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@koukibadr shared a post, 1ย month, 3ย weeks ago
Mobile Developer, Nventive

Optimizing Performance in Android Apps with Kotlin

Optimizing the performance of your Android applications is crucial for providing a smooth and responsive user experience. Kotlin, with its concise syntax and powerful features, offers several ways to enhance the performance of your apps. In this article, we'll explore various techniques and best pra..

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@laura_garcia shared a post, 1ย month, 4ย weeks ago
Software Developer, RELIANOID

๐—–๐—ต๐—ถ๐—น๐—ฒ ๐—ฎ๐—ฐ๐—ฐ๐—ฒ๐—น๐—ฒ๐—ฟ๐—ฎ๐˜๐—ฒ๐˜€ ๐—ถ๐˜๐˜€ ๐˜๐—ฒ๐—ฐ๐—ต๐—ป๐—ผ๐—น๐—ผ๐—ด๐—ถ๐—ฐ๐—ฎ๐—น ๐—น๐—ฒ๐—ฎ๐—ฝ

๐—–๐—ต๐—ถ๐—น๐—ฒ ๐—ฎ๐—ฐ๐—ฐ๐—ฒ๐—น๐—ฒ๐—ฟ๐—ฎ๐˜๐—ฒ๐˜€ ๐—ถ๐˜๐˜€ ๐˜๐—ฒ๐—ฐ๐—ต๐—ป๐—ผ๐—น๐—ผ๐—ด๐—ถ๐—ฐ๐—ฎ๐—น ๐—น๐—ฒ๐—ฎ๐—ฝ๐Ÿš€ More than ๐Ÿณ๐Ÿฌ% ๐™ค๐™› ๐˜พ๐™๐™ž๐™ก๐™š๐™–๐™ฃ ๐™ค๐™ง๐™œ๐™–๐™ฃ๐™ž๐™ฏ๐™–๐™ฉ๐™ž๐™ค๐™ฃ๐™จ are actively driving projects around ๐—”๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ถ๐—ฎ๐—น ๐—œ๐—ป๐˜๐—ฒ๐—น๐—น๐—ถ๐—ด๐—ฒ๐—ป๐—ฐ๐—ฒ, ๐—ฎ๐—ฑ๐˜ƒ๐—ฎ๐—ป๐—ฐ๐—ฒ๐—ฑ ๐—ฐ๐˜†๐—ฏ๐—ฒ๐—ฟ๐˜€๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐˜๐˜†, ๐—ฎ๐˜‚๐˜๐—ผ๐—บ๐—ฎ๐˜๐—ถ๐—ผ๐—ป, ๐—ฎ๐—ป๐—ฑ ๐—ป๐—ฒ๐˜…๐˜-๐—ด๐—ฒ๐—ป๐—ฒ๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ฐ๐—ผ๐—ป๐—ป๐—ฒ๐—ฐ๐˜๐—ถ๐˜ƒ๐—ถ๐˜๐˜†. This rapid transformationโ€”supported by strong public policies, 5G deployment, and long-..

Blog_Chileโ€™s Technological Acceleration_RELIANOID
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@alok00k shared a post, 1ย month, 4ย weeks ago

Integration Testing: The Bridge Between Unit Tests and Real-World Software Reliability

#Testingย  #integra...ย  #sdlcย  #keployย  #automat...ย 

Integration testing verifies that different parts of an applicationโ€”such as APIs, databases, and servicesโ€”work correctly together. It helps catch real-world issues that unit tests miss, like broken data flow or failed service communication. Essential for modern apps, especially microservices, it improves reliability, reduces production bugs, and should be automated in CI/CD pipelines.

ChatGPT Image Apr 27, 2026, 02_56_29 PM
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@sancharini shared a post, 1ย month, 4ย weeks ago

How Software Development Tools Influence Code Quality Over Time?

Learn how software development tools shape code quality over time by enforcing standards, automating testing, and improving developer workflows. Discover key factors that impact long-term software reliability.

Software Development Tools in 2026
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@koukibadr shared a link, 1ย month, 4ย weeks ago
Mobile Developer, Nventive

Code Templating

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@laura_garcia shared a post, 1ย month, 4ย weeks ago
Software Developer, RELIANOID

๐—›๐—ถ๐—ด๐—ต ๐—”๐˜ƒ๐—ฎ๐—ถ๐—น๐—ฎ๐—ฏ๐—ถ๐—น๐—ถ๐˜๐˜† ๐—ฎ๐—น๐—ผ๐—ป๐—ฒ ๐˜„๐—ผ๐—ปโ€™๐˜ ๐˜€๐—ฎ๐˜ƒ๐—ฒ ๐˜†๐—ผ๐˜‚.

๐Ÿšจ ๐—›๐—ถ๐—ด๐—ต ๐—”๐˜ƒ๐—ฎ๐—ถ๐—น๐—ฎ๐—ฏ๐—ถ๐—น๐—ถ๐˜๐˜† ๐—ฎ๐—น๐—ผ๐—ป๐—ฒ ๐˜„๐—ผ๐—ปโ€™๐˜ ๐˜€๐—ฎ๐˜ƒ๐—ฒ ๐˜†๐—ผ๐˜‚.

HA handles failures like node crashes or AZ outages.

But what about:

โŒ Ransomware

โŒ Region-wide outages

โŒ Human error

๐Ÿ‘‰ Thatโ€™s ๐——๐—ถ๐˜€๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ ๐—ฅ๐—ฒ๐—ฐ๐—ผ๐˜ƒ๐—ฒ๐—ฟ๐˜† (๐——๐—ฅ) territory.

Real-world proof:

GitLab โ†’ redundancy โ‰  recovery

Maersk โ†’ one offline backup saved everything

Code Spaces โ†’ no DR = shutdown

๐ŸŽฏ ๐—›๐—” = ๐—ธ๐—ฒ๐—ฒ๐—ฝ ๐—ฟ๐˜‚๐—ป๐—ป๐—ถ๐—ป๐—ด

๐ŸŽฏ ๐——๐—ฅ = ๐—ฐ๐—ผ๐—บ๐—ฒ ๐—ฏ๐—ฎ๐—ฐ๐—ธ ๐—ณ๐—ฟ๐—ผ๐—บ ๐—ณ๐—ฎ๐—ถ๐—น๐˜‚๐—ฟ๐—ฒ

At RELIANOID, we design both:

โœ”๏ธ HA with clustering & failover

โœ”๏ธ DR with multi-region + immutable backups

Because uptime is goodโ€”but ๐—ฟ๐—ฒ๐˜€๐—ถ๐—น๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐—ถ๐˜€ ๐—ฏ๐—ฒ๐˜๐˜๐—ฒ๐—ฟ.

#HighAvailability #DisasterRecovery #Resilience #Cloud #DevOps #RELIANOID

https://www.relianoid.com/blog/beyond-high-availability-why-disaster-recovery-matters-and-how-relianoid-delivers/

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@varbear shared a link, 2ย months ago
FAUN.dev()

Why are top university websites serving p0rn? It comes down to shoddy housekeeping.

Researcher Alex Shakhov found scammers commandeering staleCNAMErecords. They hijack university subdomains (eg.berkeley.edu,columbia.edu,washu.edu) and serve p0rn and scam pages. Shakhov found hundreds of abused subdomains across at least34universities. He counted thousands of hijacked pages indexed .. read more ย 

Why are top university websites serving p0rn? It comes down to shoddy housekeeping.
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@varbear shared a link, 2ย months ago
FAUN.dev()

PostgreSQL MVCC, Byte by Byte

PostgreSQL's MVCC stores two 32-bit XIDs per tuple -xminandxmax. The transaction snapshot decides visibility per tuple. Updates append new tuples and mark the old withxmax.VACUUMreclaims versions only when no active snapshot can see them. Long-runningREPEATABLE READsnapshots pin versions and cause b.. read more ย 

PostgreSQL MVCC, Byte by Byte
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@varbear shared a link, 2ย months ago
FAUN.dev()

I Decompiled the White House's New App

A React Native app built withExpo SDK 54runsHermes. It talks to a WordPress REST backend and bundles a 5.5MB Hermes bytecode.Its WebView injects JavaScript to strip cookies, GDPR prompts, and paywall dialogs. The build includes OneSignal's fused-location pipeline, polling at 4.5 and 9.5 minutes and.. read more ย 

I Decompiled the White House's New App
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@varbear shared a link, 2ย months ago
FAUN.dev()

The AWS Lambda 'Kiss of Death'

A Galera writer node froze afterInnoDBundo history ballooned. PooledAWS Lambdaconnections left transactions open and pinned MVCC read views. The team killed stalled sessions, enabledinnodb_undo_log_truncate, and cappedinnodb_max_undo_log_size. They also set sessiontransaction_isolation=READ-COMMITTE.. read more ย 

The AWS Lambda 'Kiss of Death'
Unsloth is an open-source toolkit for training and fine-tuning large language models faster and with less memory than a standard Hugging Face stack. Its core library replaces PyTorch's default autograd with custom backpropagation kernels written in OpenAI's Triton language, which is where most of its speed and memory savings come from. It supports LoRA, QLoRA, full fine-tuning, reinforcement learning, pretraining, and 4-bit, 16-bit, and FP8 training, across more than 500 text, vision, audio, and embedding models.

The practical draw is hardware reach. QLoRA workflows in Unsloth let you fine-tune an 8B model on a single 12 GB consumer GPU, and the project headlines roughly 2x faster training with about 70 percent less VRAM versus baseline implementations, though the exact figures vary by model, GPU, and config. A 2026 update added faster mixture-of-experts training, with models like Qwen3-30B-A3B fine-tunable on about 17.5 GB of VRAM. It runs on NVIDIA (including Blackwell and DGX Spark), AMD, and Intel GPUs, with free Colab and Kaggle notebooks for trying it without local hardware.

It fits cleanly into the local-AI workflow. Unsloth integrates with Hugging Face transformers and TRL, and uses llama.cpp to save and run models, exporting to GGUF for Ollama or LM Studio as well as safetensors. As of 2026 it also ships Unsloth Studio, a local no-code GUI that covers the full lifecycle from dataset creation to training to running and comparing GGUF and safetensors models, with tool-calling, web search, and an OpenAI-compatible API, all running offline on Mac and Windows, with the core library under the Apache 2.0 license.