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@girishkumarb shared a post, 6 months, 1 week ago

SEO Executive, uCertify

Top 10 Azure Services Every Developer Should Know About in 2025

#Cloud C... #microso... #Microso...

Microsoft Azure continues to dominate cloud computing in 2025, offering developers a wide range of tools to build, deploy, and scale applications efficiently. Key services like App Services, Functions, SQL Database, Cosmos DB, Blob Storage, DevOps, Kubernetes Service, AI Services, Key Vault, and Monitor are essential for modern development. Mastering these helps developers streamline workflows, integrate AI, secure data, and deliver high-performing applications—making Azure knowledge a must-have skill in today’s tech landscape.

Microsoft Azure cloud platform tools and services for developers in 2025

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@idjuric660 shared a post, 6 months, 1 week ago

Technical Content Writer, Mailtrap

Send Emails with Lovable and Mailtrap

#Nocode #email m... #Artific...

Learn how to integrate Mailtrap with your Lovable application to send transactional emails, manage contacts, and create powerful email workflows without writing complex code.

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@laura_garcia shared a post, 6 months, 1 week ago

Software Developer, RELIANOID

🔐 Is your firewall doing enough to protect your applications?

As cyber threats continue to evolve, traditional firewalls that operate at the network or transport layers are no longer sufficient. That’s where Application-Level Firewalls (ALFs) come in — offering deep inspection, application-aware filtering, and real-time protection against sophisticated attacks..

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@laura_garcia shared a post, 6 months, 1 week ago

Software Developer, RELIANOID

Strengthening Operational Technology (OT) Security: What You Need to Know

The Cybersecurity and Infrastructure Security Agency (CISA), alongside 11 international partners, has released the ‘Secure by Demand’ guide to help OT owners and operators integrate robust security measures into their procurement processes. The guide highlights 12 essential security elements that cr..

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@viktoriia-yarosh shared a post, 6 months, 1 week ago

Freshcode

How Grammarly and Kasta Made Ukraine a Global Clojure Hotspot

When developers think of the global adoption of Clojure, they often cite giants like Netflix, Walmart, or Nubank. There is, however, a thriving Clojure ecosystem that has been stealthily powering innovation from an unsuspecting part of the world: Ukraine. With over 633 tech companies and some unicor..

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

Software Developer, RELIANOID

🚀 DevOpsDays arrives in Lima for the first time!

On August 21, 2025, DevOps practitioners and tech leaders will gather to share insights on CI/CD, SRE, DevSecOps, AI/MLOps, and CloudOps. 🔹 RELIANOID will be there—showcasing how our platform empowers secure, scalable, observability-driven DevOps operations. #DevOpsDays#DevOps#SRE#DevSecOps#CloudOps..

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@faun shared a link, 6 months, 2 weeks ago

FAUN.dev()

You can’t UPDATE what you can’t find: vs PostgreSQL

ClickHouse just leveled up. Its new SQL-standardUPDATEis fast—PostgreSQL-fast on single-row changes, and up to4,000×faster on bulk updates. That’s pure columnar speed plus parallelism in the driver’s seat. Yes, both use MVCC. But unlike Postgres, ClickHouse dodges transaction bloat by default. That.. read more

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@faun shared a link, 6 months, 2 weeks ago

FAUN.dev()

Faster Index I/O with NVMe SSDs

A search service (Marginalia Search) gutted its old index internals and dropped memory-mapped B-trees. In their place: adeterministic, block-aligned skip listtuned fordirect reads on NVMe SSDs. It runs on128KB block sizes, usescustom buffer pools, and leans hard onio_uringfor async position lookups.. read more

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@faun shared a link, 6 months, 2 weeks ago

FAUN.dev()

Using AWS ECR as a universal OCI repository

AWS ECR is an OCI repository supporting different types of artifacts, from Docker images to machine learning models, allowing for simplified management and unified access. Users can interact with ECR using CLI tools like ORAS, Helm, and Terraform, providing integration with CI/CD pipelines for effic.. read more

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@faun shared a link, 6 months, 2 weeks ago

FAUN.dev()

Building a web search engine from scratch in two months with 3 billion neural embeddings

An indie dev just went full mad scientist and built a full-stack, transformer-powered search engine—solo. They indexed 280 million pages from scratch with hundreds of crawlers, a fully sharded backend, and serious metal:64 RocksDB nodes,200 CPU cores, and82 TB of SSD. Under the hood: custom HTML pa.. 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.