine it as the Peacekeeper of container-host diplomacy. It’s powered byllama.cppand can ride GPUs like a pro skater. Oh, and it plays nice with theOpenAI API. Model.. read more

Link

@faun shared a link, 1 year ago

FAUN.dev()

State of App Dev: Security

Securityisn’t just for the IT crowd anymore. Everyone's on duty.Only 1%of developers bother to look the other way. A mere20%of organizations throw money at outsiders to handle it. The real trip wire? Planning. It derails teams faster than you'd believe... read more

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.