Prometheus Logging Explained for Developers
Understand how Prometheus logging captures structured metrics, improves query performance, and scales observability in production systems.
Updates and recent posts about AIStor.. Link
Link
@anjali shared a link, 1 year ago
Customer Marketing Manager, Last9
Docker Stop vs Kill: When to Use Each Command
docker stop gives containers time to shut down cleanly. docker kill doesn't—use it only when you need an immediate shutdown.
Story
@ambertalavera shared a post, 1 year ago
Abto Software
Optimizing Research Efficiency with Custom Lab Inventory Management Software Development
Discover how custom lab inventory management software enhances research efficiency with real-time tracking, RFID, cloud access, and AI-powered analytics. Learn from industry use cases and expert insights.
Story
@laura_garcia shared a post, 1 year ago
Software Developer, RELIANOID
🚀 What an incredible few days at VIVA Technology!
We had the chance to connect withso many inspiring people, from innovative startups to global tech leaders. The energy, ideas, and conversations were truly next level. 📸 We’re excited to share some real moments from the event — because it’s not just about technology, it’s about the people behind it...
Link
@anjali shared a link, 1 year ago
Customer Marketing Manager, Last9
Network Latency: Types, Causes, and Fixes
Learn what network latency means, what causes it, and how to fix slowdowns before they start affecting your users.
Story
@laura_garcia shared a post, 1 year ago
Software Developer, RELIANOID
🔐 CISOs are ramping up crisis simulations in 2025!
A recent study shows 74% of CISOs plan to increase their budgets for cyber crisis exercises. Why? The rise in sophisticated attacks and high-profile breaches like those affecting 23andMe, NHS, and Cencora highlight the urgent need for proactive defense strategies. At RELIANOID, we help organizations..
Story FAUN.dev() Team
@eon01 shared a post, 1 year ago
Founder, FAUN.dev
🚀 Meet This Week’s Human: A New Way to Celebrate Builders
Every week, thousands of developers read FAUN to stay sharp, discover tools, and learn what’s trending in Software Engineering.
Now, we’re adding a human touch.
Story
@laura_garcia shared a post, 1 year ago
Software Developer, RELIANOID
✈️ Understanding Airport Software Systems
From check-in to takeoff, modern airports rely on a complex network of integrated IT systems to ensure efficiency, safety, and smooth operations. We’ve visualized this in a new diagram, highlighting key components like: ✅ AODB (Airport Operational Database) ✅ Passenger & baggage handling systems ✅ A..
Link
@faun shared a link, 1 year ago
FAUN.dev()
Why Go is a good fit for agents
Gorules the realm of long-lived, concurrent agent tasks. Its lightning-fast goroutines and petite memory use make Node.js and Python look like clunky dinosaurs trudging through thick mud. And don't get started on itscancellation mechanism—seamless cancelation, zero drama... read more
Link
@faun shared a link, 1 year ago
FAUN.dev()
AI Runbooks for Google SecOps: Security Operations with Model Context Protocol
Google's MCP servers arm SecOps teams with direct control of security tools using LLMs.Now, analysts can skip the fluff and get straight to work—no middleman needed. The system ties runbooks to live data, offeringautomated, role-specific security measures. The result? A fusion of top-tier protocols .. read more
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.
