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@laura_garcia shared a post, 4 months ago
Software Developer, RELIANOID

🌐 ISO/IEC 27001 Compliance Alignment at RELIANOID

At RELIANOID, security isn’t just a feature—it’s part of our foundation. Both our organization and load balancing platform are strongly aligned with the ISO/IEC 27001:2022 ISMS framework and its Annex A controls. This means our clients in finance, healthcare, public sector, and enterprise environmen..

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@idjuric660 shared a post, 4 months ago
Technical Content Writer, Mailtrap

I Tested 6 Postmark Alternatives: Here’s What I Found

Let’s not kid ourselves, Postmark is a great email service inalmostevery regard. However, if you’re reading this, the chances are that it doesn’t fit your needs anymore, and you’d like to switch it up a little bit. Luckily, you’ve come to the right place! I’ve interviewed our very own deliverability..

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Database Sharding in 1 diagram and 204 words

Sharding breaks a heavyweight database into bite-sized chunks spread across servers. That means better scalability, less strain on any one node. The key? Picking the right shard key. Get that wrong, and you’re in cross-shard query hell. Modulo, range, and consistent hashing each slice the pie diff.. read more  

Database Sharding in 1 diagram and 204 words
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The great SQLite rewrite

Turso just dropped the alpha of itsRust-based SQLite rethink—rewritten from scratch to handle today’s mess:async APIs,built-in vector search, and actualconcurrent writes. Forget the old SQLite playbook. Turso’s version leans into modularity, bakes in deterministic tests, and still aims for SQLite-l.. read more  

The great SQLite rewrite
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AI Agents and Test Suites: Lessons from the Trenches

AI agents can help wrangletest suite maintenance—if you treat them likejunior devs. That means tight prompts, clear boundaries, and someone keeping an eye on them. Teams get better results when they feed agents sharp context and task them with small, scoped jobs instead of vague laundry lists... read more  

AI Agents and Test Suites: Lessons from the Trenches
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@faun shared a link, 4 months ago
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Why I chose OCaml as my primary language

OCaml’s grown up. Multicore support is in. So are user-defined effects. Under the hood, affine types, staged metaprogramming, and effect typing are steering it toward resource-safe programming—with actual thrust. Its type system still slaps: powerful modules, GADTs, algebraic types, and now first-c.. read more  

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Git Branching Strategies: A Comprehensive Guide

This guide breaks down the major Git branching strategies—GitFlow,GitHub Flow,GitLab Flow,Trunk-Based Development, and a few others that still show up in wild repos. Each one gets sized up by structure, use case, and trade-offs. Think: how big the team is, how fast releases go out, and how people l.. read more  

Git Branching Strategies: A Comprehensive Guide
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Deeper theories of program design

A sharp teardown ofWindows vs. Unix file deletion semanticslands on this: Windows leans on read-write locks; Unix rolls with a looser, non-blocking vibe—more likeweakly-isolated DB transactions. It trades consistency for concurrency, dodging locks even if it means the rules get fuzzy. The post zoom.. read more  

Deeper theories of program design
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Ship tools as standalone static binaries

OpenAI’s rewritingCodexinRust, ditching the oldTypeScriptversion. Why? To ship it as a single static binary—no messy installs, no glue code juggling. Just run. Rust cuts down runtime failures, trims the attack surface, and kills off toolchain sprawl. Less fragility. More control. System shift:Team.. read more  

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Lessons from scaling PostgreSQL queues to 100K events

RudderStack crankedPostgreSQLup to100K events/secas a queuing engine. The secret sauce: tight tuning of job partitioning, smarter indexing, tuned VACUUM timing, and compaction that didn't choke. Recursive CTEs stood in for loose index scans. Caching cut I/O repeats. They ditched byte slices to side.. read more  

Lessons from scaling PostgreSQL queues to 100K events
BigQuery is a cloud-native, serverless analytics platform designed to store, query, and analyze massive volumes of structured and semi-structured data using standard SQL. It separates storage from compute, automatically scales resources, and eliminates the need for infrastructure management, indexing, or capacity planning.

BigQuery is optimized for analytical workloads such as business intelligence, log analysis, data science, and machine learning. It supports real-time data ingestion via streaming, batch loading from cloud storage, and federated queries across external data sources like Cloud Storage, Bigtable, and Google Drive.

Query execution is distributed and highly parallel, enabling interactive performance even on petabyte-scale datasets. The platform integrates deeply with the Google Cloud ecosystem, including Looker for BI, Vertex AI for ML workflows, Dataflow for streaming pipelines, and BigQuery ML, which allows users to train and run machine learning models directly using SQL.

Built-in security features include fine-grained IAM controls, column- and row-level security, encryption by default, and audit logging. BigQuery follows a consumption-based pricing model, charging for storage and queries (on-demand or reserved capacity).