Sidecar or Agent for OpenTelemetry: How to Decide
Sidecar or agent? See when per-service isolation beats node-level efficiency, and how gateways fit into a scalable OTel pipeline.
Updates and recent posts about AIStor.. Link
Story
@laura_garcia shared a post, 3 months, 4 weeks ago
Software Developer, RELIANOID
In case you missed this update 👇
🌏 Asia Hits 50% IPv6 Capability — A Global Milestone 📶 Asia has officially crossed a key internet threshold: half of all systems in the region are now IPv6 capable, making it a global front-runner in IPv6 adoption. 📌 Why it matters: 🌐 India (78.1%) and China (810M users) are powering this impressive..
Story Xygeni Team
@mashka shared a post, 3 months, 4 weeks ago
Paid Acquisition and Growth Marketing, xygeni
Why Tool Sprawl Is Hurting AppSec More Than Helping It
Why Tool Sprawl Is Killing AppSec Productivity?
Modern engineering teams ship software faster than ever, but security tools haven’t kept up. Instead of helping, they often slow everything down. With multiple scanners, dashboards, and sources of truth, AppSec has become noisy and fragmented.
Story
@laura_garcia shared a post, 3 months, 4 weeks ago
Software Developer, RELIANOID
Safeguarding Protected Health Information with RELIANOID 🛡️
RELIANOID aligns its organizational practices and Load Balancer platform with the HIPAA Security and Privacy Rule safeguards, ensuring the protection of electronic Protected Health Information (ePHI). ✅ Administrative, physical, and technical safeguards in place ✅ Encryption (TLS v1.2+, AES-256), RB..
Link
@anjali shared a link, 3 months, 4 weeks ago
Customer Marketing Manager, Last9
OTel Updates: Consistent Probability Sampling Fixes Fragmented Traces
One sampling decision, propagated everywhere. OpenTelemetry's Consistent Probability Sampling fixes fragmented traces across services.
Story
@laura_garcia shared a post, 3 months, 4 weeks ago
Software Developer, RELIANOID
🚀 RELIANOID at DevOpsDays Istanbul 2025 – Building the Future of DevOps Together
🗓 November 1st, 2025 | 📍 Istanbul, Türkiye The DevOps world never stops evolving — and DevOpsDays Istanbul 2025 is where innovation, collaboration, and continuous improvement meet. Join RELIANOID and the global DevOps community to explore: 🔹 Continuous Delivery & Automation – Streamlining pipelines ..
Link
@varbear shared a link, 3 months, 4 weeks ago
FAUN.dev()
Build Your Own Database
LSM trees fix the mess naive key-value stores run into. They blendin-memory sorted indexeswithappend-only disk filesto keep things snappy. Writes get logged, not scattered. Reads stay fast. When files pile up,compaction and segmentingkick in to keep storage lean. This is a rewrite of the storage pla.. read more
Link
@varbear shared a link, 3 months, 4 weeks ago
FAUN.dev()
100X Faster: How We Supercharged Netflix Maestro’s Workflow Engine
The Maestro engine has been revamped for jaw-dropping improvement: a speed boost of100Xwith overhead slashed from seconds to milliseconds. The groundbreaking redesign delivers massive performance gains, solving past workflow development hurdles and elevating user experiences sky-high!.. read more
Link
@varbear shared a link, 3 months, 4 weeks ago
FAUN.dev()
How I Reversed Amazon's Kindle Web Obfuscation Because Their App Sucked
A developer cracked Kindle Cloud Reader’s font obfuscation, sidestepping randomized glyph swaps withSVG renderingandSSIM-powered perceptual hashingto rebuild actual EPUBs. Amazon rotates font mappings every five pages, using finicky micro-paths to jam scrapers and derail OCR. It wasn’t enough. Syste.. read more
Link
@varbear shared a link, 3 months, 4 weeks ago
FAUN.dev()
Discussion of the Benefits and Drawbacks of the Git Pre-Commit Hook
Pre-commit hooks catch secrets and fix formatting before bad stuff hits your repo. But if they’re clunky or slow, devs bail. Tools likePre-Commit,Husky, anddevenvare trying to fix that.devenvstands out—hooks are baked right into your Nix env, no extra glue scripts... 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.
